The University College London at TREC 2008 Enterprise Track

Abstract

The University College London Information Retrieval Group participated in both the Expert Search and Document Search tasks in the TREC2008 Enterprise Track. We used a generic two-stage approach, which consists of a document retrieval stage followed by an expert association discovery stage, for expert finding. Since document search is an integral part of our expert finding approach, we have studied the relationship between document search and expert search. Due to the existence of rich features that can potentially contribute to expert finding, our expert finding approach integrates these features including anchor texts, indegree, and multiple levels of associations between experts and query terms. Our experimental results show that the introduction of features has helped improve the expert finding performance.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2008
Accession Number
ADA512715

Entities

People

  • Jianhan Zhu

Organizations

  • University College London

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Automatic
  • Computing-Related Activities
  • Contracts
  • Data Management
  • Frequency
  • Information Operations
  • Information Retrieval
  • Instructions
  • Integrals
  • Language
  • Local Area Networks
  • Mathematics
  • Probability
  • Standards
  • Universities

Fields of Study

  • Computer science

Readers

  • Information Retrieval
  • Systems Analysis and Design
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval