WHU at TREC KBA Vital Filtering Track 2014.

摘要

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.