Abstract: A non-transitory computer-readable recording medium storing a prediction program that uses knowledge graph embedding, for causing a computer to execute processing including: determining whether or not graph data to be predicted is data that includes a node link that indicates a relationship between nodes not included in training data used for training of the knowledge graph embedding; specifying, in a case where it is determined that the graph data to be predicted is the data that includes the node link not included in the training data, graph data similar to the graph data to be predicted from the training data based on a result of embedding prediction for a label of a node included in the graph data to be predicted; and determining a prediction result for the graph data to be predicted based on the specified similar graph data.

Abstract: A storage medium storing a machine learning program that causes at least one computer to execute a process, the process includes acquiring information regarding a first triple that includes a first node, a second node, and a first edge that indicates a relationship between the first node and the second node; and updating a vector of a third node of a plurality of vectors and a vector of a third edge of the plurality of vectors, based on the information and the plurality of vectors, each of the plurality of vectors representing each of a plurality of nodes and each of a plurality of edges that indicate relationships between the plurality of nodes, the plurality of vectors being generated by machine learning that uses the plurality of nodes and the plurality of edges, the third node and the third edge being coupled to the first triple under a certain condition.

Abstract: A non-transitory computer-readable storage medium storing an estimation program that causes at least one computer to execute a process, the process includes inputting training data that includes a vector of graph data, a vector of ontology, and a label; training a machine learning model based on a loss function acquired by the label and a value obtained by merging a value of an activation function acquired with the vector of the graph data and a value of the activation function acquired with the vector of the ontology.

Abstract: A training apparatus obtains RDF data including subjects, predicates, and objects, inputs a subject, a predicate, and an object of a first record of the obtained RDF data, and determines a predicate of a second record that has been previously input, the predicate having the same character string as the subject or object of the first record. The training apparatus generates training data including RDF data having the subject or object of the first record and the predicate of the second record that have been associated with each other. The training apparatus performs training for the generated training data so that a vector resulting from addition of a vector of the predicate to a vector of the subject associated with the RDF data becomes closer to a vector of the object associated with the RDF data, and thereby enables improvement in prediction accuracy for searching through the RDF data.

Abstract: A non-transitory computer-readable storage medium stores a program that causes a computer to execute a process. The process includes obtaining data including multiple character strings that are separated from each other, identifying a first character string and second character strings in the obtained data, extracting third character strings indicating relationships between the first character string and the second character strings from character string collections stored in a database, selecting a character string collection from the character string collections based on proportions of the extracted third character strings included in the respective character string collections, and outputting information on the selected character string collection. Each of the character string collections includes character string sets each of which includes two character strings and a third character string indicating a relationship between the two character strings.

Abstract: An information processing apparatus includes a memory and a processor. The processor is configured to receive an input physical quantity, a value of the input physical quantity, and an output physical quantity. The processor is configured to generate a first array of first conversion operations or a second array of second conversion operations by using conversion rules each for converting a value of a source physical quantity into a value of a target physical quantity. Each conversion operation is a conversion according to a conversion rule or a reverse operation thereof. The first array enables a conversion of the input physical quantity into the output physical quantity. The second array enables the reverse. The processor is configured to convert the received value of the input physical quantity into a value of the output physical quantity by using the first array or the second array.

Abstract: A new and distinct variety of ligustrum plant having a small leaf size and dwarf growth habit.

Abstract: An information processing apparatus includes a memory and a processor. The processor is configured to receive an input physical quantity, a value of the input physical quantity, and an output physical quantity. The processor is configured to generate a first array of first conversion operations or a second array of second conversion operations by using conversion rules each for converting a value of a source physical quantity into a value of a target physical quantity. Each conversion operation is a conversion according to a conversion rule or a reverse operation thereof. The first array enables a conversion of the input physical quantity into the output physical quantity. The second array enables the reverse. The processor is configured to convert the received value of the input physical quantity into a value of the output physical quantity by using the first array or the second array.

Abstract: A non-transitory computer-readable storage medium stores a program that causes a computer to execute a process. The process includes obtaining data including multiple character strings that are separated from each other, identifying a first character string and second character strings in the obtained data, extracting third character strings indicating relationships between the first character string and the second character strings from character string collections stored in a database, selecting a character string collection from the character string collections based on proportions of the extracted third character strings included in the respective character string collections, and outputting information on the selected character string collection. Each of the character string collections includes character string sets each of which includes two character strings and a third character string indicating a relationship between the two character strings.

Abstract: A systematic problem search unit searches information about a systematic problem that is a common problem to a plurality of projects, using a conditional expression for searching the information about the systematic problem based on one of or a plurality of a count by which the information about the systematic problem is stored in the retrospect storage unit, a count by which a trial improvement plan linked to the systematic problem is stored in the retrospect storage unit, and information indicating whether the stored improvement plan is stored in the retrospect storage unit, as a conditional expression indicating a condition for extracting the information about the systematic problem. a systematic problem output unit outputs a search result in the systematic problem search procedure to each of or one of a predetermined storage unit and a predetermined output unit.

Abstract: A category pair is generated in a round-robin fashion for all of categories by obtaining each category of a document directory, each category of a bookmark, and a URL registered to each category from each of a document directory storing unit and a bookmark storing unit, and the degree of similarity is calculated for each category pair. Next, a pair of categories whose degrees of association are high is selected from among all of category pairs, and a URL candidate to be recommended each other is extracted for each selected category pair.

Abstract: In a work-flow process, a work-flow apparatus, and a computer-readable medium storing a work-flow program for delivering work requests to stations in an organization: a station in charge of executing each work request is determined by comparing the work request with work definitions, and the work request is delivered to the station in charge; acceptance or rejection of the work request by the station in charge is recorded in a request-processing history in association with an identifier of the work request; and the number of work requests which have been improperly or indirectly delivered to each station is obtained on the basis of the numbers of work requests which have been rejected by the station. When the number of work requests which have been improperly or indirectly delivered to each station is greater than a predetermined number, the work definition for the station is determined to be corrected.

Abstract: A category pair is generated in a round-robin fashion for all of categories by obtaining each category of a document directory, each category of a bookmark, and a URL registered to each category from each of a document directory storing unit and a bookmark storing unit, and the degree of similarity is calculated for each category pair. Next, a pair of categories whose degrees of association are high is selected from among all of category pairs, and a URL candidate to be recommended each other is extracted for each selected category pair.

Abstract: A new and distinct variety of Ligustrum plant having a small leaf size and dwarf growth habit.