Laval University and Lakehead University Experiments at TREC 2015 Contextual Suggestion Track

Abstract

In this paper we describe our effort on TREC Contextual Suggestion Track. We present are commendation system that built upon Elastic Search along with a machine learning re-ranking model. We utilize real world users opinion as well as other information to build user profiles. With profile information, we then construct customized Elastic Search queries to search on various fields. After that, a learning to rank regressor is implemented to give better ranking results. Track results of our submitted runs show the effectiveness of the system.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 2015
Accession Number
AD1004778

Entities

People

  • Jian Mo
  • Luc Lamontagne
  • Richard Khoury

Organizations

  • Laval University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Commerce
  • Competition
  • Computer Science
  • Databases
  • Engineering
  • Language
  • Learning
  • Machine Learning
  • Precision
  • Software Development
  • Test And Evaluation
  • Training
  • Universities
  • Web Service
  • Wireless Computer Networks

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Information Retrieval

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval
  • AI & ML - Neural Networks