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公开(公告)号：US20220198369A1
公开(公告)日：2022-06-23
申请号：US17441783
申请日：2019-03-28
Applicant: NEC Corporation
Inventor： Masafumi OYAMADA , Keigo KIMURA , Kunihiro TEKEOKA
IPC: G06Q10/06
Abstract: The acquisition unit 52A acquires task request information S1, which is request information regarding a utilization of data owned by a data owner, from an owner terminal 2 used by the data owner. The determination unit 53A determines, on a basis of the task request information S1, whether or not there is a task that can be performed by use of the data. The notification unit 54A notifies the owner terminal 2 of recommended task information S2 that is information regarding the above-described task when the determination unit 53A determines that there is the above-described task.
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公开(公告)号：US20250148316A1
公开(公告)日：2025-05-08
申请号：US18832227
申请日：2022-01-31
Applicant: NEC Corporation
Inventor： Genki KUSANO , Masafumi OYAMADA , Kunihiro TAKEOKA
Abstract: In order to apply a text-based label inference approach to infer a label to be assigned to target data in a common data form, an inference apparatus (1) includes: a data converting section (11) for converting target data subject to label assignment into text; and a label inferring section (12) for inferring a label to be assigned to the target data, in accordance with a label inference model for inferring a label to be assigned to text and the text obtained by the converting carried out by the data converting means.
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公开(公告)号：US20250124313A1
公开(公告)日：2025-04-17
申请号：US18703421
申请日：2021-11-11
Applicant: NEC Corporation
Inventor： Kosuke AKIMOTO , Kunihiro TAKEOKA , Masafumi OYAMADA
IPC: G06N5/048 , G06F40/279
Abstract: To determine, with high accuracy, a label to be given to an object even in a case where only a single prediction model exists, an information processing apparatus (1) includes: an acquisition unit (11) that acquires a set of objects; an evaluation unit (12) that evaluates a degree of similarity between objects included in the set of objects and identifies one or a plurality of similar objects which are similar to a prediction target object; and a prediction unit (13) that determines a label to be given to the prediction target object with reference to a similar label(s), the similar label(s) being a label(s) which is/are given to each of the one or a plurality of similar objects and which has/have been predicted by a prediction model.
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公开(公告)号：US20250086209A1
公开(公告)日：2025-03-13
申请号：US18554311
申请日：2023-05-12
Applicant: NEC CORPORATION
Inventor： Masafumi OYAMADA
IPC: G06F16/33 , G06F16/338 , G06F40/30
Abstract: To improve reliability of a result of language processing carried out with use of a machine learning model, an information processing apparatus includes at least one processor that carries out: an acquisition process of acquiring a target text; an extraction process of extracting a document related to the target text; a rewriting process of rewriting the target text with use of the document; a generation process of generating a text corresponding to the rewritten target text with use of a machine learning model trained to generate a text based on an input text; and an output process of outputting a result obtained by adding information identifying the document to the generated text.
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公开(公告)号：US20240411993A1
公开(公告)日：2024-12-12
申请号：US18709852
申请日：2022-03-02
Applicant: NEC Corporation
Inventor： Masafumi OYAMADA
IPC: G06F40/289
Abstract: In order to make it possible to automatically carry out verification of a hypothetical sentence, a verification apparatus (1) includes: a hypothetical sentence acquisition section (11) for acquiring a hypothetical sentence which is to be verified; and a verification section (12) for determining truth or falsity of the hypothetical sentence based on a degree to which the hypothetical sentence is entailed in a premise sentence that has been generated from a finding derived from verification data for use in verification of a hypothesis.
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Patent Agency Ranking
公开(公告)号：US20230065007A1
公开(公告)日：2023-03-02
申请号：US17797951
申请日：2020-02-25
Applicant: NEC Corporation
Inventor： Masafumi OYAMADA
IPC: G06F40/279 , G06F40/268 , G06F40/242
Abstract: The acquiring unit which acquires for each item name, one or more words composing an item name from the item name belonging to a group including a plurality of item names, respectively. The computing unit which computes for each item name, relevance that is a degree to which the acquired word is related to the item name, respectively. The determination unit which determines words among the acquired words as candidates for a classification name of each item represented by the plurality of item names. The sum over the plurality of item names of the computed relevance of the determined word is up to the top Mth (M is a natural number).
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公开(公告)号：US20190340670A1
公开(公告)日：2019-11-07
申请号：US15745874
申请日：2016-10-27
Applicant: NEC Corporation
Inventor： Katsufumi TOMOBE , Masafumi OYAMADA , Shinji NAKADAI
Abstract: An object is to provide a clustering system capable of performing clustering of a plurality of types of items to be able to recommend an item whose corresponding textual data exists but relational data with another type of item does not exist, to the other type of item. A first clustering means 3001 performs clustering of first IDs, based on the relational data. A second clustering means 3002 performs clustering of second IDs, based on the relational data and textual data associated with the second IDs. A topic assignment means 3003 assigns a topic for each word included in textual data corresponding to each second ID. A parameter decision means 3004 decides a parameter used for first clustering processing, a parameter used for second clustering processing, and a parameter used for topic assignment processing. The processing described above is repeated until it is determined that a predetermined condition is satisfied.
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公开(公告)号：US20190205361A1
公开(公告)日：2019-07-04
申请号：US16322549
申请日：2017-07-25
Applicant: NEC Corporation
Inventor： Hideaki SATO , Shinji NAKADAI , Masafumi OYAMADA
CPC classification number: G06F17/18 , G06F16/00 , G06F17/245 , G06N20/00
Abstract: A learning means 71 learns, on the basis of learning data including a table including a meaning of a column, and a meaning of the table, a model indicating regularity between a distribution of attribute values according to the meaning of the column in the table and the meaning of the table. An estimating means 72 estimates, on the basis of a distribution of attribute values according to a meaning of a column in an input table and the model, a meaning of the table.
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公开(公告)号：US20190012573A1
公开(公告)日：2019-01-10
申请号：US15752469
申请日：2017-03-03
Applicant: NEC CORPORATION
Inventor： Masafumi OYAMADA , Shinji NAKADAI
Abstract: A co-clustering system capable of further improving prediction accuracy of a prediction model for each cluster is provided. Based on first master data, second master data, and fact data indicating a relation between a first ID which is an ID of a record in the first master data and a second ID which is an ID of a record in the second master data, the co-clustering means 71 executes co-clustering processing of co-clustering the first IDs and the second IDs. The prediction model generation means 72 executes prediction model generation processing of generating a prediction model for each cluster of at least the first ID. The determination means 73 determines whether or not a predetermined condition is satisfied. The prediction model generation processing and the co-clustering processing are repeated until it is determined that the predetermined condition is satisfied.
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公开(公告)号：US20180240019A1
公开(公告)日：2018-08-23
申请号：US15756108
申请日：2017-07-25
Applicant: NEC CORPORATION
Inventor： Hideaki SATO , Masafumi OYAMADA , Shinji NAKADAI
CPC classification number: G06N5/02 , G06F16/221 , G06F17/245 , G06F17/2785
Abstract: A learning means 71 learns, based on learning data containing the meaning of a column in a table and the meaning of the table, a model indicating regularity between the meaning of the column in the table and the meaning of the table. An estimation means 72 estimates the meaning of the table based on the meaning of a column of a table to be input and the model.
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