Temporal correlation between social tags and emerging long-term trend detection
Journal
4th International AAAI Conference on Weblogs and Social Media
Pages
255-258
ISBN
9781577354451
Date Issued
2010
Author(s)
Abstract
Social annotation has become a popular manner for web users to manage and share their information and interests. While users' interests vary with time, tag correlation also changes from users' perspectives. In this work, we explore four methods for estimating temporal correlation between social tags and detect if a long-term trend emerges from the history of temporal correlation between two tags. Three types of trends are specified: steadily-shifting, stabilizing, and cyclic. To compare the results of the four estimation methods, an indirect evaluation is realized by applying detected trends to tag recommendation. Copyright ? 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Type
conference paper