National Institute of Information and Communications Technology, Incorporated

Central Glass Company, Limited

Mitsui Toatsu Chemicals, Incorporated

Rakuten Group, Inc.

Nippon Oil Company

Yahoo Japan Corporation

Chikara Hashimoto

Kentaro Torisawa

Jonghoon Oh

Motoki Sano

Yutaka Kidawara

Stijn De Saeger

Kiyonori Ootake

Yulan Yan

Hiroshi Itoh

Takashi Abe

Junichi Kazama

Hitoshi Yamashita

Kunio Nakata

Takeshi Hisanaga

Takao Takebayashi

Toshihiro Yoshimura

Hiroyuki Itoh

Takehiro Toyooka

Masahiro Tanaka

Hiroshi Inaba

Motoh Asakura

Atsushi Takamatsu

Takao Kawai

Shinji Nishikawa

Kiyoshi Nakase

Ryu Iida

Yukitoshi Yanagida

Julien Kloetzer

Canasai Kruengkrai

Takuya Kawada

Manabu Sassano

Junta Mizuno

Yiou Wang

Kazuaki Inada

Istvan Varga

A processing execution system, comprising at least one processor configured to: acquire second classification information relating to a classification of second data based on a first model which has learned a relationship between first data and first classification information relating to a classification of the first data; estimate, based on a predetermined estimation method, a validity relating to a combination of the second data and the second classification information; and execute predetermined processing based on an estimation result for the validity.

Processing execution system, processing execution method, and program

Provided is a ranking determination system including at least one processor configured to: acquire a plurality of second classifications relating to second data based on a first model which has learned a relationship between first data and a first classification relating to the first data; acquire, for each of the second classifications, a second score relating to a validity of a combination of the second data and the second classification based on a second model which has learned a validity of a combination of third data and a third classification relating to the third data; and determine a second ranking for each of the plurality of second classifications based on the second score of each second classification.

Ranking determination system, ranking determination method, and information storage medium

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.

Causality recognizing apparatus and computer program therefor

An information processing device according to the present application includes an extraction unit and a subsequent stage generation unit. The extraction unit extracts a last conversation of a feedback utterance estimated to indicate a predetermined reaction of a second utterance subject relative to an utterance made by a first utterance subject, from a set of a plurality of conversations, based on a score assigned to the feedback utterance. The subsequent stage generation unit generates a subsequent stage classifier for deriving an index indicating a category of an unknown conversation, based on the last conversation extracted by the extraction unit.

Information processing device, information processing method, and non-transitory computer readable storage medium

A scenario passage pair recognizer includes: a text passage searching unit searching a set of text passages each including no more than a certain number of sentences of a document, and within which all noun phrases included in a scenario candidate co-occur; a feature extracting unit extracting a feature from each combination of the scenario candidate and each searched support passage; a classifier outputting a score indicating reliability of the scenario candidate based on the support passage as a source of the feature; and a score accumulating unit and a maximum value selecting unit, accumulating the scores output from the classifier and selecting the maximum value as the reliability of the scenario candidate. The scenario classifier determines plausibility of the scenario candidate as a causality based on the feature including the score output from the scenario passage pair recognizer.

Scenario passage pair recognizer, scenario classifier, and computer program therefor

[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 deviceanalyzes dependency of collected texts by a morpheme analyzing unitand a dependency analyzing unit. A problem report collecting unitspecifies 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 deviceand request message collecting devicecollect support information and request messages in the similar manner. A matching devicematches problem reports and support information collected by problem report collecting unitand support information collecting deviceby a method referred to as co-occurrence core matrix, and thus associates problem information (support information) with appropriate support information (problem information).

Text matching device and method, and text classification device and method

A credibility determining system enabling highly accurate credibility determination of given information includes causal relation knowledge DBand search scope constraint DB. Causal relation knowledge each includes a combination of cause and result parts, and time and position constraints associated with the causal relation. The credibility determining system further includes a query generating unitretrieving a causal relation matching the input information and based on the time and position constraints stored in search scope constraint DBin association with the retrieved causal relation, generating a query for retrieving remarks from mini-blog text DB, a text search unitsearching for related remarks from mini-blog text DBusing the query, and a display candidate selecting unitclassifying the searched remarks to expressions interpreted as causes or to results, determining credibility of the input information based on the classification result and outputting the determination result.

System and method for determining credibility of information based on many remarks on a network, and non-transitory computer readable storage medium having stored thereon computer program therefor

A question-answering system capable of appropriately answering a non-factoid question. The question-answering system responsive to a question, for taking out answer candidates from an object document storage unit; extracting plausible ones from the answer candidates; recognizing causal relation expression included in extracted answer candidates; determining whether or not a recognized causal relation is relevant as an answer; generating a feature vector related to a combination of the question and the searched answer candidate; and for calculating, when a feature vector is given, a score indicating a degree of how correct an answer candidate is as an answer to the question, for the question and the answer candidate as a source of the feature vector, and for outputting, as the answer to the question, an answer candidate having the highest score.

Non-factoid question-answering system and method

[Object] An object of the present invention is to provide a system for collecting elements as a basis for generating a social scenario useful for people to make well-balanced good decision. [Solution] A scenario generating apparatus includes: a causality phrase pair DBstoring causality phrase pairs; synonimity generatorsand, searching, for each of the causality phrase pairs, causality phrase pairs having a cause phrase with causal consistency with the result phrase of the causality phrase pair, and generating join information for joining causality phrase pairs; join relation DBstoring the join information; and a causality joining unitjoining, to a result phrase of a causality phrase pair, a causality phrase pair having a cause phrase with causal consistency with the phrase by using the join information, and thereby linking causality. A join relation generatorthat finds a hidden relation between phrases and linking causality phrase pairs may be provided.

Scenario generating apparatus and computer program therefor

A system for collecting elements as a basis for generating a social scenario useful to make a well-balanced good decision. A complex predicate template collecting apparatus includes: a simple predicate template DB storing simple predicate templates having positive or negative polarity values added; an object noun dictionary; a complex predicate template candidate extractor extracting complex predicate template candidates each formed of a combination of a word specified by the object noun dictionary and a simple predicate template, from a WEB archive; a sahen-noun polarity adder, a quantifier noun polarity adder and a trouble-noun polarity adder, determining polarity of a noun in each of the complex predicate template candidate; and a complex predicate template polarity calculator calculating polarity of a complex predicate template candidate by a combination of the polarity of the noun and the polarity of the simple predicate template included in the complex predicate template.

Complex predicate template collecting apparatus and computer program therefor

An annotation data generation assisting system includes: an input/output device receiving an input through an interactive process; morphological analysis systemand 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.

Annotation assisting apparatus and computer program therefor

[Object] An object of the present invention is to provide a system for collecting elements as a basis for generating a social scenario useful to make well-balanced good decision. [Solution] A phrase pair collecting apparatus includes: a causality seed pair DBstoring seed pairs each consisting of a pair of phrases including a combination of a noun and a predicate template; a semantic relation pattern DBstoring semantic relation patterns between words; a word pair DBstoring word pairs related to any of the semantic relation patterns; a semantic relation pattern matching unitfor determining which of the semantic relation pattern matches a noun pair in each seed pair stored in causality seed pair DB; and a word pair replacing unitfor replacing the noun pair of a seed pair using, of the word pairs stored in the word pair DB, each of those word pairs which are related to the semantic relation pattern determined to be matching the noun pair, and thereby generating new hypotheses.

Phrase pair collecting apparatus and computer program therefor

In order to provide a non-factoid question answering system with improved precision, the question answering system () includes: a candidate retrieving unit (), responsive to a question, extracting answer candidates from a corpus storage (); a feature vector generating unit () for generating features from combinations of a question with each of the answer candidates; SVMs () 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 () 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.

Non-factoid question-answering system and computer program

A predicate template collector allowing efficient and automatic recognition of predicate templates is adapted to include: a noun pair collectorand a noun pair polarity determinerfor 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, 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 builderbuilding a template network connecting predicate templates based on the predicate template pairs and match/mismatch of excitatory class thereof; and a template excitation value calculatorcalculating 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.

Predicate template collecting device, specific phrase pair collecting device and computer program therefor

A water sensor, such as a rain or dew sensor, includes a light emitting device for producing sensing light to be reflected in a transparent plate such as a windshield glass panel of a vehicle, a light receiving device for receiving the sensing light, and a hologram sheet having at least one hologram for defining a light path of the sensing light between the light emitting device and the light receiving device. The hologram sheet may be attached to the inside surface of a windshield glass panel or interposed between inside and outside glass layers of a laminated glass panel.

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Tokyo, Japan

Chikara Hashimoto