Publication | Open Access
Question Answering Systems: Survey and Trends
129
Citations
25
References
2015
Year
EngineeringSemantic SearchQuery ModelRdf DataSemantic WebCorpus LinguisticsText MiningNatural Language ProcessingInformation RetrievalData ScienceComputational LinguisticsLanguage StudiesMachine TranslationQuestion AnsweringNatural Language InterfaceComplex QueriesAutomated ReasoningLinguisticsInteractive Information Retrieval
The need to query information content available in various formats including structured and unstructured data (text in natural language, semi-structured Web documents, structured RDF data in the semantic Web, etc.) has become increasingly important. Thus, Question Answering Systems (QAS) are essential to satisfy this need. QAS aim at satisfying users who are looking to answer a specific question in natural language. In this paper we survey various QAS. We give also statistics and analysis. This can clear the way and help researchers to choose the appropriate solution to their issue. They can see the insufficiency, so that they can propose new systems for complex queries. They can also adapt or reuse QAS techniques for specific research issues.
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