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- W2015556048 abstract "We present a strategy for answering fact-based natural language questions that is guided by a characterization of real-world user queries. Our approach, implemented in a system called Aranea, extracts answers from the Web using two different techniques: knowledge annotation and knowledge mining. Knowledge annotation is an approach to answering large classes of frequently occurring questions by utilizing semi-structured and structured Web sources. Knowledge mining is a statistical approach that leverages massive amounts of Web data to overcome many natural language processing challenges. We have integrated these two different paradigms into a question answering system capable of providing users with concise answers that directly address their information needs." @default.
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- W2015556048 date "2003-11-03" @default.
- W2015556048 modified "2023-09-30" @default.
- W2015556048 title "Question answering from the web using knowledge annotation and knowledge mining techniques" @default.
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- W2015556048 doi "https://doi.org/10.1145/956863.956886" @default.
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