Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track

Abstract

Users may have a variety of tasks that give rise to issuing a particular query. The goal of the Tasks Track at TREC2015 was to identify all aspects or subtasks of a users task as well as the documents relevant to the entire task. This was broken into two parts: (1) Task Understanding which judged relevance of key phrases or queries to the original query (relative to a likely task that would have given rise to both); (2) Task Completion which performed document retrieval and measured usefulness to any task a user with the query might be peforming through either a completion measure that uses both relevance and usefulness criteria or more simply through an ad hoc retrieval measure of relevance alone. We submitted a run in the Task Understanding track. In particular, since the anchor text graph has proven useful in the general realm of query reformulation [2], we sought to quantify the value of extracting key phrases from anchor text in the broader setting of the task understanding track.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 2015
Accession Number
AD1004785

Entities

People

  • Paul N. Bennett
  • Ryen W. White

Tags

DTIC Thesaurus Topics

  • Availability
  • Boundaries
  • Computations
  • Extraction
  • Filters
  • Filtration
  • Frequency
  • Javascript Programming Language
  • Literature
  • Personality
  • Random Walk
  • Removal
  • Test And Evaluation
  • Universities

Fields of Study

  • Computer science

Readers

  • Information Retrieval
  • Instructional Design and Training Evaluation.
  • Systems Analysis and Design