2002 · 108 citations · 24 references
Ranking AlgorithmEngineeringIntelligent Information RetrievalSemantic WebCorpus LinguisticsText MiningNatural Language ProcessingInformation RetrievalData ScienceData MiningRelevance FeedbackQuery ExpansionContent AnalysisKnowledge DiscoveryBroad Topic QueriesHits-based AlgorithmsHits AlgorithmComputer ScienceSearch Engine DesignWeb MiningSearch Engine Indexing
In this paper, we present two ways to improve the precision of HITS-based algorithms on Web documents. First, by analyzing the limitations of current HITS-based algorithms, we propose a new weighted HITS-based method that assigns appropriate weights to in-links of root documents. Then, we combine content analysis with HITS-based algorithms and study the effects of four representative relevance scoring methods, VSM, Okapi, TLS, and CDR, using a set of broad topic queries. Our experimental results show that our weighted HITS-based method performs significantly better than Bharat's improved HITS algorithm. When we combine our weighted HITS-based method or Bharat's HITS algorithm with any of the four relevance scoring methods, the combined methods are only marginally better than our weighted HITS-based method. Between the four relevance-scoring methods, there is no significant quality difference when they are combined with a HITS-based algorithm.
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Authoritative sources in a hyperlinked environment
Jon Kleinberg · Symposium on Discrete Algorithms · 1998 · 1.8K citations