Document Type
Conference Proceeding
Publication Date
4-2014
Abstract
Industry and researchers have identified numerous ways to monetize microblogs for personalization and recommendation. A common challenge across these different works is the identification of user interests. Although techniques have been developed to address this challenge, a flexible approach that spans multiple levels of granularity in user interests has not been forthcoming. In this work, we focus on exploiting hierarchical semantics of concepts to infer richer user interests expressed as a Hierarchical Interest Graph. To create such graphs, we utilize users' tweets to first ground potential user interests to structured background knowledge such as Wikipedia Category Graph. We then adapt spreading activation theory to assign user interest score to each category in the hierarchy. The Hierarchical Interest Graph not only comprises of users' explicitly mentioned interests determined from Twitter, but also their implicit interest categories inferred from the background knowledge source.
Repository Citation
Kapanipathi, P.,
Jain, P.,
Venkataramani, C.,
& Sheth, A. P.
(2014). Hierarchical Interest Graph from Tweets. Proceedings of the Companion Publication of the 23rd International World Wide Web Conference, 311-312.
https://corescholar.libraries.wright.edu/knoesis/577
DOI
10.1145/2567948.2577353
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 23rd International World Wide Web Conference, Seoul, Korea, April 7-11, 2014.