Accession Number:

ADA618666

Title:

WHU at TREC KBA Vital Filtering Track 2014

Descriptive Note:

Conference paper

Corporate Author:

WUHAN UNIV HUBEI (CHINA)

Report Date:

2014-11-01

Pagination or Media Count:

5.0

Abstract:

This paper describes the WHU IRLAB participation to the Vital Filtering task of the TREC 2014 Knowledge Base Acceleration Track. In this task, we implemented a system to detect vital documents that could be used for a human editor to update or create the profile of an entity. Our approach is to view the problem as a classification problem and use Stanford NLP Toolkit to extract necessary information. Various kinds of features are leveraged to classify documents to three classes, i.e. vital, useful and non-useful garbage or neutral. We submitted four runs using different combinations of features. The results are presented and discussed.

Subject Categories:

  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE