Abstract: An information processing device includes: an acquisition unit configured to acquire document data; an analysis processing unit configured to perform morphological analysis of the document data; a feature determining unit configured to determine a feature corresponding to the document data based on a result of the morphological analysis and a hash function; an export unit configured to output export data that is data based on the feature to a second information processing device; an import unit configured to acquire a result of processing performed by the second information processing device based on the export data; and a processing unit configured to perform processing based on the result of the processing acquired by the import unit.

Abstract: An information processing device including: an obtaining unit configured to obtain document data; an analysis processing unit configured to perform morphological analysis of the document data; a feature determining unit configured to determine a feature in accordance with a result of the morphological analysis; and a learning processing unit configured to perform machine learning to determine a weight of a morpheme in a model in accordance with the feature, the morpheme being obtained by the morphological analysis, and the model being either a linear model or a generalized linear model, wherein the learning processing unit performs processing of deleting, from input data of the model, the feature corresponding to the morpheme having the weight a value of which is determined to be smaller than, or equal to, a given threshold value.

Abstract: An information processing device includes: a model obtaining unit configured to obtain a learned model generated by machine learning that includes: determining a weight of a morpheme in a model, in accordance with a feature determined using a result of morphological analysis; and deleting, from input data of the model, the feature corresponding to the morpheme having the weight determined to be smaller than, or equal to, a threshold value; an obtaining unit configured to obtain document data ; a feature determining unit configured to determine the feature to be input to the learned model, in accordance with the result of the morphological analysis; an inference processing unit configured to input the feature to the learned model, to calculate a score indicating a degree of relevance between the document data and an event; and a display control unit configured to perform display control using the score.

Abstract: An improved antislip strip or band is disclosed which can maintain shirt or blouse in place with respect to slacks, pants, trousers or skirt while being worn. The strip includes a body portion formed of an elastic, antislip fabric comprising two different warp threads of polyurethane double covered yarn and polyurethane bare yarn interlaced with weft threads in the form of leno weave, and two opposed edge portions in the form of plain weave. The weaving is done in the antislip fabric to provide a roughened or irregular surface having a plurality of spaced-apart nubs formed on both sides of each gap between two adjacent weft threads. The antislip strip may be sewn into the waist portion of a garment with the roughened or irregular surface facing inside.