Developing Of An Ontological Interface Agent With Template-based Linguistic Processing Technique For Faq Services

摘要

This paper proposes an ontological Interface agent which works as an assistant between the users and FAQ systems. We integrated several interesting techniques including domain ontology, user modeling, and template-based linguistic processing to effectively tackle the problems associated with traditional FAQ retrieval systems. Specifically, we address the following issues. Firstly, how can an interface agent learn a user's specialty in order to build a proper user model for him/her? Secondly, how can domain ontology help in establishing user models, analyzing user query, and assisting and guiding interface usage? Finally, how can the intention and focus of a user be correctly extracted? Our work features an template-based linguistic processing technique for developing ontological interface agents; a nature language query mode, along with an improved keyword-based query mode; and an assistance and guidance for human-machine interaction. Our preliminary experimentation demonstrates that user intention and focus of up to eighty percent of the user queries can be correctly understood by the system, and accordingly provides the query solutions with higher user satisfaction.