USING ONTOLOGICAL INFORMATION IN OPEN DOMAIN TYPE COERCION
    1.
    发明公开
    USING ONTOLOGICAL INFORMATION IN OPEN DOMAIN TYPE COERCION 审中-公开
    维尔纽斯医学家信息BEI EINER BEDROHUNG DURCH OFFENEDOMÄNEN

    公开(公告)号:EP2616927A4

    公开(公告)日:2017-02-22

    申请号:EP11827693

    申请日:2011-09-24

    Applicant: IBM

    CPC classification number: G06N5/02 G06F17/30654

    Abstract: A system, method and computer program product for efficiently retrieving relevant passages to questions based on a corpus of data. A processor device receives an input query and performs a query analysis to obtain searchable query terms. The processor performs: matching metadata associated with one or more documents against the query terms. The document metadata includes one or more of: a title of the documents, one or more user tags or clouds. Then the processor device performs: mapping matched document metadata to corresponding one or more documents; identifying corresponding matched documents to form a subcorpus of documents; and conducting a search in the data subcorpus using the searchable query terms to obtain one or more passages relevant input query from the identified documents.

    Abstract translation: 一种系统,方法和计算机程序产品,用于根据数据语料库高效地检索问题的相关段落。 处理器设备接收输入查询并执行查询分析以获得可搜索查询项。 处理器执行:根据查询条件匹配与一个或多个文档相关联的元数据。 文档元数据包括以下一个或多个:文档的标题,一个或多个用户标签或云。 然后处理器设备执行:将匹配的文档元数据映射到相应的一个或多个文档; 识别相应的匹配文档以形成文档的副标题; 以及使用可搜索的查询条件在数据子库中进行搜索以从所识别的文档中获得一个或多个相关输入查询的段落。

    PROVIDING QUESTION AND ANSWERS WITH DEFERRED TYPE EVALUATION USING TEXT WITH LIMITED STRUCTURE
    2.
    发明公开
    PROVIDING QUESTION AND ANSWERS WITH DEFERRED TYPE EVALUATION USING TEXT WITH LIMITED STRUCTURE 审中-公开
    计提TEXT临时结构的基础问题与解答与延迟的评估

    公开(公告)号:EP2616926A4

    公开(公告)日:2015-09-23

    申请号:EP11827460

    申请日:2011-09-21

    Applicant: IBM

    CPC classification number: G06F17/30675

    Abstract: A system, method and computer program product for conducting questions and answers with deferred type evaluation based on any corpus of data. The method includes processing a query including waiting until a “Type” (i.e. a descriptor) is determined AND a candidate answer is provided. Then, a search is conducted to look (search) for evidence that the candidate answer has the required Lexical Answer Type (e.g., as determined by a matching function that can leverage a parser, a semantic interpreter and/or a simple pattern matcher). Prior to or during candidate answer evaluation, a process is provided for extracting and storing collections of entity-type pairs from semi-structured text documents. During QA processing and candidate answer scoring, a process is implemented to match the query LAT against the lexical type of each provided candidate answer and generate a score judging a degree of match.

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