Details
| Original language | English |
|---|---|
| Title of host publication | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
| Pages | 779-780 |
| Number of pages | 2 |
| Publication status | Published - 3 May 2013 |
| Event | 22nd International Conference on World Wide Web - Rio de Janeiro, Brazil Duration: 13 May 2013 → 17 May 2013 Conference number: 22 |
Publication series
| Name | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
|---|
Abstract
The Web of people is highly dynamic and the life experi- ences between our on-line and \real-world" interactions are increasingly interconnected. For example, users engaged in the Social Web more and more rely upon continuous social streams for real-time access to information and fresh knowl- edge about current affairs. However, given the deluge of data items, it is a challenge for individuals to find relevant and appropriately ranked information at the right time. Hav- ing Twitter as test bed, we tackle this information overload problem by following an online collaborative approach. That is, we go beyond the general perspective of information find- ing in Twitter, that asks: \What is happening right now?", towards an individual user perspective, and ask:\What is in- teresting to me right now within the social media stream?". In this paper, we review our recently proposed online col- laborative filtering algorithms and outline potential research directions.
Keywords
- Collaborative filtering, Online ranking, Twitter
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web. 2013. p. 779-780 (WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Towards Real-time Collaborative Filtering for Big Fast Data
AU - Diaz-Aviles, Ernesto
AU - Nejdl, Wolfgang
AU - Drumond, Lucas
AU - Schmidt-Thieme, Lars
N1 - Conference code: 22
PY - 2013/5/3
Y1 - 2013/5/3
N2 - The Web of people is highly dynamic and the life experi- ences between our on-line and \real-world" interactions are increasingly interconnected. For example, users engaged in the Social Web more and more rely upon continuous social streams for real-time access to information and fresh knowl- edge about current affairs. However, given the deluge of data items, it is a challenge for individuals to find relevant and appropriately ranked information at the right time. Hav- ing Twitter as test bed, we tackle this information overload problem by following an online collaborative approach. That is, we go beyond the general perspective of information find- ing in Twitter, that asks: \What is happening right now?", towards an individual user perspective, and ask:\What is in- teresting to me right now within the social media stream?". In this paper, we review our recently proposed online col- laborative filtering algorithms and outline potential research directions.
AB - The Web of people is highly dynamic and the life experi- ences between our on-line and \real-world" interactions are increasingly interconnected. For example, users engaged in the Social Web more and more rely upon continuous social streams for real-time access to information and fresh knowl- edge about current affairs. However, given the deluge of data items, it is a challenge for individuals to find relevant and appropriately ranked information at the right time. Hav- ing Twitter as test bed, we tackle this information overload problem by following an online collaborative approach. That is, we go beyond the general perspective of information find- ing in Twitter, that asks: \What is happening right now?", towards an individual user perspective, and ask:\What is in- teresting to me right now within the social media stream?". In this paper, we review our recently proposed online col- laborative filtering algorithms and outline potential research directions.
KW - Collaborative filtering
KW - Online ranking
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=84893105571&partnerID=8YFLogxK
U2 - https://doi.org/10.1145/2487788.2488044
DO - https://doi.org/10.1145/2487788.2488044
M3 - Conference contribution
AN - SCOPUS:84893105571
SN - 9781450320382
T3 - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
SP - 779
EP - 780
BT - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
T2 - 22nd International Conference on World Wide Web
Y2 - 13 May 2013 through 17 May 2013
ER -