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1.
公开(公告)号:US20190164072A1
公开(公告)日:2019-05-30
申请号:US16322593
申请日:2016-08-02
Applicant: NEC Corporation
Inventor: Kentarou SASAKI , Daniel Georg ANDRADE SILVA , Yotaro WATANABE , Kunihiko SADAMASA
IPC: G06N5/04
Abstract: An inference system according to the present invention relates to inference from a starting state and a first rule set to an ending state. The inference system includes: a memory; and at least one processor coupled to the memory. The processor performs operations. The operations includes: receiving a parameter for use in selecting a second rule set from the first rule set; and visualizing the second rule set associated with the parameter.
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公开(公告)号:US20180314951A1
公开(公告)日:2018-11-01
申请号:US15772678
申请日:2015-11-10
Applicant: NEC CORPORATION
Inventor: Kunihiko SADAMASA , Takashi ONISHI , Kentarou SASAKI , Yotaro WATANABE , Kai ISHIKAWA , Satoshi MORINAGA
CPC classification number: G06N5/04
Abstract: A reasoning system that enables reasoning when there is a shortage of knowledge. An input unit receives a start state and an end state. A rule candidate generation unit identifies a first state, obtained by tracking one or more known rules from the start state, and a second state, obtained by backtracking one or more known rules from the end state, respectively. The generation unit generates a rule candidate relating to the first state and the second state or generates a rule candidate relating to the first state and a rule candidate relating to the second state. A rule selection unit selects, based on feasibility of the generated rule candidate, which is calculated based on one or more known rules, the generated rule candidate as a new rule. A derivation unit derives the end state from the start state, based on one or more known rules and the new rule.
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3.
公开(公告)号:US20190266503A1
公开(公告)日:2019-08-29
申请号:US16347734
申请日:2017-10-11
Applicant: NEC CORPORATION
Inventor: Takashi ONISHI , Satoshi MORINAGA , Yotaro WATANABE
Abstract: A parameter optimization apparatus 10 includes a simulator 11, which executes a simulation on a specific event by using a parameter as an input, a data interpreter 2, which converts the result of the output from the simulator 11 into a logical expression, an inference unit 13, which estimates a phenomenon that occurs in the specific event by using the logical expression, a query representing a target state of the specific event, and knowledge information prepared in advance for the specific event and generates an inference path from the estimated phenomenon, and a parameter determiner 14, which determines from the inference path a new parameter that is an input in the simulation, and when the new parameter is determined, the simulator 11 executes the simulation on the specific event by using the new parameter as an input.
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公开(公告)号:US20200293929A1
公开(公告)日:2020-09-17
申请号:US16083992
申请日:2017-03-09
Applicant: NEC Corporation
Inventor: Kentarou SASASKI , Daniel Georg ANDRADE SILVA , Yotaro WATANABE , Kunihiko SADAMASA
Abstract: An inference method according to the present invention in an inference system inferring a probability that an ending state holds based on a starting state and a rule set, the method includes: when a rule set derived by excluding one rule from rules constituting a first rule set is set as a second rule set, a probability that the ending state holds based on the starting state and the first rule set is set as a first inference result, and a probability that the ending state holds based on the starting state and the second rule set is set as a second inference result, calculating an importance being an indicator indicating magnitude of a difference between the first inference result and the second inference result; and outputting the rule and the importance of the rule, being associated with each other for each of the excluded rule.
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5.
公开(公告)号:US20190180192A1
公开(公告)日:2019-06-13
申请号:US16323285
申请日:2016-08-18
Applicant: NEC Corporation
Inventor: Daniel Georg ANDRADE SILVA , Yotaro WATANABE , Satoshi MORINAGA , Kunihiko SADAMASA
IPC: G06N5/02 , G06F16/901 , G06N7/00
Abstract: An information processing system for learning new probabilistic rules even if only one training sample is given. A learning system (100) includes a KB (knowledge base) storage (110), a rule generator (130), and a weight calculator (140). The KB storage (110) stores a KB including a knowledge storage for storing rules between events among a plurality of events. The rule generator (130) generates one or more new rules based on the rules and an implication score between the events. The weight calculator (140) calculates a weight of the one or more new rules for probabilistic reasoning based on the implication score.
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