Abstract: A computer-readable recording medium has stored therein a program including instructions for obtaining multiple classification results of classification of a plurality of data pieces outputted from a machine learning model into which the plurality of data pieces have been inputted; specifying in accordance with classification results, a first plurality of attributes among a plurality of attributes included in a first plurality of data pieces classified into a first group and a second plurality of data pieces classified into a second group, each difference between each value of the first plurality of attributes of the first plurality of data pieces and each value of the first plurality of attributes of the second plurality of data pieces satisfying a condition; determining labels of the data pieces based on a first index representing a combination of the first multiple attributes; and training the machine learning model, using the labels and the data pieces.

Abstract: A computer calculates a ratio of a number of sets of data labeled as favorable and a number of sets of data labeled as unfavorable with respect to each of a plurality of types determined by values of a combination of a first attribute and a second attribute that are associated with the sets of data, with respect to each combination of a first type contained in the plurality of types and each of types other than the first type, based on the ratio, specifies candidate data to be changed from among a plurality of sets of data having values corresponding to the first type, based on the candidate data specified with respect to each of the combinations, selects first data from among the plurality of sets of data, and generates training data by changing a label of the first data.

Abstract: A non-transitory computer-readable storage medium storing a training data generation program for causing a computer to perform processing including: receiving an evaluation value for a value calculated on a basis of a number of data for each attribute included in a plurality of data; determining a reference value for each attribute on a basis of the received evaluation value and the number of data for each attribute; and generating training data for machine learning by changing the attribute of at least partial data of the plurality of data according to the reference value for each attribute.

Abstract: An item presentation method implemented by a computer, the item presentation method includes: executing a selection processing that includes selecting a plurality of candidate items that are presentation candidates from a plurality of items, based on a preference of a user; executing a calculation processing that includes calculating the number of new items newly presented among the plurality of candidate items by referring to an item presentation history to the user; executing a decision processing when the number of new items is a predetermined number or less, the decision processing including deciding, as a recommendation item, an item located away from the preference in an item space about the preference by a distance less than a threshold value; and executing a presentation processing that includes selecting a presentation item presented to the user from the plurality of candidate items and the recommendation item, and presenting the selected presentation item.

Abstract: A search device, for each of a plurality of inquiries including a plurality of options, based on a log of answers of a respondent in the past, specifies a matching option corresponding to a trend of answers of the respondent from the plurality of options to be represented to the respondent. The search device, when an answer to the plurality of options is included in the matching option, determines that it is a preference-reached mode that is a mode where the estimating a preference of the user converges. The search device transmits, to the respondent, an inquiry including options, contents of the options included in the inquiry being changed depend on whether it is determined to be a preference-reached mode in the determining.

Abstract: An item presentation method implemented by a computer, the item presentation method includes: executing a selection processing that includes selecting a plurality of candidate items that are presentation candidates from a plurality of items, based on a preference of a user; executing a calculation processing that includes calculating the number of new items newly presented among the plurality of candidate items by referring to an item presentation history to the user; executing a decision processing when the number of new items is a predetermined number or less, the decision processing including deciding, as a recommendation item, an item located away from the preference in an item space about the preference by a distance less than a threshold value; and executing a presentation processing that includes selecting a presentation item presented to the user from the plurality of candidate items and the recommendation item, and presenting the selected presentation item.

Abstract: A search device generates a preference trend based on content of a plurality of answers from a respondent for a plurality of inquiries each including a plurality of options. The search device, based on a log of content of representation items that are represented at the plurality of inquiries to the respondent, determines whether information that changes the representation items is to be represented. The search device generates an input candidate that changes the representation items according to a determining result based on the preference trend and displays the input candidate together with the representation items at the plurality of inquiries.

Abstract: A search device, for each of a plurality of inquiries including a plurality of options, based on a log of answers of a respondent in the past, specifies a matching option corresponding to a trend of answers of the respondent from the plurality of options to be represented to the respondent. The search device, when an answer to the plurality of options is included in the matching option, determines that it is a preference-reached mode that is a mode where the estimating a preference of the user converges. The search device transmits, to the respondent, an inquiry including options, contents of the options included in the inquiry being changed depend on whether it is determined to be a preference-reached mode in the determining.

Abstract: A search apparatus specifies a first respondent group based on a respondent attribute of a respondent. The search apparatus searches for a respondent preference of the respondent utilizing a plurality of inquiries for the respondent, the plurality of inquiries being made with a first preference of the first respondent group as an initial value and corresponding to a first segment that the first respondent group belongs to. The search apparatus, when a specific condition is not satisfied after search from the initial value with a specific number of inquiries, generates or selects a second respondents group based on the respondent attribute, answers to the plurality of inquiries, and on preferences of a second respondent group, the second respondent group satisfying the specific condition. The search apparatus searches for the respondent preference with a preference of the second respondent group being an initial value.