公开(公告)号：US20180121434A1

公开(公告)日：2018-05-03

申请号：US15625379

申请日：2017-06-16

Applicant: Beijing Baidu Netcom Science And Technology Co., Ltd.

Inventor： Di JIANG ,  Lei SHI ,  Zeyu CHEN ,  Jiajun JIANG ,  Rongzhong LIAN

IPC: G06F17/30 ,  G06N3/08 ,  G06F17/16

CPC classification number: G06F16/24578 ,  G06F16/3334 ,  G06F16/3347 ,  G06F17/16 ,  G06N3/02 ,  G06N3/08

Abstract: A method and an apparatus for recalling a search result based on a neural network are provided, the method comprising: receiving a query and collecting a plurality of search results corresponding to the query; acquiring a first feature vector corresponding to the query, and acquiring second feature vectors corresponding to titles of the plurality of search results respectively; acquiring similarities between the first feature vector and the second feature vectors respectively, and acquiring semantic matching scores between the query and the plurality of search results respectively according to the similarities; and determining at least one target search result from the plurality of search results according to the semantic marching scores, wherein the at least one target search result is regarded as the search result recalled according to the query.

公开(公告)号：US20180293507A1

公开(公告)日：2018-10-11

申请号：US15945611

申请日：2018-04-04

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Rongzhong LIAN ,  Zeyu CHEN ,  Di JIANG ,  Jiajun JIANG ,  Jingzhou HE

IPC: G06N7/00 ,  G06F17/30

Abstract: Method and apparatus for extracting keywords based on artificial intelligence, a device and readable medium. Based on a topic model, predicting a distribution probability of a target document in each topic among multiple topics; calculating correlation between word vectors of respective words in multiple words of the target document and topic vectors of respective topics in multiple topics, wherein the word vectors of words and topic vectors of respective topics are all generated based on a word vector model; extracting, from the multiple words, words as keywords of the target document, according to distribution probabilities of words in respective topics and the correlation between the word vectors of the respective words and the topic vectors of the respective topics in multiple topics. Keywords are extracted according to the distribution probabilities of words in topics and the correlation between word vectors of words and topic vectors of topics in multiple topics.