Paper: Topical PageRank: A Model of Scientific Expertise for Bibliographic Search

ACL ID E14-1053
Title Topical PageRank: A Model of Scientific Expertise for Bibliographic Search
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We model scientific expertise as a mixture of topics and authority. Authority is calcu- lated based on the network properties of each topic network. ThemedPageRank, our combi- nation of LDA-derived topics with PageRank differs from previous models in that topics in- fluence both the bias and transition probabili- ties of PageRank. It also incorporates the age of documents. Our model is general in that it can be applied to all tasks which require an estimate of document?document, document? query, document?topic and topic?query sim- ilarities. We present two evaluations, one on the task of restoring the reference lists of 10,000 articles, the other on the task of au- tomatically creating reading lists that mimic reading lists created by experts. In both eval- uations, our system beats state-...