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 - 10.1145/2487788.2488044

DO - 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 -