An Exploration of Ranking-based Strategy for Contextual Suggestion

Abstract

We describe our efforts in TREC 2012 Contextual Suggestion Track. The task is to provide sug- gestions to users based on their personal interests as well as their contexts. To tackle the problem, we propose to rank candidate suggestions based on their similarity to the personal profile and that to the contexts (i.e. geographic and temporal information). The ranking function is computed based on the similarity between a suggestion and the places that the user like and the dis-similarity between the suggestion and the places disliked by the user. The similarities are computed based on the either the category or description of the suggestions.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2012
Accession Number
ADA576857

Entities

People

  • Hui Fang
  • Peilin Yang

Organizations

  • University of Delaware

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Commerce
  • Computers
  • Data Sets
  • Delaware
  • Engineering
  • Governments
  • Information Operations
  • Information Retrieval
  • Maryland
  • New York
  • Standards
  • Universities
  • Websites

Fields of Study

  • Computer science

Readers

  • Information Retrieval
  • Neural Network Machine Learning.