Exploration of Opinion-aware Approach to Contextual Suggestion

Abstract

In this paper we describe our effort on TREC Contextual Suggestion Track. Using resources such as description or websites of example suggestions to build user profile has been proven to be effective on last year's TREC. This year we also leverage the power of using user profile. Real world opinions of the suggestions are used in our method to build both user profile and candidate suggestion profile. Two ranking method are investigated to rank the candidate suggestions: linear interpolation and learning to rank. For description generation, we apply the similar method as used in the last year. The structured description combines the category information of the suggestion, meta-description of the website, reviews of the suggestion and the similar example suggestions that the user liked. Official results of our submitted runs show the effectiveness of the proposed method.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2014
Accession Number
ADA618606

Entities

People

  • Hui Fang
  • Peilin Yang

Organizations

  • University of Delaware

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Commerce
  • Demographic Cohorts
  • Information Operations
  • Interpolation
  • Learning
  • Mathematics
  • Measurement
  • Mental Processes
  • Precision
  • Psychological Phenomena And Processes
  • Ratings
  • Standards
  • Supervised Machine Learning
  • Training
  • Websites

Fields of Study

  • Computer science

Readers

  • Computer Science.
  • Information Retrieval
  • Systems Analysis and Design