Constructing a Question Corpus for Textual Semantic Relations

13403

Authors

nan

Abstract

AbstractFinding useful questions is a challenging task in Community Question Answering (CQA). There are two key issues need to be resolved: 1) what is a useful question to the given reference question; and furthermore 2) what kind of relations exist between a given pair of questions. In order to answer these two questions, in this paper, we propose a fine-grained inventory of textual semantic relations between questions and annotate a corpus constructed from the WikiAnswers website. We also extract large archives of question pairs with user-generated links and use them as labeled data for separating useful questions from neutral ones, achieving 72.2% of accuracy. We find such online CQA repositories valuable resources for related research.

Keywords

nan

Full Content

nan

Labeled Text

AbstractFinding useful questions is a challenging task in Community Question Answering (CQA). There are two key issues need to be resolved: 1) what is a useful question to the given reference question; and furthermore 2) what kind of relations exist between a given pair of questions. In order to answer these two questions, in this paper, we propose a fine-grained inventory of textual semantic relations between questions and annotate a corpus constructed from the WikiAnswers website. We also extract large archives of question pairs with user-generated links and use them as labeled data for separating useful questions from neutral ones, achieving 72.2% of accuracy. We find such online CQA repositories valuable resources for related research.

Publication Details

Paper ID:
13403
Year:
2012
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan