Venue Recommendation and Web Search Based on Anchor Text

Abstract

This paper presents the University of Amsterdam's participation in TREC 2014. For the Contextual Suggestion Track, we experimented with the use of anchor text representations in the language modeling framework, and base our runs either on full ClueWeb12 or the subset of touristic aggregators (e.g., tripadvisor) provided by the organizers of the track. We also look at the effectiveness of priors (in particular, PageRank) and ways of formulating the query based on the context. Our main finding is that the anchor text representation is effective for retrieving candidate attractions, and performs better than a standard document text index. A linear combination of both anchor and document text leads to further improvement. For the Web Track, we continued our experiment with the fusion of anchor text relative to the text-based baseline run. Our main finding is, again, that the combination of anchor and document text leads to improvement, and we demonstrate how the fusion weight can be used as a handle to tune the amount of risk acceptable for the risk sensitive evaluation.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2014
Accession Number
ADA618624

Entities

People

  • Jaap Kamps
  • Seyyed H. Hashemi

Organizations

  • University of Amsterdam

Tags

DTIC Thesaurus Topics

  • Abstracts
  • African Americans
  • Data Sets
  • Equations
  • Filters
  • Information Retrieval
  • Judgment
  • Language
  • Maximum Likelihood Estimation
  • Models
  • Observation
  • Probabilistic Models
  • Probability
  • Standards
  • Test And Evaluation
  • United States
  • Universities

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Information Retrieval
  • Systems Analysis and Design