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公开(公告)号：US20180365528A1
公开(公告)日：2018-12-20
申请号：US15622131
申请日：2017-06-14
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Dongxu Duan , JIAN MIN JIANG , ZHONG SU , LI ZHANG , SHI WAN ZHAO
CPC classification number: G06K9/6269 , G06K9/00416 , G06K9/726 , G06N3/0445 , G06N3/0454
Abstract: A computer-implemented method and a system are proposed. According to the method, in response to receiving a character, a first representation of the character is generated by performing word embedding processing on the character. The first representation is related to context of the character. A second representation of the character is generated by performing convolutional neural network (CNN) processing on the character. The second representation is related to a hieroglyphic feature of the character. A label for the character is determined by performing recurrent neural network (RNN) processing on the first representation and the second representation. The label indicates an attribute of the character related to the context.
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公开(公告)号：US20170124599A1
公开(公告)日：2017-05-04
申请号：US14954504
申请日：2015-11-30
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： KEKE CAI , HONGLEI GUO , JIAN MIN JIANG , ZHONG SU , CHANGHUA SUN , GUOYU TANG
CPC classification number: G06Q30/0627 , G06Q30/0255 , G06Q30/0276 , G06Q30/0282 , G06Q30/0623
Abstract: Technical solutions are described for displaying product labels for a product to a user, where the product is associated with a first category. An example method includes analyzing product reviews posted by the user for a set of other products, which includes a second product from a second category, distinct from the first category. The method also includes identifying a set of product labels personalized for the user based on the analysis of the product reviews for other products, including the second product from the second category. The method also includes obtaining a plurality of product labels associated with the product that is being displayed to the user, based on product labels common to the set of product labels for the user and the plurality of product labels of the product. The method also includes displaying the subset of product labels as part of the information of the product.
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公开(公告)号：US20220208373A1
公开(公告)日：2022-06-30
申请号：US17139014
申请日：2020-12-31
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Ya Bin Dang , Ke Wang , Jian Wang , JIAN MIN JIANG
Abstract: A machine-guided inquiry recommendation for medical diagnosis. Generate a knowledge graph data structure using one or more electronic medical guideline documents. Evaluate a likelihood value for one or more diseases based on the knowledge graph data structure. Generate a best next inquiry question for use in a medical diagnosis process.
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Patent Agency Ranking
公开(公告)号：US20210081502A1
公开(公告)日：2021-03-18
申请号：US16569874
申请日：2019-09-13
Applicant: International Business Machines Corporation
Inventor： JIAN MIN JIANG , JIAN Wang , SONGFANG HUANG
Abstract: Method and apparatus are presented for receiving a medical or medical condition related input term or phrase in a source language, and translating the term or phrase from the source language into at least one target language to obtain a set of translated terms of the input term. For each translated term in the set of translations, the method and apparatus further translate the set of translations back into the source language to obtain an output list of standard versions of the input term, scoring each entry of the output list as to probability of being the most standard version of the input term, and providing the entry of the output list that has the highest score to a user.
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公开(公告)号：US20170124623A1
公开(公告)日：2017-05-04
申请号：US14930767
申请日：2015-11-03
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： KEKE CAI , HONGLEI GUO , JIAN MIN JIANG , ZHONG SU , CHANGHUA SUN , GUOYU TANG
CPC classification number: G06Q30/0627 , G06Q30/0255 , G06Q30/0276 , G06Q30/0282 , G06Q30/0623
Abstract: Technical solutions are described for displaying product labels for a product to a user, where the product is associated with a first category. An example method includes analyzing product reviews posted by the user for a set of other products, which includes a second product from a second category, distinct from the first category. The method also includes identifying a set of product labels personalized for the user based on the analysis of the product reviews for other products, including the second product from the second category. The method also includes obtaining a plurality of product labels associated with the product that is being displayed to the user, based on product labels common to the set of product labels for the user and the plurality of product labels of the product. The method also includes displaying the subset of product labels as part of the information of the product.
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公开(公告)号：US20230177363A1
公开(公告)日：2023-06-08
申请号：US17457445
申请日：2021-12-03
Applicant: International Business Machines Corporation
Inventor： JING LI , Jian Wang , JIAN MIN JIANG , Zi Ming Huang , Zhen Zhang , WANQING LIU
IPC: G06N5/04 , G06N5/02 , G06F40/295
CPC classification number: G06N5/04 , G06N5/02 , G06F40/295
Abstract: A processor obtains a pair including a question and an answer in natural language; determines at least one entity in the question and an entity type of each of the at least one entity consistent with the schema of a knowledge graph (KG); identifies a subset of candidate query templates based on the entity type of each of the at least one entity, wherein the candidate query templates are generated based on the schema of the KG; composes a set of queries by populating the at least one entity into each of the subset of candidate query templates; executes the set of queries on the KG to generate respective answers; identifies a first answer from the respective answers that is matching with the answer in the pair; and determines a candidate query template, from the subset of candidate query templates, corresponding to the first answer as a query template.
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公开(公告)号：US20180365529A1
公开(公告)日：2018-12-20
申请号：US15848329
申请日：2017-12-20
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： DONGXU DUAN , JIAN MIN JIANG , ZHONG SU , LI ZHANG , SHI WAN ZHAO
CPC classification number: G06K9/6269 , G06K9/00416 , G06K9/726 , G06N3/0445 , G06N3/0454
Abstract: A computer-implemented method and a system are proposed. According to the method, in response to receiving a character, a first representation of the character is generated by performing word embedding processing on the character. The first representation is related to context of the character. A second representation of the character is generated by performing convolutional neural network (CNN) processing on the character. The second representation is related to a hieroglyphic feature of the character. A label for the character is determined by performing recurrent neural network (RNN) processing on the first representation and the second representation. The label indicates an attribute of the character related to the context.
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公开(公告)号：US20180330230A1
公开(公告)日：2018-11-15
申请号：US15590066
申请日：2017-05-09
Applicant: International Business Machines Corporation
Inventor： BIBO HAO , GANG HU , JIAN MIN JIANG , JING MEI , CHANGHUA SUN , GUO TONG XIE
CPC classification number: G06N3/08 , G06F17/2235 , G06F17/2785 , G06N3/02 , H04L67/02
Abstract: A computer implemented method identifies guidelines through use of a neural network by a remote guideline server. A client computer transmits instructions to the remote guideline server to retrieve and evaluate multiple candidate guidelines. The remote guideline server utilizes a neural network to identify a string of terms found in each of the multiple candidate guidelines that match one or more strings of terms from a model guideline; to identify a semantic concept of each of the multiple candidate guidelines that matches one or more semantic concepts from the model guideline; and to identify a structural pattern of each of the multiple candidate guidelines that matches one or more structural patterns of the model guideline. The candidate guidelines that match the model guideline are then sent from the remote guideline server to the client computer.
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