2014 WhoAreExpertsSpecializinginLand

From GM-RKB
Jump to: navigation, search

Subject Headings:

Notes

Cited By

Quotes

Author Keywords

Abstract

With the rapid growth of Web 2.0, a variety of content sharing services, such as Flickr, YouTube, Blogger, and TripAdvisor etc, have become extremely popular over the last decade. On these websites, users have created and shared with each other various kinds of resources, such as photos, video, and travel blogs. The sheer amount of user-generated content varies greatly in quality, which calls for a principled method to identify a set of authorities, who created high-quality resources, from a massive number of contributors of content. Since most previous studies only infer global authoritativeness of a user, there is no way to differentiate the authoritativeness in different aspects of life (topics).

In this paper, we propose a novel model of Topic-specific Authority Analysis (TAA), which addresses the limitations of the previous approaches, to identify authorities specific to given query topic (s) on a content sharing service. This model jointly leverages the usage data collected from the sharing log and the favorite log. The parameters in TAA are learned from a constructed training dataset, for which a novel logistic likelihood function is specifically designed. To perform Bayesian inference for TAA with the new logistic likelihood, we extend typical Gibbs sampling by introducing auxiliary variables. Thorough experiments with two real-world datasets demonstrate the effectiveness of TAA in topic-specific authority identification as well as the generalizability of the TAA generative model.

References

;

 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2014 WhoAreExpertsSpecializinginLandBin Bi
Ben Kao
Chang Wan
Junghoo Cho
Who Are Experts Specializing in Landscape Photography?: Analyzing Topic-specific Authority on Content Sharing Services10.1145/2623330.26237522014
AuthorBin Bi +, Ben Kao +, Chang Wan + and Junghoo Cho +
conferenceKDD-2014 +
doi10.1145/2623330.2623752 +
proceedingsProceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining +
titleWho Are Experts Specializing in Landscape Photography?: Analyzing Topic-specific Authority on Content Sharing Services +
year2014 +