Abstract: A machine learning method includes: obtaining first teacher data, which includes first encrypted words and corresponding search word information including one or more second encrypted words to be used for search, the first encrypted words being generated such that the first encrypted word includes a code sequence different from other encrypted words even though both of the first encrypted words and the other encrypted words have been generated from a same word; obtaining a group of words from among the first encrypted words by using a trapdoor scheme; generating second teacher data by using one encrypted word included in the obtained group to replace a rest of the obtained group of words; and performing, on the basis of the second teacher data, machine learning of a parameter to determine, in response to receiving of one or more encrypted words, one or more encrypted words to be used for search.

Abstract: When retrieving specific text from a search target document, an information processing apparatus receives text, generates a semantic structure indicating a meaning of a word that is included in the received text, by subjecting the received text to semantic analysis, identifies a word that is associated with the generated semantic structure, by referring to a synonym dictionary that stores a word and semantic structure indicating a meaning of the word in an associated manner, determines whether the identified word is included in the search target document, and outputs information according to a determination result.

Abstract: A determination method executed by a computer including a memory and a processor coupled to the memory, includes receiving a plurality of sentences and designation of terms included in the plurality of sentences, generating, for each term for which the designation is received, information indicating a relation between the term and each of other terms included in one of the plurality of sentences containing the term, extracting, for each term for which the designation is received, information indicating a specific relation from the generated information indicating the relation, generating characteristic information that uses the extracted information as a feature, and determining similarity between a plurality of the terms based on the generated characteristic information for each term.

Abstract: A determination method executed by a computer including a memory and a processor coupled to the memory, includes receiving a plurality of sentences and designation of terms included in the plurality of sentences, generating, for each term for which the designation is received, information indicating a relation between the term and each of other terms included in one of the plurality of sentences containing the term, extracting, for each term for which the designation is received, information indicating a specific relation from the generated information indicating the relation, generating characteristic information that uses the extracted information as a feature, and determining similarity between a plurality of the terms based on the generated characteristic information for each term.

Abstract: A machine learning method includes obtaining a first plurality of pieces of teacher data including encrypted words associated with first information indicating words received for search and encrypted words associated with second information indicating words used for search, generating a second plurality of pieces of teacher data in which a first encrypted word is replaced with a second encrypted word on the basis of the first plurality of pieces of teacher data, a plain text of the first encrypted word being equal to a plain text of the second encrypted word, and performing, on the basis of the second plurality of pieces of teacher data, machine learning of a parameter with which an encrypted word associated with the second information is determined in response to receiving an encrypted word associated with the first information.

Abstract: When retrieving specific text from a search target document, an information processing apparatus receives text, generates a semantic structure indicating a meaning of a word that is included in the received text, by subjecting the received text to semantic analysis, identifies a word that is associated with the generated semantic structure, by referring to a synonym dictionary that stores a word and semantic structure indicating a meaning of the word in an associated manner, determines whether the identified word is included in the search target document, and outputs information according to a determination result.

Abstract: An information processing device receives sentence data. The information processing device generates sets of information, each of the sets indicating a relationship between each of words included in the received sentence data and another word among the words by executing a semantic analysis process on the words. The information processing device determines a similarity between the words based on a similarity between the generated the sets of information. The information processing device outputs a result of the determining.

Abstract: A non-transitory computer-readable recording medium stores an operation process creation program that causes a computer to execute a process, the process including extracting a candidate operation manipulation component to be combined with an operation process following an operation manipulation component that has been determined to be arranged, when creating the operation process by arranging a plurality of the operation manipulation components on a screen, the candidate being extracted based on previously set relevance information indicating relevance between operation manipulation components and usage frequency information indicating usage frequencies of operation manipulation components in past instances of creating the operation processes; and displaying the extracted candidate operation manipulation component on the screen, by combining the extracted candidate operation manipulation component with the operation manipulation component that has been determined to be arranged.

Abstract: The present processing apparatus includes an extraction unit and a control unit. The extraction unit extracts a job group including an extraction job and a subsequent job from a plurality of scheduled jobs, the plurality of scheduled jobs being included in a second operation, the second operation being scheduled in a second period which is after a first period in which a first operation is scheduled, the extraction job extracting a data group and being included in the plurality of scheduled jobs, and the subsequent job processing on the data group within a range of the data group. The control unit executes jobs in the extracted job group in the first period. Accordingly, the second operation can be completed by the start of the first operation.

Abstract: A non-transitory computer-readable recording medium stores an operation process creation program that causes a computer to execute a process, the process including extracting a candidate operation manipulation component to be combined with an operation process following an operation manipulation component that has been determined to be arranged, when creating the operation process by arranging a plurality of the operation manipulation components on a screen, the candidate being extracted based on previously set relevance information indicating relevance between operation manipulation components and usage frequency information indicating usage frequencies of operation manipulation components in past instances of creating the operation processes; and displaying the extracted candidate operation manipulation component on the screen, by combining the extracted candidate operation manipulation component with the operation manipulation component that has been determined to be arranged.