On Duplicate Results in a Search Session

Abstract

In this paper, we introduce the PITT group's methods and findings in TREC 2012 session track. After analyzing the search logs in session track 2011 and 2012 datasets, we find that users' reformulated queries are very different from their previous ones, probably indicating their expectations to find not only relevant but also novel results. However, as indicated from our results, a major approach adopted by the session track participants, i.e. using relevance feedback information extracted from previous queries for search, will sacrifice the novelty of results for improving ad hoc search performance (e.g. nDCG@10). Such issues were not disclosed in previous years' session tracks because TREC did not consider the effects of duplicate results in evaluation. Therefore, we proposed a method to properly penalize the duplicate results in ranking by simulating users' browsing behaviors in a search session. A duplicate result in current search will be penalized to a greater extent if it was ranked in higher positions in previous searches or it was returned by more previous queries. The method can effectively improve the novelty of search results and lead to only slight and insignificant drop in ad hoc search performance.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2012
Accession Number
ADA581289

Entities

People

  • Daqing He
  • Jiepu Jiang
  • Shuguang Han

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Data Science
  • Feedback
  • Information Operations
  • Information Science
  • Language
  • Maximum Likelihood Estimation
  • Probability
  • Standards
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Information Retrieval
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval