公开(公告)号：US10936664B2

公开(公告)日：2021-03-02

申请号：US16321988

申请日：2017-07-26

申请人： National Institute of Information and Communications Technology

发明人： Noriyuki Abe ,  Kanako Onishi ,  Kentaro Torisawa ,  Canasai Kruengkrai ,  Jonghoon Oh ,  Ryu Iida ,  Yutaka Kidawara

IPC分类号： G06F16/9032 ,  G10L15/22 ,  G10L15/26

摘要： A dialogue system includes: a question generating unit receiving an input sentence from a user and generating a question using an expression included in the input sentence, by using a dependency relation; an answer obtaining unit inputting the question generated by the question generating unit to a question-answering system and obtaining an answer to the question from question-answering system; and an utterance generating unit for generating an output sentence to the input sentence, based on the answer obtained by the answer obtaining unit.

公开(公告)号：US10803103B2

公开(公告)日：2020-10-13

申请号：US14898565

申请日：2014-05-15

申请人： National Institute of Information and Communications Technology

发明人： Motoki Sano ,  Istvan Varga ,  Kentaro Torisawa ,  Chikara Hashimoto ,  Kiyonori Ootake ,  Takao Kawai ,  Jonghoon Oh ,  Stijn De Saeger

IPC分类号： G06N20/00 ,  G06F16/33 ,  G06F16/35 ,  G06F16/332 ,  G06F40/211 ,  G06N5/04

摘要： [Object] To provide a system for automatically and reliably collecting information belonging to a given category, and matching the information appropriately in a timely manner.[Solution] A text classifying device 30 analyzes dependency of collected texts by a morpheme analyzing unit 52 and a dependency analyzing unit 54. A problem report collecting unit 64 specifies a core consisting of noun+predicate in a text based on dependency relation of the text, and using a combination of noun classification (trouble/non-trouble) and predicate classification (excitatory/inhibitory), classifies the text to a problem report or the rest, by a method referred to as core-based matrix. Support information collecting device 66 and request message collecting device 68 collect support information and request messages in the similar manner. A matching device 76 matches problem reports and support information collected by problem report collecting unit 64 and support information collecting device 66 by a method referred to as co-occurrence core matrix, and thus associates problem information (support information) with appropriate support information (problem information).

公开(公告)号：US11176328B2

公开(公告)日：2021-11-16

申请号：US16629293

申请日：2018-06-14

申请人： National Institute of Information and Communications Technology

发明人： Jonghoon Oh ,  Kentaro Torisawa ,  Canasai Kruengkrai ,  Ryu Iida ,  Julien Kloetzer

IPC分类号： G06F17/00 ,  G06F40/30 ,  G06F16/33 ,  G06F16/332 ,  G06N3/08

摘要： A question answering device includes: a general word vector converter converting a question and an answer to semantic vectors in accordance with general context; a general sentence level CNN 214, in response to similarities of semantic vectors between words in question and answer and to strength of causality between the words, for weighting each semantic vector to calculate sentence level representations of the question and the answer; a general passage level CNN 218, in response to similarity between sentence level representations of question and answer, and to strength of relation of vectors in the sentence level representations viewed from causality, for weighting the sentence level representation to calculate a passage level representation for the question and answer passage; and a classifier determining whether or not an answer is a correct answer, based on the similarities between outputs from CNNs 214 and 218.

公开(公告)号：US09582487B2

公开(公告)日：2017-02-28

申请号：US14377988

申请日：2013-01-23

申请人： National Institute of Information and Communications Technology

发明人： Chikara Hashimoto ,  Kentaro Torisawa ,  Stijn De Saeger ,  Jonghoon Oh ,  Junichi Kazama

IPC分类号： G06F17/27

CPC分类号： G06F17/27 ,  G06F17/2775 ,  G06F17/2785 ,  G06F17/2795

摘要： A predicate template collector allowing efficient and automatic recognition of predicate templates is adapted to include: a noun pair collector 94 and a noun pair polarity determiner 98 for collecting noun pairs co-occurring with predicate template pairs and determining polarity of relation between nouns, using conjunctions and seed templates; a template pair collector 100, collecting template pairs co-occurring with noun pairs and determining, based on the relation of noun pairs co-occurring with the predicate template pairs and the conjunctions between predicate templates pairs, whether the polarity of excitatory class of predicate template pair is the same or not; a template network builder 106 building a template network connecting predicate templates based on the predicate template pairs and match/mismatch of excitatory class thereof; and a template excitation value calculator 112 calculating excitation value to be assigned to each node, using the excitation value of seed templates and the relation between each of the nodes in the network.

摘要翻译： 允许对谓词模板进行有效和自动识别的谓词模板收集器适于包括：名词对收集器94和名词对极性确定器98，用于收集与谓词模板对共存的名词对，并使用连词确定名词之间的关系的极性 和种子模板; 模板对收集器100，收集与名词对共同存在的模板对，并且基于与谓词模板对共同出现的名词对与谓词模板对之间的连接的关系确定谓词模板的兴奋类的极性 对是一样的 模板网络构建器106构建基于谓词模板对连接谓词模板的模板网络，并且其兴奋类别的匹配/不匹配; 以及模板激励值计算器112，使用种子模板的激励值和网络中的每个节点之间的关系来计算要分配给每个节点的激励值。

公开(公告)号：US20150039296A1

公开(公告)日：2015-02-05

申请号：US14377988

申请日：2013-01-23

申请人： National Institute of Information and Communications Technology

发明人： Chikara Hashimoto ,  Kentaro Torisawa ,  Stijn De Saeger ,  Jonghoon Oh ,  Junichi Kazama

IPC分类号： G06F17/27

CPC分类号： G06F17/27 ,  G06F17/2775 ,  G06F17/2785 ,  G06F17/2795

摘要： A predicate template collector allowing efficient and automatic recognition of predicate templates is adapted to include: a noun pair collector 94 and a noun pair polarity determiner 98 for collecting noun pairs co-occurring with predicate template pairs and determining polarity of relation between nouns, using conjunctions and seed templates; a template pair collector 100, collecting template pairs co-occurring with noun pairs and determining, based on the relation of noun pairs co-occurring with the predicate template pairs and the conjunctions between predicate templates pairs, whether the polarity of excitatory class of predicate template pair is the same or not; a template network builder 106 building a template network connecting predicate templates based on the predicate template pairs and match/mismatch of excitatory class thereof; and a template excitation value calculator 112 calculating excitation value to be assigned to each node, using the excitation value of seed templates and the relation between each of the nodes in the network.

摘要翻译： 允许对谓词模板进行有效和自动识别的谓词模板收集器适于包括：名词对收集器94和名词对极性确定器98，用于收集与谓词模板对共存的名词对，并使用连词确定名词之间的关系的极性 和种子模板; 模板对收集器100，收集与名词对共同存在的模板对，并且基于与谓词模板对共同出现的名词对与谓词模板对之间的连接的关系确定谓词模板的兴奋类的极性 对是一样的 模板网络构建器106构建基于谓词模板对连接谓词模板的模板网络，并且其兴奋类别的匹配/不匹配; 以及模板激励值计算器112，使用种子模板的激励值和网络中的每个节点之间的关系来计算要分配给每个节点的激励值。

公开(公告)号：US12099801B2

公开(公告)日：2024-09-24

申请号：US17622798

申请日：2020-07-06

申请人： National Institute of Information and Communications Technology

发明人： Jonghoon Oh ,  Kazuma Kadowaki ,  Julien Kloetzer ,  Ryu Iida ,  Kentaro Torisawa

IPC分类号： G06F40/20 ,  G06F16/2455 ,  G06F16/35 ,  G06F40/30

CPC分类号： G06F40/20 ,  G06F16/35 ,  G06F40/30

摘要： A program for training a representation generator generating a representation representing an answer part included in a passage to classify whether the passage is related to an answer or not. The program causes a computer to operate as: a fake representation generator responsive to a question and a passage for outputting a fake representation representing an answer part of the passage; a real representation generator for outputting, for the question and a core answer, a real representation representing the core answer, in the same format as fake representation; a discriminator for discriminating whether fake representation and real representation are a real or fake representation; and a generative adversarial network unit training the discriminator and fake representation generator through generative adversarial network such that error determination of fake representation is maximized and error determination of real representation is minimized.

公开(公告)号：US11256658B2

公开(公告)日：2022-02-22

申请号：US16336676

申请日：2017-09-28

申请人： National Institute of Information and Communications Technology

发明人： Canasai Kruengkrai ,  Chikara Hashimoto ,  Kentaro Torisawa ,  Julien Kloetzer ,  Jonghoon Oh ,  Masahiro Tanaka

IPC分类号： G06F16/95 ,  G06F16/2457 ,  G06F16/00 ,  G06F40/20 ,  G06F16/33 ,  G06F40/289 ,  G06F40/30 ,  G06N3/04 ,  G06N5/00 ,  G06N5/02

摘要： A causality recognizing apparatus includes a candidate vector generating unit configured to receive a causality candidate for generating a candidate vector representing a word sequence forming the candidate; a context vector generating unit generating a context vector representing a context in which noun-phrases of cause and effect parts of the causality candidate appear; a binary pattern vector generating unit, an answer vector generating unit and a related passage vector generating unit, generating a word vector representing background knowledge for determining whether or not there is causality between the noun-phrase included in the cause part and the noun-phrase included in the effect part; and a multicolumn convolutional neural network learned in advance to receive these word vectors and to determine whether or not the causality candidate has causality.

公开(公告)号：US20150026106A1

公开(公告)日：2015-01-22

申请号：US14377999

申请日：2013-01-23

申请人： National Institute of Information and Communications Technology

发明人： Jonghoon Oh ,  Kentaro Torisawa ,  Chikara Hashimoto ,  Takuya Kawada ,  Stijn De Saeger ,  Junichi Kazama ,  Yiou Wang

IPC分类号： G06N99/00 ,  G06F17/30 ,  G06N7/00 ,  G06F17/27

CPC分类号： G06N99/005 ,  G06F17/2705 ,  G06F17/30598 ,  G06F17/30654 ,  G06F17/3069 ,  G06N7/00

摘要： In order to provide a non-factoid question answering system with improved precision, the question answering system (160) includes: a candidate retrieving unit (222), responsive to a question, extracting answer candidates from a corpus storage (178); a feature vector generating unit (232) for generating features from combinations of a question with each of the answer candidates; SVMs (176) trained to calculate a score of how correct a combination of the question with an answer candidate is, upon receiving the feature vector therefor; and an answer ranker unit (234) outputting the answer candidate with the highest calculated score as the answer. The features are generated on the basis of the results of morphological analysis and parsing of the question, a phrase in the question evaluated as being positive or negative as well as its polarity, and the semantic classes of nouns in the features.

摘要翻译： 为了提供更精确的非事实型问答系统，问答系统（160）包括：候选者检索单元（222），响应于问题，从语料库存储（178）提取答案候选者; 特征向量生成单元，用于从问题的组合中产生每个候选答案的特征; 在接收到该特征向量时，经训练的SVM（176）被训练以计算问题组合与答案候选者的正确度的得分; 以及将具有最高计算得分的答案候选作为答案输出的回答保持单元（234）。 这些特征是基于形态学分析和问题解析的结果生成的，被评价为正或负的一个短语以及其极性，以及特征中名词的语义类别。

公开(公告)号：US11106714B2

公开(公告)日：2021-08-31

申请号：US16610916

申请日：2018-05-07

申请人： National Institute of Information and Communications Technology

发明人： Ryu Iida ,  Kentaro Torisawa ,  Jonghoon Oh ,  Canasai Kruengkrai ,  Yoshihiko Asao ,  Noriyuki Abe ,  Junta Mizuno ,  Julien Kloetzer

IPC分类号： G06F16/34 ,  G06F40/30 ,  G06F40/268 ,  G06N3/08 ,  G06F40/20

摘要： A summary generating apparatus includes a text storage device storing text with information indicating a portion to be focused on; word vector converters vectorizing each word of the text and adding an element indicating whether the word is focused on or not to the vector and thereby converting the text to a word vector sequence; an LSTM implemented by a neural network performing sequence-to-sequence type conversion, pre-trained by machine learning to output, in response to each of the word vectors of the word vector sequence input in a prescribed order, a summary of the text consisting of the words represented by the word sequence; and input units inputting each of the word vectors of the word vector sequence in the prescribed order to the neural network.

公开(公告)号：US10157171B2

公开(公告)日：2018-12-18

申请号：US15544227

申请日：2016-01-20

申请人： National Institute of Information and Communications Technology

发明人： Ryu Iida ,  Kentaro Torisawa ,  Chikara Hashimoto ,  Jonghoon Oh ,  Kiyonori Ootake ,  Yutaka Kidawara

IPC分类号： G06F17/22 ,  G06F17/24 ,  G06F17/27 ,  G06F17/28 ,  G06F3/0482

摘要： An annotation data generation assisting system includes: an input/output device receiving an input through an interactive process; morphological analysis system 380 and dependency parsing system performing morphological and dependency parsing on text data in text archive; first to fourth candidate generating units detecting a zero anaphor or a referring expression in the dependency relation of a predicate in a sequence of morphemes, identifying a position as an object of annotation and estimating candidates of expressions to be inserted by using language knowledge; a candidate DB storing estimated candidates; and an interactive annotation device reading candidates of annotation from candidate DB and annotate a candidate selected by an interactive process by input/output device.