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Search for Answers in Domain-Specific Supported by Intelligent Agents


Affiliations
1 Computer Science, Universidad Autonoma de Puebla, Puebla, Mexico
2 Universidad Autónoma de Puebla, Puebla, Mexico
 

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.
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Abstract Views: 357

PDF Views: 168




  • Search for Answers in Domain-Specific Supported by Intelligent Agents

Abstract Views: 357  |  PDF Views: 168

Authors

Fernando Zacarias
Computer Science, Universidad Autonoma de Puebla, Puebla, Mexico
Rosalba Cuapa
Universidad Autónoma de Puebla, Puebla, Mexico
Guillermo De Ita
Computer Science, Universidad Autonoma de Puebla, Puebla, Mexico
Miguel Bracamontes
Computer Science, Universidad Autonoma de Puebla, Puebla, Mexico

Abstract


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.

References