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公开(公告)号:US10606949B2
公开(公告)日:2020-03-31
申请号:US15921386
申请日:2018-03-14
Inventor: Zhifan Zhu , Shikun Feng , Kunsheng Zhou , Jingzhou He
Abstract: This disclosure discloses an artificial intelligence based method and apparatus for checking a text. An embodiment of the method comprises: lexing a first to-be-checked text and a second to-be-checked text respectively, determining word vectors of the lexed words to generate a first word vector sequence and a second word vector sequence; inputting the first word vector sequence and the second word vector sequence respectively into a pre-trained convolutional neural network containing at least one multi-scale convolutional layer, identifying vector sequences in a plurality of vector sequences outputted by a last multi-scale convolutional layer as eigenvector sequences, to obtain eigenvector sequence groups respectively corresponding to the texts; combining eigenvector sequences in each eigenvector sequence group to generate a combined eigenvector sequence; and analyzing the generated combined eigenvector sequences to determine whether the first text and the second text pass a similarity check. The embodiment improves the flexibility in checking a text.
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公开(公告)号:US10831993B2
公开(公告)日:2020-11-10
申请号:US16306488
申请日:2016-12-22
Inventor: Kunsheng Zhou , Jingzhou He , Lei Shi , Shikun Feng
IPC: G06F40/242 , G06F16/00 , G06F40/30 , G06N3/02 , G06F40/20 , G06F40/284 , G06F17/18 , G06N3/08
Abstract: Disclosed are a method and an apparatus for constructing a binary feature dictionary. The method may include: extracting binary features from a corpus; calculating a preset statistic of each binary feature; and selecting a preset number of binary features in sequence according to the preset statistic to constitute the binary feature dictionary.
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公开(公告)号:US20190057164A1
公开(公告)日:2019-02-21
申请号:US16054559
申请日:2018-08-03
Inventor: Kunsheng Zhou , Shikun Feng , Zhifan Zhu , Jingzhou He
Abstract: The disclosure discloses a search method and apparatus based on artificial intelligence. An embodiment of the method includes: receiving search information entered by a user; determining a candidate to-be-pushed message set based on the search information; predicting a probability of being clicked for a candidate to-be-pushed message in the candidate to-be-pushed message set using a pre-trained scoring model based on the search information and the candidate to-be-pushed message set, the scoring model being obtained by training based on a pre-stored first search information set, a to-be-pushed message set corresponding to a piece of first search information in the first search information set, and a preset priority of a to-be-pushed message in the to-be-pushed message set; and selecting a preset number of the candidate to-be-pushed messages to form a message sequence in descending order of the probability of being clicked, and pushing the message sequence to a terminal of the user.
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