Details
| Original language | English |
|---|---|
| Title of host publication | CIKM 2012 - Proceedings of the 21st ACM International Conference on Information and Knowledge Management |
| Pages | 1592-1596 |
| Number of pages | 5 |
| Publication status | Published - 29 Oct 2012 |
| Event | 21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States Duration: 29 Oct 2012 → 2 Nov 2012 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Abstract
Users engaged in the Social Web increasingly rely upon continuous streams of Twitter messages (tweets) for real-time access to information and fresh knowledge about current affairs. However, given the deluge of tweets, it is a challenge for individuals to find relevant and appropriately ranked information. We propose to address this knowledge management problem by going beyond the general perspective of information finding in Twitter, that asks: "What is happening right now?", towards an individual user perspective, and ask: "What is interesting to me right now?" In this paper, we consider collaborative filtering as an online ranking problem and present RMFO, a method that creates, in real-time, user-specific rankings for a set of tweets based on individual preferences that are inferred from the user's past system interactions. Experiments on the 476 million Twitter tweets dataset show that our online approach largely outperforms recommendations based on Twitter's global trend and Weighted Regularized Matrix Factorization (WRMF), a highly competitive state-of-the-art Collaborative Filtering technique, demonstrating the efficacy of our approach.
Keywords
- collaborative filtering, online ranking, twitter
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Computer Networks and Communications
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CIKM 2012 - Proceedings of the 21st ACM International Conference on Information and Knowledge Management. 2012. p. 1592-1596 (ACM International Conference Proceeding Series).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - What is Happening Right Now ... That Interests Me?
T2 - 21st ACM International Conference on Information and Knowledge Management, CIKM 2012
AU - Diaz-Aviles, Ernesto
AU - Drumond, Lucas
AU - Gantner, Zeno
AU - Schmidt-Thieme, Lars
AU - Nejdl, Wolfgang
PY - 2012/10/29
Y1 - 2012/10/29
N2 - Users engaged in the Social Web increasingly rely upon continuous streams of Twitter messages (tweets) for real-time access to information and fresh knowledge about current affairs. However, given the deluge of tweets, it is a challenge for individuals to find relevant and appropriately ranked information. We propose to address this knowledge management problem by going beyond the general perspective of information finding in Twitter, that asks: "What is happening right now?", towards an individual user perspective, and ask: "What is interesting to me right now?" In this paper, we consider collaborative filtering as an online ranking problem and present RMFO, a method that creates, in real-time, user-specific rankings for a set of tweets based on individual preferences that are inferred from the user's past system interactions. Experiments on the 476 million Twitter tweets dataset show that our online approach largely outperforms recommendations based on Twitter's global trend and Weighted Regularized Matrix Factorization (WRMF), a highly competitive state-of-the-art Collaborative Filtering technique, demonstrating the efficacy of our approach.
AB - Users engaged in the Social Web increasingly rely upon continuous streams of Twitter messages (tweets) for real-time access to information and fresh knowledge about current affairs. However, given the deluge of tweets, it is a challenge for individuals to find relevant and appropriately ranked information. We propose to address this knowledge management problem by going beyond the general perspective of information finding in Twitter, that asks: "What is happening right now?", towards an individual user perspective, and ask: "What is interesting to me right now?" In this paper, we consider collaborative filtering as an online ranking problem and present RMFO, a method that creates, in real-time, user-specific rankings for a set of tweets based on individual preferences that are inferred from the user's past system interactions. Experiments on the 476 million Twitter tweets dataset show that our online approach largely outperforms recommendations based on Twitter's global trend and Weighted Regularized Matrix Factorization (WRMF), a highly competitive state-of-the-art Collaborative Filtering technique, demonstrating the efficacy of our approach.
KW - collaborative filtering
KW - online ranking
KW - twitter
UR - http://www.scopus.com/inward/record.url?scp=84871061502&partnerID=8YFLogxK
U2 - 10.1145/2396761.2398479
DO - 10.1145/2396761.2398479
M3 - Conference contribution
AN - SCOPUS:84871061502
SN - 9781450311564
T3 - ACM International Conference Proceeding Series
SP - 1592
EP - 1596
BT - CIKM 2012 - Proceedings of the 21st ACM International Conference on Information and Knowledge Management
Y2 - 29 October 2012 through 2 November 2012
ER -