Optimizing Web Search Using Social Annotations

1. Optimizing Web Search Using Social Annotations Shanghai JiaoTong University IBM China Research Lab Stated Problem/Why interesting? Proposed Solution SocialSimRank to calculate similarity between annotations and query Recent studies: • Ranking web pages based on similarity (vector-space model) • Ranking web pages based on quality (PageRank) • Utilizing social annotations (folksonomies, Semantic Web) Trivial approach: Better solution: First to propose integrating social annotations with traditional web search SocialPageRank to calculate quality in terms of annotation count My Opinion • Similar to PageRank: “quality” is passed between the users, annotations and pages until convergence • Annotations are descriptive, but not “clean” summaries (synonymy problem) • Not very clear exactly how to incorporate both algorithms into web search (not the point of the paper?) • Web’s adversarial nature ignored, tag spamming only briefly mentioned • Paper is interesting and readable; known concepts applied in novel way. We could’ve thought of it! It was our corn to cut! Connection with Course Material • Including new measure into basic similarity formula • SocialSimRank label disambiguation approach (similar to SemTag/SemSeeker) • SocialPageRank concept identical to PageRank • Use of annotation correlation matrices analogous to term-term matrices