Samira Pouyanfar
Yimin Yang
Skip Abstract Section
Abstract
With the proliferation of online services and mobile technologies, the world has stepped into a multimedia big data era. A vast amount of research work has been done in the multimedia area, targeting different aspects of big data analytics, such as the capture, storage, indexing, mining, and retrieval of multimedia big data. However, very few research work provides a complete survey of the whole pine-line of the multimedia big data analytics, including the management and analysis of the large amount of data, the challenges and opportunities, and the promising research directions. To serve this purpose, we present this survey, which conducts a comprehensive overview of the state-of-the-art research work on multimedia big data analytics. It also aims to bridge the gap between multimedia challenges and big data solutions by providing the current big data frameworks, their applications in multimedia analyses, the strengths and limitations of the existing methods, and the potential future directions in multimedia big data analytics. To the best of our knowledge, this is the first survey that targets the most recent multimedia management techniques for very large-scale data and also provides the research studies and technologies advancing the multimedia analyses in this big data era.
- Veronika Abramova and Jorge Bernardino. 2013. NoSQL databases: MongoDB vs Cassandra. In Proceedings of the International C* Conference on Computer Science and Software Engineering. ACM, 14--22.Google Scholar
Digital Library
- Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan. 2016. YouTube-8M: A large-scale video classification benchmark. CoRR abs/1609.08675 (2016). http://arxiv.org/abs/1609.08675.Google Scholar
- Balázs Adamcsek, Gergely Palla, Illés J. Farkas, Imre Derényi, and Tamás Vicsek. 2006. CFinder: Locating cliques and overlapping modules in biological networks. Bioinformatics 22, 8 (2006), 1021--1023.Google ScholarDigital Library
- Fatima Binta Adamu, Adib Habbal, Suhaidi Hassan, R. Les Cottrell, Bebo White, and Ibrahim Abdullahi. 2016. A Survey on Big Data Indexing Strategies. Technical Report. SLAC National Accelerator Laboratory.Google Scholar
- Donald A. Adjeroh and Kingsley C. Nwosu. 1997. Multimedia database management -- Requirements and issues. IEEE MultiMedia 4, 3 (1997), 24--33.Google ScholarDigital Library
- Emily Adler. 2016. Social media engagement: The surprising facts about how much time people spend on the major social networks. Retrieved from http://www.businessinsider.com/social-media-engagement-statistics-2013-12.Google Scholar
- Divyakant Agrawal, Sudipto Das, and Amr El Abbadi. 2011. Big data and cloud computing: Current state and future opportunities. In Proceedings of the 14th International Conference on Extending Database Technology. 530--533.Google ScholarDigital Library
- Ian F. Akyildiz, Tommaso Melodia, and Kaushik R. Chowdhury. 2007. A survey on wireless multimedia sensor networks. Comput. Netw. 51, 4 (2007), 921--960.Google ScholarDigital Library
- Jesus Alcala-Fdez, Luciano Sanchez, Salvador Garcia, Maria Jose del Jesus, and others. 2009. KEEL: A software tool to assess evolutionary algorithms for data mining problems. Soft Comput. 13, 3 (2009), 307--318.Google ScholarDigital Library
- Victor Alvarez, Stefan Richter, Xiao Chen, and Jens Dittrich. 2015. A comparison of adaptive radix trees and hash tables. In Proceedings of the 31st IEEE International Conference on Data Engineering. 1227--1238.Google ScholarCross Ref
- Flora Amato, Francesco Colace, Luca Greco, Vincenzo Moscato, and Antonio Picariello. 2016. Semantic processing of multimedia data for e-government applications. J. Vis. Lang. Comput. 32 (2016), 35--41.Google ScholarDigital Library
- Flora Amato, Aniello De Santo, Francesco Gargiulo, Vincenzo Moscato, Fabio Persia, Antonio Picariello, and Silvestro Roberto Poccia. 2015. SemTree: An index for supporting semantic retrieval of documents. In Proceedings of the 31st IEEE International Conference on Data Engineering Workshops. 62--67.Google ScholarCross Ref
- AWS. 2016. Amazon S3. Retrieved October 16, 2016 from http://aws.amazon.com/s3/.Google Scholar
- Hadoop. 2016. Apache Hadoop. Retrieved April 29, 2016 http://hadoop.apache.org.Google Scholar
- Mahout. 2016. Apache Mahout. Retrieved May 7, 2016 from http://mahout.apache.org.Google Scholar
- Marcos D. Assunção, Rodrigo N. Calheiros, Silvia Bianchi, Marco A. S. Netto, and Rajkumar Buyya. 2015. Big data computing and clouds: Trends and future directions. J. Parallel Distrib. Comput. 79 (2015), 3--15.Google ScholarDigital Library
- Pradeep K. Atrey, M. Anwar Hossain, Abdulmotaleb El Saddik, and Mohan S. Kankanhalli. 2010. Multimodal fusion for multimedia analysis: A survey. Multimedia Syst. 16, 6 (2010), 345--379.Google ScholarDigital Library
- Mathieu Bastian, Sebastien Heymann, Mathieu Jacomy, and others. 2009. Gephi: An open source software for exploring and manipulating networks. In Third International Conference on Weblogs and Social Media. CA, USA, 361--362.Google Scholar
- Vladimir Batagelj and Andrej Mrvar. 2004. Pajek—Analysis and visualization of large networks. In Graph Drawing Software. Springer, Berlin, 77--103.Google Scholar
- Eric Bender. 2015. Big data in biomedicine. Nature 527, 7576 (2015), S1--S1.Google Scholar
- Rachid Benmokhtar and Benoit Huet. 2014. An ontology-based evidential framework for video indexing using high-level multimodal fusion. Multimedia Tools Appl. 73, 2 (2014), 663--689.Google ScholarDigital Library
- Jonathan Bergstrom, Mark Drovdahl, and Sinclair Temple. 2008. Wireless data capture and sharing system, such as image capture and sharing of digital camera images via a wireless cellular network and related tagging of images. (2008). US Patent App. 12/182,952.Google Scholar
- Chidansh Amitkumar Bhatt and Mohan S. Kankanhalli. 2011. Multimedia data mining: State of the art and challenges. Multimedia Tools Appl. 51, 1 (2011), 35--76.Google ScholarDigital Library
- Jingwen Bian, Yang Yang, and Tat-Seng Chua. 2013. Multimedia summarization for trending topics in microblogs. In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. ACM, 1807--1812.Google ScholarDigital Library
- Albert Bifet. 2013. Mining big data in real time. Informatica (Slovenia) 37, 1 (2013), 15--20.Google Scholar
- Albert Bifet, Geoff Holmes, Richard Kirkby, and Bernhard Pfahringer. 2010. MOA: Massive online analysis. J. Mach. Learn. Res. 11 (2010), 1601--1604.Google ScholarDigital Library
- Import.io. 2016. All the best big data tools and how to use them. Retrieved November 16, 2016 from https://www.import.io/post/all-the-best-big-data-tools-and-how-to-use-them/.Google Scholar
- Randal Bryant, Randy H. Katz, and Edward D. Lazowska. 2008. Big-data computing: Creating revolutionary breakthroughs in commerce, science and society. Retreived from https://pdfs.semanticscholar.org/65a8/b00f712ffd5c230bf0de6b9bd13923d20078.pdf.Google Scholar
- Hongming Cai, Boyi Xu, Lihong Jiang, and Athanasios V. Vasilakos. 2017. IoT-based big data storage systems in cloud computing: Perspectives and challenges. IEEE I-o-T J. 4, 1 (2017), 75--87.Google Scholar
- Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber. 2008. Bigtable: A distributed storage system for structured data. ACM Trans. Comput. Syst. 26, 2 (2008), 4:1--4:26.Google ScholarDigital Library
- Yung Fu Chang, C. S. Chen, and Hao Zhou. 2009. Smart phone for mobile commerce. Comput. Stand. Interfaces 31, 4 (2009), 740--747.Google ScholarDigital Library
- Thibaud Chardonnens. 2013. Big Data Analytics on High Velocity Streams: Specific Use Cases with Storm. Master’s thesis. Software Engineering Group, Department of Informatics, University of Fribourg, Switzerland.Google Scholar
- Kasturi Chatterjee and Shu-Ching Chen. 2006. Affinity hybrid tree: An indexing technique for content-based image retrieval in multimedia databases. In Proceedings of the 8th IEEE International Symposium on Multimedia. IEEE, 47--54.Google ScholarDigital Library
- Kasturi Chatterjee and Shu-Ching Chen. 2007. A novel indexing and access mechanism using affinity hybrid tree for content-based image retrieval in multimedia databases. Int. J. Semant. Comput. 1, 2 (2007), 147--170.Google ScholarCross Ref
- Kasturi Chatterjee and Shu-Ching Chen. 2008. Hierarchical affinity hybrid tree: A multidimensional index structure to organize videos and support content-based retrievals. In Proceedings of the IEEE International Conference on Information Reuse and Integration. IEEE, 435--440.Google ScholarCross Ref
- Kasturi Chatterjee and Shu-Ching Chen. 2010. HAH-tree: Towards a multidimensional index structure supporting different video modelling approaches in a video database management system. Int. J. Inf. Decis. Sci. 2, 2 (2010), 188--207.Google Scholar
- Dunren Che, Mejdl Safran, and Zhiyong Peng. 2013. From big data to big data mining: Challenges, issues, and opportunities. In Database Systems for Advanced Applications. Springer, Wuhan, China, 1--15.Google Scholar
- Chao Chen, Qiusha Zhu, Lin Lin, and Mei-Ling Shyu. 2013. Web media semantic concept retrieval via tag removal and model fusion. ACM Trans. Intell. Syst. Technol. 4, 4 (2013), 61:1--61:22.Google ScholarDigital Library
- CL Philip Chen and Chun-Yang Zhang. 2014. Data-intensive applications, challenges, techniques and technologies: A survey on big data. Inf. Sci. 275 (2014), 314--347.Google ScholarCross Ref
- Cindy Xinmin Chen. 2001. Data Models and Query Languages of Spatio-temporal Information. Ph.D. Dissertation. University of California Los Angeles.Google Scholar
- Lei Chen, Jianliang Xu, Christian S. Jensen, and Yafei Li. 2016. YASK: A why-not question answering engine for spatial keyword query services. Proc. VLDB Endow. 9, 13 (2016), 1501--1504.Google ScholarDigital Library
- Min Chen. 2014. A hierarchical security model for multimedia big data. Int. J. Multimedia Data Eng. Manage. 5, 1 (2014), 1--13.Google ScholarDigital Library
- Min Chen, Shu-Ching Chen, Mei-Ling Shyu, and Kasun Wickramaratna. 2006. Semantic event detection via multimodal data mining. IEEE Sign. Process. Mag. 23, 2 (2006), 38--46.Google ScholarCross Ref
- Min Chen, Shiwen Mao, and Yunhao Liu. 2014. Big data: A survey. Mobile Netw. Appl. 19, 2 (2014), 171--209.Google ScholarDigital Library
- Shu-Ching Chen. 2010. Multimedia databases and data management: A survey. Int. J. Multimedia Data Eng. Manage. 1, 1 (2010), 1--11.Google ScholarDigital Library
- Shu-Ching Chen and Rangasami L. Kashyap. 2001. A spatio-temporal semantic model for multimedia database systems and multimedia information systems. IEEE Trans. Knowl. Data Eng. 13, 4 (2001), 607--622.Google ScholarDigital Library
- Shu-Ching Chen, Rangasami Laksminarayana Kashyap, and Arif Ghafoor. 2000. Semantic Models for Multimedia Database Searching and Browsing. Vol. 21. Kluwer Academic Publishers, MA.Google Scholar
- Shu-Ching Chen, Stuart H. Rubin, Mei-Ling Shyu, and Chengcui Zhang. 2006. A dynamic user concept pattern learning framework for content-based image retrieval. IEEE Trans. Syst. Man. Cybernet. C 36, 6 (2006), 772--783.Google ScholarDigital Library
- Shu-Ching Chen, Mei-Ling Shyu, Srinivas Peeta, and Chengcui Zhang. 2003. Learning-based spatio-temporal vehicle tracking and indexing for transportation multimedia database systems. IEEE Trans. Intell. Trans. Syst. 4, 3 (2003), 154--167.Google ScholarDigital Library
- Shu-Ching Chen, Mei-Ling Shyu, and Chengcui Zhang. 2005. Innovative shot boundary detection for video indexing. In Video Data Management and Information Retrieval. Idea Group Publishing, Hershey, PA, 217--236.Google Scholar
- Shu-Ching Chen, Mei-Ling Shyu, Chengcui Zhang, and Min Chen. 2006. A multimodal data mining framework for soccer goal detection based on decision tree logic. Int. J. Comput. Appl. Technol. 27, 4 (2006), 312--323.Google ScholarDigital Library
- Shu-Ching Chen, Mei-Ling Shyu, Chengcui Zhang, Lin Luo, and Min Chen. 2003. Detection of soccer goal shots using joint multimedia features and classification rules. In Proceedings of the 4th International Workshop on Multimedia Data Mining. 36--44.Google Scholar
- Shu-Ching Chen, Mei-Ling Shyu, Chengcui Zhang, and Jeff Strickrott. 2001b. Multimedia data mining for traffic video sequences. In Proceedings of the 2nd International Workshop on Multimedia Data Mining. 78--86.Google Scholar
- Shu-Ching Chen, Mei-Ling Shyu, Cheng-Cui Zhang, and Rangasami L. Kashyap. 2001a. Video scene change detection method using unsupervised segmentation and object tracking. In Proceedings of the IEEE International Conference on Multimedia and Expo. IEEE, 15.Google Scholar
- Shu-Ching Chen, Srinivas Sista, Mei-Ling Shyu, and Rangasami L. Kashyap. 1999. Augmented transition networks as video browsing models for multimedia databases and multimedia information systems. In Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence. IEEE, 175--182.Google Scholar
- Xin Chen, Chengcui Zhang, Shu-Ching Chen, and Min Chen. 2005. A latent semantic indexing based method for solving multiple instance learning problem in region-based image retrieval. In Proceedings of the 7th IEEE International Symposium on Multimedia. IEEE, 37--45.Google Scholar
- Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, and Evan Shelhamer. 2014. cuDNN: Efficient primitives for deep learning. CoRR abs/1410.0759 (2014).Google Scholar
- Ming Cheung, James She, and Zhanming Jie. 2015. Connection discovery using big data of user-shared images in social media. IEEE Trans. Multimedia 17, 9 (2015), 1417--1428.Google ScholarDigital Library
- Jaegul Choo and Haesun Park. 2013. Customizing computational methods for visual analytics with big data. Comput. Graph. Appl. 33, 4 (2013), 22--28.Google ScholarDigital Library
- Tat-Seng Chua, Jinhui Tang, Richang Hong, Haojie Li, Zhiping Luo, and Yantao Zheng. 2009. NUS-WIDE: A real-world web image database from national university of singapore. In Proceedings of the ACM International Conference on Image and Video Retrieval. 48:1--48:9.Google ScholarDigital Library
- Yang Cong, Shuai Wang, Baojie Fan, Yunsheng Yang, and Haibin Yu. 2016. UDSFS: Unsupervised deep sparse feature selection. Neurocomputing 196 (2016), 150--158.Google ScholarDigital Library
- Marshall Copeland, Julian Soh, Anthony Puca, Mike Manning, and David Gollob. 2015. Overview of microsoft azure services. In Microsoft Azure. Springer, 27--69.Google Scholar
- Michael Cox and David Ellsworth. 1997. Application-controlled demand paging for out-of-core visualization. In Proceedings of the 8th Conference on Visualization’97. IEEE Computer Society Press, 235--244.Google ScholarDigital Library
- Henggang Cui, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, and Eric P. Xing. 2016. GeePS: Scalable deep learning on distributed GPUs with a GPU-specialized parameter server. In Proceedings of the 11th European Conference on Computer Systems. ACM, 4:1--4:16.Google Scholar
- DataMelt. 2016. DataMelt: Computation and visualization environment. Retrieved May 7, 2016 from http://jwork.org/dmelt/.Google Scholar
- James Davidson, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He, Mike Lambert, Blake Livingston, and others. 2010. The YouTube video recommendation system. In Proceedings of the 4th ACM Conference on Recommender Systems. ACM, 293--296.Google ScholarDigital Library
- Shuvashis Dey, Arpan Chakraborty, Sourav Naskar, and Prasant Misra. 2012. Smart city surveillance: Leveraging benefits of cloud data stores. In Proceedings of the IEEE 37th Conference on Local Computer Networks Workshops. IEEE, 868--876.Google ScholarCross Ref
- Jean Pierre Dijcks. 2012. Oracle: Big data for the enterprise. Retrieved from http://www.oracle.com/us/products/database/big-data-for-enterprise-519135.pdf.Google Scholar
- Shengyong Ding, Liang Lin, Guangrun Wang, and Hongyang Chao. 2015. Deep feature learning with relative distance comparison for person re-identification. Pattern Recogn. 48, 10 (2015), 2993--3003.Google ScholarDigital Library
- Trinh Minh Tri Do, Jan Blom, and Daniel Gatica-Perez. 2011. Smartphone usage in the wild: A large-scale analysis of applications and context. In Proceedings of the 13th International Conference on Multimodal Interfaces. ACM, 353--360.Google Scholar
- Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell. 2013. Decaf: A deep convolutional activation feature for generic visual recognition. CoRR abs/1310.1531 (2013). http://arxiv.org/abs/1310.1531.Google Scholar
- Charalampos Doukas, Thomas Pliakas, and Ilias Maglogiannis. 2010. Mobile healthcare information management utilizing cloud computing and android OS. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE, 1037--1040.Google ScholarCross Ref
- Ahmed Eldawy and Mohamed F. Mokbel. 2015. SpatialHadoop: A MapReduce framework for spatial data. In Proceedings of the IEEE 31st International Conference on Data Engineering. IEEE, 1352--1363.Google Scholar
- StatisticBrain. 2016. Facebook statistics. Retrieved April 7, 2016 from http://www.statisticbrain.com/facebook-statistics/.Google Scholar
- Facebook.Com. 2016. Facebook. Retrieved May 20, 2016 from https://www.facebook.com/.Google Scholar
- Jianqing Fan, Fang Han, and Han Liu. 2014. Challenges of big data analysis. Natl. Sci. Rev. 1, 2 (2014), 293--314.Google ScholarCross Ref
- Ruogu Fang, Samira Pouyanfar, Yimin Yang, Shu-Ching Chen, and SS Iyengar. 2016. Computational health informatics in the big data age: A survey. ACM Comput. Surv. 49, 1 (2016), 12.Google ScholarDigital Library
- Fausto Fleites, Haohong Wang, and Shu-Ching Chen. 2015a. TV shopping via multi-cue product detection. IEEE Trans. Emerg. Top. Comput. 3, 2 (2015), 161--171.Google ScholarCross Ref
- Fausto C. Fleites and Shu-Ching Chen. 2013. Efficient content-based multimedia retrieval using novel indexing structure in PostgreSQL. In Proceedings of the IEEE International Symposium on Multimedia. IEEE, 500--501.Google Scholar
- Fausto C. Fleites, Shu-Ching Chen, and Kasturi Chatterjee. 2011. AH+-tree: An efficient multimedia indexing structure for similarity queries. In Proceedings of the IEEE International Symposium on Multimedia. IEEE, 69--76.Google ScholarDigital Library
- Fausto C. Fleites, Shu-Ching Chen, and Kasturi Chatterjee. 2012. A semantic index structure for multimedia retrieval. Int. J. Semantic Comput. 6, 2 (2012), 155--178.Google ScholarCross Ref
- Fausto C. Fleites, Hsin-Yu Ha, Yimin Yang, and Shu-Ching Chen. 2014. Large-scale correlation-based semantic classification using MapReduce. In Cloud Computing and Digital Media: Fundamentals, Techniques, and Applications. Chapman and Hall/CRC, 169--190.Google Scholar
- Fausto C. Fleites, Haohong Wang, and Shu-Ching Chen. 2015b. Enabling enriched TV shopping experience via computational and temporal aware view-centric multimedia abstraction. IEEE Trans. Multimedia 17, 7 (2015), 1068--1080.Google ScholarDigital Library
- Flickr.Com. 2016. Flickr. Retrieved May 20, 2016 from https://www.flickr.com/.Google Scholar
- Foursquare.Com. 2016. Foursquare statistics. Retrieved April 8, 2016 from https://foursquare.com/about.Google Scholar
- Borivoje Furht and Armando Escalante. 2010. Handbook of Cloud Computing. Vol. 3. Springer.Google ScholarDigital Library
- Amir Gandomi and Murtaza Haider. 2015. Beyond the hype: Big data concepts, methods, and analytics. Int. J. Inf. Manage. 35, 2 (2015), 137--144.Google ScholarDigital Library
- Abdullah Gani, Aisha Siddiqa, Shahaboddin Shamshirband, and Fariza Hanum. 2016. A survey on indexing techniques for big data: Taxonomy and performance evaluation. Knowl. Inf. Syst. 46, 2 (2016), 241--284.Google ScholarDigital Library
- Lianli Gao, Jingkuan Song, Xingyi Liu, Junming Shao, Jiajun Liu, and Jie Shao. 2017. Learning in high-dimensional multimedia data: The state of the art. Multimedia Syst. 23, 3 (2017), 303--313.Google ScholarDigital Library
- Salvador García, Julián Luengo, and Francisco Herrera. 2015. Data Preprocessing in Data Mining. Vol. 72. Springer.Google ScholarDigital Library
- IGSR. 2016. IGSR and the 1000 Genomes Project. Retrieved December 21, 2017 from http://www.internationalgenome.org.Google Scholar
- Ivan Giangreco, Ihab Al Kabary, and Heiko Schuldt. 2014. ADAM-A database and information retrieval system for big multimedia collections. In Proceedings of the IEEE International Congress on Big Data. IEEE, 406--413.Google ScholarDigital Library
- Tim Gollub, Michael Volske, Matthias Hagen, and Bernardo Stein. 2014. Dynamic taxonomy composition via keyqueries. In Proceedings of the IEEE/ACM Joint Conference on Digital Libraries. IEEE, 39--48.Google ScholarCross Ref
- Yihong Gong and Wei Xu. 2007. Machine Learning for Multimedia Content Analysis. Vol. 30. Springer Science 8 Business Media.Google Scholar
- Google.Com. 2016. Google statistics. Retrieved April 8, 2016 from https://www.google.com/.Google Scholar
- Kehua Guo, Wei Pan, Mingming Lu, Xiaoke Zhou, and Jianhua Ma. 2015. An effective and economical architecture for semantic-based heterogeneous multimedia big data retrieval. J. Syst. Softw. 102 (2015), 207--216.Google ScholarDigital Library
- Ralf Hartmut Güting and Markus Schneider. 2005. Moving Objects Databases. Morgan Kaufmann.Google Scholar
- Hsin-Yu Ha, Shu-Ching Chen, and Mei-Ling Shyu. 2015. Negative-based sampling for multimedia retrieval. In Proceedings of the IEEE International Conference on Information Reuse and Integration. IEEE, 64--71.Google ScholarDigital Library
- Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. 2009. The WEKA data mining software: An update. ACM SIGKDD Explor. Newslett. 11, 1 (2009), 10--18.Google ScholarDigital Library
- Jiawei Han, Micheline Kamber, and Jian Pei. 2011. Data Mining: Concepts and Techniques. Morgan Kaufmann.Google ScholarDigital Library
- Ibrahim Abaker Targio Hashem, Victor Chang, Nor Badrul Anuar, Kayode Adewole, Ibrar Yaqoob, Abdullah Gani, Ejaz Ahmed, and Haruna Chiroma. 2016. The role of big data in smart city. Int. J. Inf. Manage. 36, 5 (2016), 748--758.Google ScholarDigital Library
- Ibrahim Abaker Targio Hashem, Ibrar Yaqoob, Nor Badrul Anuar, Salimah Mokhtar, Abdullah Gani, and Samee Ullah Khan. 2015. The rise of “big data” on cloud computing: Review and open research issues. Inf. Syst. 47 (2015), 98--115.Google ScholarDigital Library
- Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 770--778.Google ScholarCross Ref
- Joseph M. Hellerstein, Jeffrey F. Naughton, and Avi Pfeffer. 1995. Generalized search trees for database systems. In Proceedings of the 21th International Conference on Very Large Data Bases. Morgan Kaufmann, Zurich, Switzerland, 562--573.Google ScholarDigital Library
- Scott Hendrickson. 2010. Getting started with Hadoop with Amazon’s elastic MapReduce. Retrieved April 7, 2016 from https://www.slideshare.net/DrSkippy27/amazon-elastic-map-reduce-getting-started-with-hadoop.Google Scholar
- Li-Yung Ho, Jan-Jan Wu, and Pangfeng Liu. 2012. Distributed graph database for large-scale social computing. In Proceedings of the IEEE 5th International Conference on Cloud Computing. IEEE Computer Society, 455--462.Google ScholarDigital Library
- Steven C. H. Hoi, Jialei Wang, Peilin Zhao, and Rong Jin. 2012. Online feature selection for mining big data. In Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications. ACM, 93--100.Google ScholarDigital Library
- Han Hu, Yonggang Wen, Tat-Seng Chua, and Xuelong Li. 2014. Toward scalable systems for big data analytics: A technology tutorial. IEEE Access 2 (2014), 652--687.Google ScholarCross Ref
- Weiming Hu, Nianhua Xie, Li Li, Xianglin Zeng, and Stephen Maybank. 2011. A survey on visual content-based video indexing and retrieval. IEEE Trans. Syst. Man Cybernet. C 41, 6 (2011), 797--819.Google ScholarDigital Library
- Tiejun Huang. 2014. Surveillance video: The biggest big data. Comput. Now 7, 2 (2014), 82--91.Google Scholar
- iCloud.Com. 2016. iCloud. Retrieved May 20, 2016 from https://www.icloud.com/.Google Scholar
- Image-net.Org. 2016. ImageNet. Retrieved April 18, 2016 from http://image-net.org/about-stats.Google Scholar
- Instagram.Com. 2016. Instagram. Retrieved May 20, 2016 from https://www.instagram.com/?hl=en.Google Scholar
- Fatima EL Jamiy, Abderrahmane Daif, Mohamed Azouazi, and Abdelaziz Marzak. 2015. The potential and challenges of big data-Recommendation systems next level application. CoRR abs/1501.03424 (2015). http://arxiv.org/abs/1501.03424.Google Scholar
- Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. 2014. Caffe: Convolutional architecture for fast feature embedding. In Proceedings of the ACM International Conference on Multimedia. 675--678.Google ScholarDigital Library
- Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Konda, Sébastien Jean, Pierre Froumenty, Yann Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, and Yoshua Bengio. 2016. EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10, 2 (2016), 99--111.Google ScholarCross Ref
- U. Kang, Duen Horng Chau, and Christos Faloutsos. 2012. Pegasus: Mining billion-scale graphs in the cloud. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. 5341--5344.Google ScholarCross Ref
- Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei. 2014. Large-scale video classification with convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 1725--1732.Google ScholarDigital Library
- Amreen Khan and KamalKant Ahirwar. 2011. Mobile cloud computing as a future of mobile multimedia database. Int. J. Comput. Sci. Commun. 2, 1 (2011), 219--221.Google Scholar
- Nawsher Khan, Ibrar Yaqoob, Ibrahim Abaker Targio Hashem, Zakira Inayat, Waleed Kamaleldin Mahmoud Ali, Muhammad Alam, Muhammad Shiraz, and Abdullah Gani. 2014. Big data: Survey, technologies, opportunities, and challenges. Sci. World J. 2014 (2014), 18.Google Scholar
- KNIME.Org. 2016. KNIME. Retrieved May 7, 2016 from https://www.knime.org/.Google Scholar
- Ioannis Kompatsiaris, Sotiris Diplaris, and Symeon Papadopoulos. 2014. Social data and multimedia analytics for news and events applications. In Proceedings of the International Conference on Database Theory Workshops Jointly with Extending Database Technology. CEUR-WS, 280--281.Google Scholar
- Robert Kosara and Jock Mackinlay. 2013. Storytelling: The next step for visualization. IEEE Comput. 46, 5 (2013), 44--50.Google ScholarDigital Library
- Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems. Curran Associates, Inc., 1097--1105.Google ScholarDigital Library
- Alexandros Labrinidis and H. V. Jagadish. 2012. Challenges and opportunities with big data. Proc. VLDB Endow. 5, 12 (2012), 2032--2033.Google ScholarDigital Library
- Griffin Lacey, Graham W. Taylor, and Shawki Areibi. 2016. Deep learning on FPGAs: Past, present, and future. CoRR abs/1602.04283 (2016). http://arxiv.org/abs/1602.04283.Google Scholar
- Sara Landset, Taghi M. Khoshgoftaar, Aaron N. Richter, and Tawfiq Hasanin. 2015. A survey of open source tools for machine learning with big data in the Hadoop ecosystem. J. Big Data 2, 1 (2015), 1--36.Google ScholarCross Ref
- Nicholas D. Lane, Emiliano Miluzzo, Hong Lu, Daniel Peebles, Tanzeem Choudhury, and Andrew T. Campbell. 2010. A survey of mobile phone sensing. IEEE Commun. Mag. 48, 9 (2010), 140--150.Google ScholarDigital Library
- Juha K. Laurila, Daniel Gatica-Perez, Imad Aad, Olivier Bornet, Trinh-Minh-Tri Do, Olivier Dousse, Julien Eberle, Markus Miettinen, and others. 2012. The mobile data challenge: Big data for mobile computing research. In Proceedings of the Workshop on the Nokia Mobile Data Challenge in Conjunction with the 10th International Conference on Pervasive Computing. 1--8.Google Scholar
- Quoc V. Le. 2013. Building high-level features using large scale unsupervised learning. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. 8595--8598.Google ScholarCross Ref
- LEADTOOLS. 2016. Multimedia Capture SDK Technology. Retrieved April 26, 2016 from https://www.leadtools.com/sdk/multimedia/capture.Google Scholar
- Taesung Lee, Jin-woo Park, Sanghoon Lee, Seung-won Hwang, Sameh Elnikety, and Yuxiong He. 2015. Processing and optimizing main memory spatial-keyword queries. Proc. VLDB Endow. 9, 3 (2015), 132--143.Google ScholarDigital Library
- Lin Lin, Guy Ravitz, Mei-Ling Shyu, and Shu-Ching Chen. 2008. Effective feature space reduction with imbalanced data for semantic concept detection. In Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing. 262--269.Google ScholarDigital Library
- Dianting Liu, Yilin Yan, Mei-Ling Shyu, Guiru Zhao, and Min Chen. 2015. Spatio-temporal analysis for human action detection and recognition in uncontrolled environments. Int. J. Multimedia Data Eng. Manage. 6, 1 (2015), 1--18.Google ScholarDigital Library
- Philipos C. Loizou. 2013. Speech Enhancement: Theory and Practice. CRC Press, Boca Raton, FL.Google ScholarCross Ref
- Yucheng Low, Joseph E. Gonzalez, Aapo Kyrola, Danny Bickson, Carlos E. Guestrin, and Joseph Hellerstein. 2014. Graphlab: A new framework for parallel machine learning. CoRR abs/1408.2041 (2014). http://arxiv.org/abs/1408.2041.Google Scholar
- Zhe-Ming Lu and Yong Shi. 2013. Fast video shot boundary detection based on SVD and pattern matching. IEEE Trans. Image Process. 22, 12 (2013), 5136--5145.Google ScholarDigital Library
- Jian Luo. 2017. Multimedia big data frame combination storage strategy based on virtual space distortion. Int. J. Online Eng. 13, 2 (2017), 119--130.Google ScholarCross Ref
- Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, and Irwin King. 2011. Recommender systems with social regularization. In Procedings of the 5th ACM International Conference on Web Search and Data Mining. AC, 287--296.Google ScholarDigital Library
- Kaleem Razzaq Malik, Tauqir Ahmad, Muhammad Farhan, Muhammad Aslam, Sohail Jabbar, Shehzad Khalid, and Mucheol Kim. 2016. Big-data: Transformation from heterogeneous data to semantically-enriched simplified data. Multimedia Tools Appl. 75, 20 (2016), 12727--12747.Google ScholarDigital Library
- James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and Angela H. Byers. 2011. Big Data: The Next Frontier for Innovation, Competition, and Productivity. Technical Report. McKinsey Global Institute.Google Scholar
- Jonathan Masci, Ueli Meier, Dan Cireşan, and Jürgen Schmidhuber. 2011. Stacked convolutional auto-encoders for hierarchical feature extraction. In Artificial Neural Networks and Machine Learning. Springer, 52--59.Google Scholar
- Ayaka Matsui, Satoshi Nishimura, and Seiichiro Katsura. 2014. A classification method of motion database using hidden Markov model. In Proceedings of the 23rd International Symposium on Industrial Electronics. IEEE, 2232--2237.Google ScholarCross Ref
- Lucas Mearian. 2012. By 2020, there will be 5,200 GB of data for every person on the Earth. Retreived April 5, 2016 from http://www.computerworld.com/article/2493701/data-center/by-2020-there-will-be-5-200-gb-of-data-for-every-person-on-earth.html.Google Scholar
- MediaEval. 2015. MediaEval 2015 - Multimedia Benchmark Workshop. Retrieved April 18, 2016 from http://ceur-ws.org/Vol-1436/.Google Scholar
- David Mera, Michal Batko, and Pavel Zezula. 2017. Speeding up the multimedia feature extraction: A comparative study on the big data approach. Multimedia Tools Appl. 76, 5 (2017), 7497--7517.Google ScholarDigital Library
- Katina Michael and Roger Clarke. 2013. Location and tracking of mobile devices: Überveillance stalks the streets. Comput. Law Secur. Rev. 29, 3 (2013), 216--228.Google ScholarCross Ref
- Katina Michael and Keith Miller. 2013. Big data: New opportunities and new challenges [guest editors’ introduction]. Computer 46, 6 (2013), 22--24.Google ScholarDigital Library
- MLlib. 2016. Machine Learning Library. Retrieved May 7, 2016 from http://spark.apache.org/docs/latest/mllib-guide.html.Google Scholar
- MongoDB.Com. 2016. MongoDB. Retrieved November 16, 2016 from https://www.mongodb.com/.Google Scholar
- Julián Moreno-Schneider, Paloma Martínez, and José L. Martínez-Fernández. 2017. Combining heterogeneous sources in an interactive multimedia content retrieval model. Exp. Syst. Appl. 69 (2017), 201--213.Google ScholarCross Ref
- Neo4j.Com. 2016. Neo4j. Retrieved October 16, 2016 from https://neo4j.com/.Google Scholar
- Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, and Andrew Y. Ng. 2011. Multimodal deep learning. In Proceedings of the 28th International Conference on Machine Learning. 689--696.Google Scholar
- Oracle 2015. Digital video archiving: The evolving reality of any content, anywhere, anytime. Retrieved April 26, 2016 from http://www.oracle.com/us/products/digital-video-archiving-wp-2549967.pdf.Google Scholar
- Amalia Panteli, Chrisa Tsinaraki, Lemonia Ragia, Fotis Kazasis, and Stavros Christodoulakis. 2011. MObile multimedia event capturing and visualization (MOME). In Proceedings of the 5th FTRA International Conference on Multimedia and Ubiquitous Engineering. 101--106.Google ScholarDigital Library
- James Philbin, Ondřej Chum, Michael Isard, Josef Sivic, and Andrew Zisserman. 2007. Object retrieval with large vocabularies and fast spatial matching. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1--8.Google ScholarCross Ref
- Samira Pouyanfar and Shu-Ching Chen. 2016. Semantic event detection using ensemble deep learning. In Proceedings of the IEEE International Symposium on MultimediaI. IEEE, 203--208.Google ScholarCross Ref
- Samira Pouyanfar and Shu-Ching Chen. 2017. Automatic video event detection for imbalance data using enhanced ensemble deep learning. Int. J. Semant. Comput. 11, 01 (2017), 85--109.Google ScholarCross Ref
- Zoltán Prekopcsák, Gabor Makrai, Tamas Henk, and Csaba Gaspar-Papanek. 2011. Radoop: Analyzing big data with Rapidminer and Hadoop. In Proceedings of the 2nd RapidMiner Community Meeting and Conference. Citeseer, 865--874.Google Scholar
- Enislay Ramentol, Yailé Caballero, Rafael Bello, and Francisco Herrera. 2012. SMOTE-RSB*: A hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory. Knowl. Inf. Syst. 33, 2 (2012), 245--265.Google ScholarDigital Library
- RapidMiner.Com. 2016. RapidMiner. Retrieved May 7, 2016 from https://rapidminer.com/.Google Scholar
- Priyanka Rawat, Kamal Deep Singh, Hakima Chaouchi, and Jean Marie Bonnin. 2014. Wireless sensor networks: A survey on recent developments and potential synergies. J. Supercomput. 68, 1 (2014), 1--48.Google ScholarDigital Library
- Daniel A. Reed, Dennis B. Gannon, and James R. Larus. 2012. Imagining the future: Thoughts on computing. IEEE Comput. 45, 1 (2012), 25--30.Google ScholarDigital Library
- Nathan Regola, David A. Cieslak, and Nitesh V. Chawla. 2014. The need to consider hardware selection when designing big data applications supported by metadata. In Big Data Management, Technologies, and Applications. IGI Global, 381--396.Google Scholar
- Francesco Ricci. 2010. Mobile recommender systems. Inf. Technol. Tour. 12, 3 (2010), 205--231.Google ScholarCross Ref
- Petar Ristoski and Heiko Paulheim. 2014. Feature selection in hierarchical feature spaces. In Discovery Science. Springer, 288--300.Google Scholar
- Daniel A. Rodríguez-Silva, Lilian Adkinson-Orellana, F. J. Gonz’lez-Castano, I. Armino-Franco, and D. Gonz’lez-Martinez. 2012. Video surveillance based on cloud storage. In Proceedings of the IEEE 5th International Conference on Cloud Computing. IEEE, 991--992.Google Scholar
- Noha A. Sakr, Ali I. ELdesouky, and Hesham Arafat. 2016. An efficient fast-response content-based image retrieval framework for big data. Comput. Electr. Eng. 54 (2016), 522--538.Google ScholarDigital Library
- Salam Sakr, An Liu, Daniel M. Batista, and Mohammad Alomari. 2011. A survey of large scale data management approaches in cloud environments. Commun. Surv. Tutor. 13, 3 (2011), 311--336.Google ScholarCross Ref
- Neil J. Salkind. 2006. Encyclopedia of Measurement and Statistics. Vol. 1. Sage, Thousand Oaks, CA.Google Scholar
- Arjmand Samuel, Muhammad I. Sarfraz, Hammad Haseeb, Saleh Basalamah, and Arif Ghafoor. 2015. A framework for composition and enforcement of privacy-aware and context-driven authorization mechanism for multimedia big data. IEEE Trans. Multimedia 17, 9 (2015), 1484--1494.Google ScholarDigital Library
- Eric E. Schadt, Michael D. Linderman, Jon Sorenson, Lawrence Lee, and Garry P. Nolan. 2010. Computational solutions to large-scale data management and analysis. Nat. Rev. Genet. 11, 9 (2010), 647--657.Google ScholarCross Ref
- Gerald Schuller, Matthias Gruhne, and Tanja Friedrich. 2011. Fast audio feature extraction from compressed audio data. IEEE J. Select. Top. Sign. Process. 5, 6 (2011), 1262--1271.Google ScholarCross Ref
- Andrei Seres. 2010. Three database management systems (DBMS) compared. Open Source Sci. J. 2, 4 (2010), 65--82.Google Scholar
- Mei-Ling Shyu, Shu-Ching Chen, Qibin Sun, and Heather Yu. 2007. Overview and future trends of multimedia research for content access and distribution. Int. J. Semant. Comput. 1, 01 (2007), 29--66.Google ScholarCross Ref
- Mei-Ling Shyu, Zongxing Xie, Min Chen, and Shu-Ching Chen. 2008. Video semantic event/concept detection using a subspace-based multimedia data mining framework. IEEE Trans. Multimedia 10, 2 (2008), 252--259.Google ScholarDigital Library
- Aisha Siddiqa, Ibrahim Abaker Targio Hashem, Ibrar Yaqoob, Mohsen Marjani, Shahabuddin Shamshirband, Abdullah Gani, and Fariza Nasaruddin. 2016. A survey of big data management: Taxonomy and state-of-the-art. J. Netw. Comput. Appl. 71 (2016), 151--166.Google ScholarDigital Library
- Sam B. Siewert. 2013. Big data in the cloud - Data velocity, volume, variety and veracity. https://www.ibm.com/developerworks/library/bd-bigdatacloud/index.html.Google Scholar
- John R. Smith. 2013. Riding the multimedia big data wave. In Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, Dublin, Ireland, 1--2.Google ScholarDigital Library
- Thurston Smith. 2015. Social media and big data statistics. Retreived April 5, 2015 from https://www.youtube.com/watch?v=hoZ7YhfRchw.Google Scholar
- Houbing Song, Pablo Basanta-Val, Anthony Steed, Minho Jo, and others. 2017. Next-generation big data analytics: State of the art, challenges, and future research topics. IEEE Trans. Industr. Inf. 13, 4 (2017), 1891--1899. DOI:http://dx.doi.org/10.1109/TII.2017.2650204Google ScholarCross Ref
- Jingkuan Song, Yang Yang, Yi Yang, Zi Huang, and Heng Tao Shen. 2013. Inter-media hashing for large-scale retrieval from heterogeneous data sources. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data. 785--796.Google ScholarDigital Library
- Statista.Com. 2015. Statistics and facts about Big Data. Retrieved April 5, 2016 from http://www.statista.com/topics/1464/big-data/.Google Scholar
- Statisticbrain.Com. 2016. Twitter statistics. Retrieved April 8, 2016 from http://www.statisticbrain.com/twitter-statistics/.Google Scholar
- Eliza Strickland. 2013. The gene machine and me. IEEE Spectr. 50, 3 (2013), 30--59.Google ScholarCross Ref
- Subashini Subashini and Veeraruna Kavitha. 2011. A survey on security issues in service delivery models of cloud computing. J. Netw. Comput. Appl. 34, 1 (2011), 1--11.Google ScholarDigital Library
- Sreenivas R. Sukumar, Ramachandran Natarajan, and Regina K. Ferrell. 2015. Quality of big data in health care. Int. J. Health Care Qual. Assur. 28, 6 (2015), 621--634.Google ScholarCross Ref
- Cees H. Taal, Richard C. Hendriks, and Richard Heusdens. 2012. A speech preprocessing strategy for intelligibility improvement in noise based on a perceptual distortion measure. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 4061--4064.Google ScholarCross Ref
- Mingkui Tan, Ivor W. Tsang, and Li Wang. 2014. Towards ultrahigh dimensional feature selection for big data. J. Mach. Learn. Res. 15, 1 (2014), 1371--1429.Google ScholarDigital Library
- Weimin Tan, Bo Yan, Ke Li, and Qi Tian. 2016. Image retargeting for preserving robust local feature: Application to mobile visual search. IEEE Trans. Multimedia 18, 1 (2016), 128--137.Google ScholarDigital Library
- R Core Team. 2014. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
- Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li. 2016. YFCC100M: The new data in multimedia research. Commun. ACM 59, 2 (2016), 64--73.Google ScholarDigital Library
- Yonghong Tian, Shu-Ching Chen, Mei-Ling Shyu, Tiejun Huang, Phillip Sheu, and Alberto Del Bimbo. 2015. Multimedia big data. IEEE MultiMedia 22, 3 (2015), 93--95.Google ScholarCross Ref
- Tiny. 2016. Tiny images dataset. Retreived April 18, 2016 from http://horatio.cs.nyu.edu/mit/tiny/data/index.html.Google Scholar
- Ankit Toshniwal, Siddarth Taneja, Amit Shukla, Karthik Ramasamy, and others. 2014. Storm@ twitter. In Proceedings of the ACM SIGMOD International Conference on Management of Data. 147--156.Google ScholarDigital Library
- Nicolas Touchard and Jean-Marie Vau. 2004. Method for sharing multimedia data. (2004). US Patent App. 10/550,115.Google Scholar
- Trecvid. 2016. Trecvid 2016-AVS. Retreived April 18, 2016 from http://www-nlpir.nist.gov/projects/tv2016/tv2016.html#avs.Google Scholar
- Chun-Wei Tsai, Chin-Feng Lai, Han-Chieh Chao, and Athanasios V. Vasilakos. 2015. Big data analytics: A survey. J. Big Data 2, 1 (2015), 1--32.Google ScholarCross Ref
- Zeynep Tufekci. 2014. Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In Proceedings of the Eighth International Conference on Weblogs and Social Media. Michigan, USA, 505--514.Google Scholar
- Twitter.Com. 2016. Twitter. Retrieved May 20, 2016 from https://twitter.com/?lang=en.Google Scholar
- Alper Kursat Uysal and Serkan Gunal. 2014. The impact of preprocessing on text classification. Inf. Process. Manage. 50, 1 (2014), 104--112.Google ScholarDigital Library
- Stef Van Buuren. 2012. Flexible Imputation of Missing Data. CRC Press, Boca Raton, FL.Google Scholar
- Fritz Venter and Andrew Stein. 2012. Images 8 videos: Really big data. Analytics Magazine (2012), 14--47.Google Scholar
- Subhashini Venugopalan, Marcus Rohrbach, Jeffrey Donahue, Raymond Mooney, Trevor Darrell, and Kate Saenko. 2015. Sequence to sequence-video to text. In Proceedings of the IEEE International Conference on Computer Vision. 4534--4542.Google ScholarDigital Library
- Pushpendra Verma, Jayant Shekhar, Amit Asthana, and others. 2016. Digital right management model based on cryptography for mobile multimedia content. Int. J. Adv. Res. Comput. Sci. 7, 2 (2016).Google Scholar
- Javier Vidal-García, Marta Vidal, and Rafael Hernandez Barros. 2017. Computational business intelligence, big data, and their role in business decisions in the age of the internet of things. In The Internet of Things in the Modern Business Environment. IGI Global, 249--268.Google Scholar
- VW. 2016. Vowpal Wabbit. Retrieved May 7, 2016 from http://hunch.net/∼vw/.Google Scholar
- Kun Wang, Yunqi Wang, Xiaoxuan Hu, Yanfei Sun, Der-Jiunn Deng, Alexey Vinel, and Yan Zhang. 2017. Wireless big data computing in smart grid. IEEE Wireless Commun. 24, 2 (2017), 58--64.Google ScholarDigital Library
- Lijun Wang, Yu Lei, Ying Zeng, Li Tong, and Bin Yan. 2013. Principal feature analysis: A multivariate feature selection method for fMRI data. Computat. Math. Methods Med. 2013, 645921 (2013), 1--7.Google Scholar
- Yong Wang, Kevin Streff, and Sonell Raman. 2012. Smartphone security challenges. Computer 45, 12 (2012), 0052--58.Google ScholarDigital Library
- Yang Wang, Xinggang Wang, and Wenyu Liu. 2016. Unsupervised local deep feature for image recognition. Inf. Sci. 351 (2016), 67--75.Google ScholarDigital Library
- Robert E. Wilson, Samuel D. Gosling, and Lindsay T. Graham. 2012. A review of Facebook research in the social sciences. Perspect. Psychol. Sci. 7, 3 (2012), 203--220.Google ScholarCross Ref
- Worldometers. 2016. Real time world statistics. Retrieved April 7, 2016 from http://www.worldometers.info/world-population/.Google Scholar
- Jiajun Wu, Yinan Yu, Chang Huang, and Kai Yu. 2015. Deep multiple instance learning for image classification and auto-annotation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3460--3469.Google ScholarCross Ref
- Xindong Wu and Xingquan Zhu. 2008. Mining with noise knowledge: Error-aware data mining. IEEE Trans. Syst. Man Cybernet. A 38, 4 (2008), 917--932.Google ScholarDigital Library
- Hongbo Xu, Nianmin Yao, Wen Hu, Haiwei Pan, and Xiang Gao. 2012. The design and implementation of image information retrieval. In Proceedings of the International Conference on Computer Science 8 Service System. 1547--1550.Google ScholarDigital Library
- Zheng Xu, Yunhuai Liu, Lin Mei, Chuanping Hu, and Lan Chen. 2015. Semantic based representing and organizing surveillance big data using video structural description technology. J. Syst. Softw. 102 (2015), 217--225.Google ScholarDigital Library
- Yilin Yan, Min Chen, Saad Sadiq, and Mei-Ling Shyu. 2017. Efficient imbalanced multimedia concept retrieval by deep learning on spark clusters. International Journal of Multimedia Data Engineering and Management 8, 1 (2017), 1--20.Google ScholarDigital Library
- Yilin Yan, Mei-Ling Shyu, and Qiusha Zhu. 2016a. Negative correlation discovery for big multimedia data semantic concept mining and retrieval. In Proceedings of the IEEE 10th International Conference on Semantic Computing. 55--62.Google ScholarCross Ref
- Yilin Yan, Qiusha Zhu, Mei-Ling Shyu, and Shu-Ching Chen. 2016b. A classifier ensemble framework for multimedia big data classification. In Proceedings of the 17th IEEE International Conference on Information Reuse and Integration. IEEE Computer Society, 615--622.Google ScholarDigital Library
- Chaowei Yang, Qunying Huang, Zhenlong Li, Kai Liu, and Fei Hu. 2017. Big data and cloud computing: Innovation opportunities and challenges. Int. J. Digit. Earth 10, 1 (2017), 13--53.Google ScholarCross Ref
- Yimin Yang. 2015. Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis. Ph.D. Dissertation. Florida International University.Google Scholar
- Yimin Yang, Hsin-Yu Ha, Fausto Fleites, Shu-Ching Chen, and Steven Luis. 2011. Hierarchical disaster image classification for situation report enhancement. In Proceedings of the IEEE International Conference on Information Reuse and Integration. 181--186.Google ScholarCross Ref
- Yimin Yang, Daniel Lopez, Haiman Tian, Samira Pouyanfar, Fausto C. Fleites, Shu-Ching Chen, and Shahid Hamid. 2015. Integrated execution framework for catastrophe modeling. In Proceedings of the IEEE International Conference on Semantic Computing. IEEE, 201--207.Google ScholarCross Ref
- Yimin Yang, Wenting Lu, Jesse Domack, Tao Li, Shu-Ching Chen, Steve Luis, and Jainendra K. Navlakha. 2012. Madis: A multimedia-aided disaster information integration system for emergency management. In Proceedings of the 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom). ICST/IEEE, 233--241.Google Scholar
- Shanshan Yao, Yunsheng Wang, and Baoning Niu. 2015. An efficient cascaded filtering retrieval method for big audio data. IEEE Trans. Multimedia 17, 9 (2015), 1450--1459.Google ScholarDigital Library
- Zhan Ye, Ahmad P. Tafti, Karen Y. He, Kai Wang, and Max M. He. 2016. SparkText: Biomedical text mining on big data framework. PloS One 11, 9 (2016), e0162721.Google ScholarCross Ref
- YouTube.Com. 2016. YouTube statistics. Retreived April 7, 2016 from https://www.youtube.com/yt/press/statistics.html.Google Scholar
- Zhiwen Yu, Xingshe Zhou, Daqing Zhang, Chung-Yau Chin, Xiaohang Wang, and Ji Men. 2006. Supporting context-aware media recommendations for smart phones. IEEE Perv. Comput. 5, 3 (2006), 68--75.Google ScholarDigital Library
- John Zachary, S. Sitharama Iyengar, and Jacob Barhen. 2001. Content based image retrieval and information theory: A general approach. J. Am. Soc. Inf. Sci. Technol. 52, 10 (2001), 840--852.Google ScholarDigital Library
- Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu. 2014. Social Media Mining: An Introduction. Cambridge University Press.Google ScholarDigital Library
- Arkady Zaslavsky, Charith Perera, and Dimitrios Georgakopoulos. 2013. Sensing as a service and big data. CoRR abs/1301.0159 (2013). http://arxiv.org/abs/1301.0159.Google Scholar
- Xingyu Zeng, Wanli Ouyang, Meng Wang, and Xiaogang Wang. 2014. Deep learning of scene-specific classifier for pedestrian detection. In Proceedings of the 13th European Conference on Computer Vision. Springer, Zurich, 472--487.Google ScholarCross Ref
- Chengcui Zhang, Shu-Ching Chen, Mei-Ling Shyu, and Srinivas Peeta. 2003. Adaptive background learning for vehicle detection and spatio-temporal tracking. In Proceedings of the 4th IEEE Pacific-Rim Conference on Multimedia. IEEE.Google Scholar
- Jian Zhang, Shifei Ding, Nan Zhang, and Zhongzhi Shi. 2016. Incremental extreme learning machine based on deep feature embedded. Int. J. Mach. Learn. Cybernet. 7, 1 (2016), 111--120.Google ScholarCross Ref
- Xishan Zhang, Yang Yang, Yongdong Zhang, Huanbo Luan, Jintao Li, Hanwang Zhang, and Tat-Seng Chua. 2015. Enhancing video event recognition using automatically constructed semantic-visual knowledge base. IEEE Trans. Multimedia 17, 9 (2015), 1562--1575.Google ScholarDigital Library
- Liang Zhou and Han-Chieh Chao. 2011. Multimedia traffic security architecture for the internet of things. IEEE Netw. 25, 3 (2011), 35--40.Google ScholarCross Ref
- Qiusha Zhu, Zhao Li, Haohong Wang, Yimin Yang, and Mei-Ling Shyu. 2013. Multimodal sparse linear integration for content-based item recommendation. In Proceedings of the IEEE International Symposium on Multimedia. IEEE Computer Society, Los Alamitos, CA, 187--194.Google ScholarDigital Library
- Xingquan Zhu and Xindong Wu. 2005. Cost-constrained data acquisition for intelligent data preparation. IEEE Trans. Knowl. Data Eng. 17, 11 (2005), 1542--1556.Google ScholarDigital Library
- Paul Zikopoulos, Krishnan Parasuraman, Thomas Deutsch, James Giles, David Corrigan, and others. 2012. Harness the Power of Big Data The IBM Big Data Platform. McGraw-Hill Professional, New York, NY.Google Scholar
Index Terms
- Multimedia Big Data Analytics: A Survey
Recommendations
Responsible Big Data Analytics for E-Business Services
ICBDR '21: Proceedings of the 5th International Conference on Big Data ResearchThis paper examines responsible big data analytics for e-business services and looks at how to use responsible big data analytics to obtain responsible e-business services. It addresses why responsibility matters to big data analytics and e-business ...
Modeling SmallClient indexing framework for big data analytics
Continually growing big data by the intervention of electronic and automated devices affects the data retrieval performance of contemporary big data analytics technologies and makes exploration and adoption of improved procedures inevitable. Indexing on ...
Comments