AIRCC's International Journal of Computer Science and Information Technology

The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


Search for answers in specific domains is a new milestone in question answering. Traditionally, question answering has focused on general domain questions. Thus, the most relevant answers (or passages) are selected according to the type of question and the Named Entities included in the possible answers. In this paper, we present a novel approach on question answering over specific (or technical) domains. This proposal allows us to answer questions such as “What article is appropriate for … “, “What are the articles related to … “, these kind of questions cannot be answered by a general question answering system. Our approach is based on a set of laws of a specific domain, which contain a large set of laws regarding the work organized into a hierarchy. We consider generic concepts such as “article” semantic categories. Our results on the corpus of Federal Labor Law show that this approach is effective and highly reliable.

Keywords

Question Answering, Search for Answers, Mobiles, Intelligent Agents, & Question Answering.
User
Notifications
Font Size