Question Focus Recognition in Question Answering Systems

Abstract

Question Answering (QA) Systems are systems that attempts to answer questions posed by human in natural language. As a part of the QA system comes the question processing module. The question processing module serves several tasks including question classification and focus identification. Question classification and focus identification play crucial role in Question Answering systems. This paper describes and evaluates the techniques we developed for answer type detection based on question classification and focus identification in Arabic Question Answering systems. Question classification helps in providing the type of the expected answer and hence directing the answer extraction module to apply the proper technique for extracting the answer. While focus identification helps in ranking the candidate answers. Consequently, that has increased the accuracy of answers produced by the QA system. Question processing module involves analysing the questions in order to extract the important information for identifying what is being asked and how to approach answering it, and this is one of the most important components of a QA system. Therefore, we propose methods for solving two main problems in question analysis, namely question classification and focus extraction.

Developing an Intelligent Question Answering System

“…For instance, in question "What movie did Rachel Carson starred in 1962? ", the question focus "movie" can be used to provide supporting indicators to locate the answer in the subsequent process, by seeking for phrases containing the question focus [24]. The different additional NLP pre-processing steps that a question goes through includes stop word removal [25] ,tokenization [26], stemming [27]where words with less importance are removed from the question , and question expansion [28] where synonyms for some terms of the question are added to improve the information retrieval process.…”