ABSTRACT
Recommendation is essential to many online services; however current systems often provide limited interaction and visualization mechanisms, affecting the user satisfaction of recommendation. This paper presents an interactive recommendation approach for the general public without any knowledge of recommendation or visualization algorithms. Our approach emphasizes interactivity, explicit user input, and semantic information convey with the following two components. First, we propose a Latent Semantic Model that captures the statistical features of semantic concepts on 2D domains and abstracts user preferences for personal recommendation, so that high-dimensional spectral space from the rating records can be understood and interacted with directly. Second, we propose an interactive recommendation approach through a storytelling mechanism for promoting the communication between the user and the recommendation system. We demonstrate and evaluate our approach with a real dataset. Our approach can also be extended to other applications including various online recommendation systems.
- Fereshteh Amini, Nathalie Henry Riche, Bongshin Lee, Christophe Hurter, and Pourang Irani. 2015. Understanding data videos: Looking at narrative visualization through the cinematography lens. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 1459--1468. Google ScholarDigital Library
- Benjamin Bach, Natalie Kerracher, Kyle Wm Hall, Sheelagh Carpendale, Jessie Kennedy, and Nathalie Henry Riche. 2016. Telling Stories about Dynamic Networks with Graph Comics. In Proceedings of the Conference on Human Factors in Information Systems (CHI). ACM, New York, United States. Google ScholarDigital Library
- Fedor Bakalov, Marie-Jean Meurs, Birgitta König-Ries, Bahar Sateli, René Witte, Greg Butler, and Adrian Tsang. 2013. An Approach to Controlling User Models and Personalization Effects in Recommender Systems. In Proceedings of the 2013 International Conference on Intelligent User Interfaces (IUI '13). 49--56. Google ScholarDigital Library
- Svetlin Bostandjiev, John O'Donovan, and Tobias Höllerer. 2012. TasteWeights: A Visual Interactive Hybrid Recommender System. In Proceedings of the Sixth ACM Conference on Recommender Systems (RecSys '12). 35--42. Google ScholarDigital Library
- Jeremy Boy, Françoise Detienne, and Jean-Daniel Fekete. 2015. Storytelling in Information Visualizations: Does It Engage Users to Explore Data?. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI '15). 1449--1458. Google ScholarDigital Library
- C. Bryan, K. L. Ma, and J. Woodring. 2016. Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement. IEEE Transactions on Visualization and Computer Graphics (2016). Google ScholarDigital Library
- Giuseppe Carenini, Jocelyin Smith, and David Poole. 2003. Towards More Conversational and Collaborative Recommender Systems. In Proceedings of the 8th International Conference on Intelligent User Interfaces (IUI '03). 12--18. Google ScholarDigital Library
- Li Chen and Feng Wang. 2017. Explaining Recommendations Based on Feature Sentiments in Product Reviews. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces (IUI '17). 17--28. Google ScholarDigital Library
- Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann. 2016. Towards Conversational Recommender Systems. In Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16). 815--824. Google ScholarDigital Library
- Tarik Crnovrsanin, Isaac Liao, Yingcai Wuy, and Kwan-Liu Ma. 2011. Visual Recommendations for Network Navigation. In Proceedings of the 13th Eurographics / IEEE - VGTC Conference on Visualization (EuroVis'11). 1081--1090. Google ScholarDigital Library
- Pedro Cruz and Penousal Machado. 2011. Generative storytelling for information visualization. IEEE computer graphics and applications 31, 2 (2011), 80--85. Google ScholarDigital Library
- Mukund Deshpande and George Karypis. 2004. Item-based top-N Recommendation Algorithms. ACM Trans. Inf. Syst. 22, 1 (Jan. 2004), 143--177. Google ScholarDigital Library
- Pierre Dragicevic, Anastasia Bezerianos, Waqas Javed, Niklas Elmqvist, and Jean-Daniel Fekete. 2011. Temporal distortion for animated transitions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2009--2018. Google ScholarDigital Library
- R. Eccles, T. Kapler, R. Harper, and W. Wright. 2007. Stories in GeoTime. In Visual Analytics Science and Technology, 2007. VAST 2007. IEEE Symposium on. 19--26. Google ScholarDigital Library
- Michael D. Ekstrand, John T. Riedl, and Joseph A. Konstan. 2011. Collaborative Filtering Recommender Systems. Found. Trends Hum.-Comput. Interact. 4, 2 (Feb. 2011), 81--173. Google ScholarDigital Library
- A. Figueiras. 2014. How to Tell Stories Using Visualization. In Information Visualisation (IV), 2014 18th International Conference on. 18--26.Google ScholarCross Ref
- D. Fisher, A. Hoff, G. Robertson, and M. Hurst. 2008. Narratives: A visualization to track narrative events as they develop. In IEEE Symposium on Visual Analytics Science and Technology. 115--122.Google Scholar
- Nahum Gershon and Ward Page. 2001. What Storytelling Can Do for Information Visualization. Commun. ACM 44, 8 (Aug. 2001), 31--37. Google ScholarDigital Library
- Brynjar Gretarsson, John O'Donovan, Svetlin Bostandjiev, Christopher Hall, and Tobias Höllerer. 2010. Smallworlds: Visualizing social recommendations. Computer Graphics Forum 29, 3 (2010), 833--842. Google ScholarDigital Library
- Xianlin Hu, Aidong Lu, and Xintao Wu. 2013. Spectrum-Based Network Visualization for Topology Analysis. Computer Graphics and Applications, IEEE 33, 1 (Jan 2013), 58--68. Google ScholarDigital Library
- Jessica Hullman and Nicholas Diakopoulos. 2011. Visualization rhetoric: Framing effects in narrative visualization. Visualization and Computer Graphics, IEEE Transactions on 17, 12 (2011), 2231--2240. Google ScholarDigital Library
- Jessica Hullman, Nicholas Diakopoulos, and Eytan Adar. 2013a. Contextifier: Automatic Generation of Annotated Stock Visualizations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). 2707--2716. Google ScholarDigital Library
- Jessica Hullman, Steven Drucker, Nathalie Henry Riche, Bongshin Lee, Danyel Fisher, and Eytan Adar. 2013b. A Deeper Understanding of Sequence in Narrative Visualization. IEEE Transactions on Visualization and Computer Graphics 19, 12 (2013), 2406--2415. Google ScholarDigital Library
- Anne-Marie Kermarrec and Afshin Moin. 2012. Data Visualization Via Collaborative Filtering. Research report. Inria. 23 pages. https://hal.inria.fr/hal-00673330Google Scholar
- Bart P. Knijnenburg, Martijn C. Willemsen, Zeno Gantner, Hakan Soncu, and Chris Newell. 2012. Explaining the user experience of recommender systems. User Modeling and User-Adapted Interaction 22, 4 (01 Oct 2012), 441--504. Google ScholarDigital Library
- Yehuda Koren. 2008. Factorization Meets the Neighborhood: A Multifaceted Collaborative Filtering Model. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '08). 426--434. Google ScholarDigital Library
- R. Kosara and J. Mackinlay. 2013. Storytelling: The Next Step for Visualization. Computer 46, 5 (2013), 44--50. Google ScholarDigital Library
- Johannes Kunkel, Benedikt Loepp, and Jürgen Ziegler. 2017. A 3D Item Space Visualization for Presenting and Manipulating User Preferences in Collaborative Filtering. In Proceedings of the International Conference on Intelligent User Interfaces (IUI). 3--15. Google ScholarDigital Library
- Bongshin Lee, Rubaiat Habib Kazi, and Greg Smith. 2013. SketchStory: Telling More Engaging Stories with Data Through Freeform Sketching. IEEE Transactions on Visualization and Computer Graphics 19, 12 (Dec. 2013), 2416--2425. Google ScholarDigital Library
- Bongshin Lee, N.H. Riche, P. Isenberg, and S. Carpendale. 2015. More Than Telling a Story: Transforming Data into Visually Shared Stories. Computer Graphics and Applications, IEEE 35, 5 (2015), 84--90.Google Scholar
- Jure Leskovec, Anand Rajaraman, and Jeffrey David Ullman. 2014. Mining of massive datasets. Cambridge University Press. Google ScholarDigital Library
- Benedikt Loepp, Katja Herrmanny, and Jürgen Ziegler. 2015. Blended Recommending: Integrating Interactive Information Filtering and Algorithmic Recommender Techniques. In Proceedings of ACM Conference on Human Factors in Computing Systems. ACM, 975--984. Google ScholarDigital Library
- Benedikt Loepp, Tim Hussein, and Jüergen Ziegler. 2014. Choice-based preference elicitation for collaborative filtering recommender systems. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 3085--3094. Google ScholarDigital Library
- Hangzai Luo, Jianping Fan, Daniel A Keim, and Shin'ichi Satoh. 2009. Personalized news video recommendation. In Advances in Multimedia Modeling. Springer, 459--471. Google ScholarDigital Library
- Kwan-Liu Ma, I. Liao, J. Frazier, H. Hauser, and H.-N. Kostis. 2012. Scientific Storytelling Using Visualization. Computer Graphics and Applications, IEEE 32, 1 (2012), 12--19. Google ScholarDigital Library
- Alex Mitchell and Kevin McGee. 2011. Limits of rereadability in procedural interactive stories. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1939--1948. Google ScholarDigital Library
- John O'Donovan, Barry Smyth, Brynjar Gretarsson, Svetlin Bostandjiev, and Tobias Höllerer. 2008. PeerChooser: Visual Interactive Recommendation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '08). 1085--1088. Google ScholarDigital Library
- Denis Parra, Peter Brusilovsky, and Christoph Trattner. 2014. See What You Want to See: Visual User-driven Approach for Hybrid Recommendation. In Proceedings of the 19th International Conference on Intelligent User Interfaces (IUI '14). 235--240. Google ScholarDigital Library
- Li Pu and Boi Faltings. 2013. Understanding and Improving Relational Matrix Factorization in Recommender Systems. In Proceedings of the 7th ACM Conference on Recommender Systems (RecSys '13). 41--48. Google ScholarDigital Library
- Pearl Pu, Li Chen, and Rong Hu. 2012. Evaluating recommender systems from the user's perspective: survey of the state of the art. User Modeling and User-Adapted Interaction 22, 4 (01 Oct 2012), 317--355. Google ScholarDigital Library
- GroupLens Research. 2015. MovieLens100k: Movie rating Dataset. (2015). http://grouplens.org/datasets/movielens/Google Scholar
- M.O. Riedl and R.M. Young. 2006. From linear story generation to branching story graphs. Computer Graphics and Applications, IEEE 26, 3 (2006), 23--31. Google ScholarDigital Library
- Arvind Satyanarayan and Jeffrey Heer. 2014. Authoring Narrative Visualizations with Ellipsis. Comput. Graph. Forum 33, 3 (2014), 361--370.Google ScholarCross Ref
- Edward Segel and Jeffrey Heer. 2010. Narrative visualization: Telling stories with data. Visualization and Computer Graphics, IEEE Transactions on 16, 6 (2010), 1139--1148. Google ScholarDigital Library
- Eric Spaulding and Haakon Faste. 2013. Design-driven narrative: using stories to prototype and build immersive design worlds. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2843--2852. Google ScholarDigital Library
- Nava Tintarev and Judith Masthoff. 2015. Explaining Recommendations: Design and Evaluation. Springer US, Boston, MA, 353--382.Google Scholar
- Chao Tong, Richard Roberts, Rita Borgo, Robert S Laramee, Kodzo Wegba, Aidong Lu, Yun Wang, Huamin Qu, Qiong Luo, and Xiaojuan Ma. 2018. Storytelling and Visualization: A Survey. In Proceedings of the 9th International Conference on Information Visualization Theory and Applications (IVAPP).Google ScholarCross Ref
- Katrien Verbert, Denis Parra, Peter Brusilovsky, and Erik Duval. 2013. Visualizing Recommendations to Support Exploration, Transparency and Controllability. In Proceedings of the 2013 International Conference on Intelligent User Interfaces (IUI '13). 351--362. Google ScholarDigital Library
- Jesse Vig, Shilad Sen, and John Riedl. 2009. Tagsplanations: Explaining Recommendations Using Tags. In Proceedings of the 14th International Conference on Intelligent User Interfaces (IUI '09). 47--56. Google ScholarDigital Library
- Michail Vlachos and Daniel Svonava. 2012. Recommendation and visualization of similar movies using minimum spanning dendrograms. Information Visualization (2012). Google ScholarDigital Library
- Michael Wohlfart and Helwig Hauser. 2007. Story Telling for Presentation in Volume Visualization. In Proceedings of the 9th Joint Eurographics / IEEE VGTC Conference on Visualization (EUROVIS'07). 91--98. Google ScholarDigital Library
- Wita Wojtkowski and W Gregory Wojtkowski. 2002. Storytelling: its role in information visualization. In European Systems Science Congress.Google Scholar
- Li Yu, Aidong Lu, William Ribarsky, and Wei Chen. 2010. Automatic Animation for Time-Varying Data Visualization. Computer Graphics Forum 29, 7 (2010), 2271--2280.Google ScholarCross Ref
- Fajie Yuan, Guibing Guo, Joemon M. Jose, Long Chen, Haitao Yu, and Weinan Zhang. 2017. BoostFM: Boosted Factorization Machines for Top-N Feature-based Recommendation. In Proceedings of the 22Nd International Conference on Intelligent User Interfaces (IUI '17). 45--54. Google ScholarDigital Library
Index Terms
- Interactive Storytelling for Movie Recommendation through Latent Semantic Analysis
Recommendations
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