skip to main content
10.1145/3289600.3291372acmconferencesArticle/Chapter ViewAbstractPublication PageswsdmConference Proceedingsconference-collections
abstract

The 1st International Workshop on Context-Aware Recommendation Systems with Big Data Analytics (CARS-BDA)

Published: 30 January 2019 Publication History

Abstract

With the explosive growth of online service platforms, increasing number of people and enterprises are doing everything online. In order for organizations, governments, and individuals to understand their users, and promote their products or services, it is necessary for them to analyse big data and recommend the media or online services in real time. Effective recommendation of items of interest to consumers has become critical for enterprises in domains such as retail, e-commerce, and online media. Driven by the business successes, academic research in this field has also been active for many years. Through many scientific breakthroughs have been achieved, there are still tremendous challenges in developing effective and scalable recommendation systems for real-world industrial applications. Existing solutions focus on recommending items based on pre-set contexts, such as time, location, weather etc. The big data sizes and complex contextual information add further challenges to the deployment of advanced recommender systems. This workshop aims to bring together researchers with wide-ranging backgrounds to identify important research questions, to exchange ideas from different research disciplines, and, more generally, to facilitate discussion and innovation in the area of context-aware recommender systems and big data analytics.

References

[1]
M. Jiang, P. Cui, R. Liu, Q. Yang, F.Wang,W. Zhu, and S. Yang, "Social contextual recommendation," in CIKM. ACM, 2012, pp. 45--54.
[2]
Y. Huang, B. Cui, J. Jiang, K. Hong, W. Zhang, and Y. Xie, "Real-time video recommendation exploration," in SIGMOD, 2016, pp. 35--46.
[3]
R. Kumar, B. K. Verma, and S. S. Rastogi, "Context-aware social popularity based recommender system," IJCA, vol. 92, no. 2, pp. 37--42, April 2014.
[4]
X. Yang, H. Steck, and Y. Liu, "Circle-based recommendation in online social networks," in KDD, 2012, pp. 1267--1275.
[5]
H. Yin, B. Cui, L. Chen, Z. Hu, and Z. Huang, "A temporal context-aware model for user behavior modeling in social media systems," in SIGMOD, 2014, pp. 1543-- 1554.
[6]
A. Akther, K. M. Alam, H. N. Kim, and A. E. Saddik, "Social network and user context assisted personalization for recommender systems," in IIT, 2012, pp. 95--100.
[7]
X. Zhou, L. Chen, Y. Zhang, L. Cao, G. Huang, and C. Wang, "Online video recommendation in sharing community," in SIGMOD. ACM, 2015, pp. 1645-- 1656.
[8]
X. Zhou, L. Chen, Y. Zhang, D. Qin, L. Cao, G. Huang, and C. Wang, "Enhancing online video recommendation using social user interactions," VLDB J., vol. 26, no. 5, pp.637--656, 2017.
[9]
X. Zhou, D. Qin, L. Chen, and Y. Zhang, "Real-time context-aware social media recommendation," VLDB J., 2018.
[10]
D. Qin, X. Zhou, L. Chen, G. Huang, and Y. Zhang, "Dynamic Connection-based Social Group Recommendation," TKDE, 2018.
[11]
H. Luo, J. Fan, and D. A. Keim, "Personalized news video recommendation," in ACM MM, 2008, pp. 1001--1002.
[12]
L. Li, D.Wang, T. Li, D. Knox, and B. Padmanabhan, "SCENE: a scalable two-stage personalized news recommendation system," in SIGIR, 2011, pp. 125--134.
[13]
http://storm.apache.org/releases/1.0.0/Concepts.html
[14]
http://www.ruizhang.info/
[15]
G. Adomavicius, L. Baltrunas, E. William de Luca, T. Hussein, and A. Tuzhilin. 4th Workshop on Context-aware Recommender Systems (CARS 2012). In RecSys'12. 349--350.
[16]
G. Adomavicius, L. Baltrunas, T. Hussein, F. Ricci, and A. Tuzhilin. 2011. 3rd Workshop on Context-aware Recommender Systems (CARS 2011). In RecSys '11. 379--380.
[17]
G. Adomavicius and F. Ricci. 2009. RecSys'09 workshop 3: workshop on contextaware recommender systems (CARS-2009). In RecSys 2009. 423--424.
[18]
G. Adomavicius, A. Tuzhilin, S. Berkovsky, E. W. De Luca, and A. Said. 2010. Context-awareness in Recommender Systems: Research Workshop and Movie Recommendation Challenge. In RecSys '10. 385--386.

Cited By

View all
  • (2022)Q-Chef: The impact of surprise-eliciting systems on food-related decision-makingProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501862(1-14)Online publication date: 29-Apr-2022

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining
January 2019
874 pages
ISBN:9781450359405
DOI:10.1145/3289600
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 January 2019

Check for updates

Author Tags

  1. big data analysis
  2. context-aware recommendation

Qualifiers

  • Abstract

Conference

WSDM '19

Acceptance Rates

WSDM '19 Paper Acceptance Rate 84 of 511 submissions, 16%;
Overall Acceptance Rate 498 of 2,863 submissions, 17%

Upcoming Conference

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)6
  • Downloads (Last 6 weeks)0
Reflects downloads up to 08 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2022)Q-Chef: The impact of surprise-eliciting systems on food-related decision-makingProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501862(1-14)Online publication date: 29-Apr-2022

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media