<p>The rapid growth in the development of Internet-basedinformation systems increases the demand for natural langu-ageinterfaces that are easy to set up and maintain. Unfortunately,the problem of understanding natural language queries is farfrom being solved. Therefore this research proposes a simplertask of matching a one-sentence-long user question to a numberof question templates, which cover the knowledge domain of theinformation system, without in-depth understanding of the userquestion itself.The research started with development of an FAQ(Frequently Asked Question) answering system that providespre-stored answers to user questions asked in ordinary English.The language processing technique developed for FAQ retrievaldoes not analyze user questions. Instead, analysis is appliedto FAQs in the database long before any user questions aresubmitted. Thus, the work of FAQ retrieval is reduced tokeyword matching without understanding the questions, and thesystem still creates an illusion of intelligence.Further, the research adapted the FAQ answering techniqueto a question-answering interface for a structured database,e.g., relational database. The entity-relationship model of thedatabase is covered with an exhaustive collection of questiontemplates - dynamic, parameterized "frequently asked questions"- that describe the entities, their attributes, and therelationships in form of natural language questions. Unlike astatic FAQ, a question template contains entity slots - freespace for data instances that represent the main concepts inthe question. In order to answer a user question, the systemfinds matching question templates and data instances that fillthe entity slots. The associated answer templates create theanswer.Finally, the thesis introduces a generic model oftemplate-based question answering which is a summary andgene-ralization of the features common for the above systems:they (i) split the application-specific knowledge domain into anumber of question-specific knowledge domains, (ii) attach aquestion template, whose answer is known in advance, to eachknowledge domain, and (iii) match the submitted user questionto each question template within the context of its ownknowledge domain.</p><p><b>Keywords:</b>automated question answering, FAQ answering,question-answering system, template-based question answering,question template, natural language based interface</p>

The rapid growth in the development of Internet-basedinformation systems increases the demand for natural langu-ageinterfaces that are easy to set up and maintain. Unfortunately,the problem of understanding natural language queries is farfrom being solved. Therefore this research proposes a simplertask of matching a one-sentence-long user question to a numberof question templates, which cover the knowledge domain of theinformation system, without in-depth understanding of the userquestion itself.The research started with development of an FAQ(Frequently Asked Question) answering system that providespre-stored answers to user questions asked in ordinary English.The language processing technique developed for FAQ retrievaldoes not analyze user questions. Instead, analysis is appliedto FAQs in the database long before any user questions aresubmitted. Thus, the work of FAQ retrieval is reduced tokeyword matching without understanding the questions, and thesystem still creates an illusion of intelligence.Further, the research adapted the FAQ answering techniqueto a question-answering interface for a structured database,e.g., relational database. The entity-relationship model of thedatabase is covered with an exhaustive collection of questiontemplates - dynamic, parameterized "frequently asked questions"- that describe the entities, their attributes, and therelationships in form of natural language questions. Unlike astatic FAQ, a question template contains entity slots - freespace for data instances that represent the main concepts inthe question. In order to answer a user question, the systemfinds matching question templates and data instances that fillthe entity slots. The associated answer templates create theanswer.Finally, the thesis introduces a generic model oftemplate-based question answering which is a summary andgene-ralization of the features common for the above systems:they (i) split the application-specific knowledge domain into anumber of question-specific knowledge domains, (ii) attach aquestion template, whose answer is known in advance, to eachknowledge domain, and (iii) match the submitted user questionto each question template within the context of its ownknowledge domain. Keywords:automated question answering, FAQ answering,question-answering system, template-based question answering,question template, natural language based interface / <p>NR 20140805</p>