Search for Answers in Domain Specific Supported by Intelligent Agents

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