GENERATING FEATURE EMBEDDINGS FROM A CO-OCCURRENCE MATRIX

    公开(公告)号:US20170228414A1

    公开(公告)日:2017-08-10

    申请号:US15424671

    申请日:2017-02-03

    Applicant: Google Inc.

    Abstract: Methods, and systems, including computer programs encoded on computer storage media for generating compressed representations from a co-occurrence matrix. A method includes obtaining a set of sub matrices of a co-occurrence matrix, where each row of the co-occurrence matrix corresponds to a feature from a first feature vocabulary and each column of the co-occurrence matrix corresponds to a feature from a second feature vocabulary; selecting a sub matrix, wherein the sub matrix is associated with a particular row block and column block of the co-occurrence matrix; assigning respective d-dimensional initial row and column embedding vectors to each row and column from the particular row and column blocks, respectively; and determining a final row embedding vector and a final column embedding vector by iteratively adjusting the initial row embedding vectors and the initial column embedding vectors using the co-occurrence matrix.

    WORD SENSE DISAMBIGUATION USING HYPERNYMS
    2.
    发明申请
    WORD SENSE DISAMBIGUATION USING HYPERNYMS 审中-公开
    WORD SENSE DISAMBIGATION使用HYPERNYMS

    公开(公告)号:US20160292149A1

    公开(公告)日:2016-10-06

    申请号:US14450233

    申请日:2014-08-02

    Applicant: Google Inc.

    CPC classification number: G06F17/2785 G06F16/3344 G06F17/2735

    Abstract: Methods and apparatus related to word sense disambiguation utilizing hypernyms. In some implementations, one or more senses of a word are determined based on hypernyms for the word and an association of the word to the one or more senses is stored. In some implementations, a target word in a textual segment is identified and a word sense to assign to the target word is determined based on hypernyms that are associated with the target word.

    Abstract translation: 与词义消歧相关的方法和设备利用高词。 在一些实施方式中,基于该单词的多义词确定单词的一个或多个感觉,并存储该单词与一个或多个感官的关联。 在一些实施方式中,识别文本段中的目标字,并且基于与目标字相关联的超级词确定要分配给目标词的词义。

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