Diversifying Search Results with Popular Subtopics

Abstract

The problem we aim to solve is the diversification of search results for ambiguous web queries. We present a model based on knowledge of the diversity of query subtopics to generate a diversified ranking for retrieved documents. We expand the original query into several related queries, assuming that query expansions expose subtopics of the original query. Moreover, each query expansion is given a weight which reflects the likelihood of the interpretation (the fraction of users who issued this query given the general query topic). We issue all those expanded queries including the original query to a standard BM25 search engine, then re-rank the retrieved documents to generate the final ranking. Our method can detect possible subtopics of a given query and provide a reasonable ranking that satisfies both relevancy and diversity metrics. The TREC evaluations show our method is effective on the diversity task.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2009
Accession Number
ADA517746

Entities

People

  • Brian D. Davison
  • Dawei Yin
  • Xiaoguang Qi
  • Zhenzhen Xue

Organizations

  • Lehigh University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computer Science
  • Computers
  • Detection
  • Engineering
  • Information Operations
  • Instructions
  • Precision
  • Probability
  • Random Walk
  • Redundancy
  • Standards
  • Test And Evaluation
  • Universities

Fields of Study

  • Computer science

Readers

  • Information Retrieval
  • Regression Analysis.