Word grouping using a plurality of models

An apparatus comprising:

• a processor or a programmable circuitry;
• and
• one or more computer readable mediums collectively including instructions that, in response to being executed by the processor or the programmable circuitry, cause the processor or the programmable circuitry to:
• acquire a seed word;
• calculate a similarity score of each of a plurality of words relative to the seed word for each of a plurality of models to calculate a weighted sum of the similarity scores for each of the plurality of words;
• output a plurality of candidate words among the plurality of words;
• acquire annotations indicating one or more preferred words among the plurality of candidate words;
• update weights of the plurality of models in a manner to cause weighted sums of similarity scores for the preferred words to be relatively larger than weighted sums of the similarity scores for non-annotated words, the non-annotated words being non-preferred words;
• and
• group the plurality of candidate words output based on the weighted sum of similarity scores calculated with updated weights of the plurality of models.

A computer program product including one or more computer readable storage mediums collectively storing program instructions that are executable by a processor or programmable circuitry to cause the processor or the programmable circuitry to perform operations comprising:

• acquiring a seed word;
• calculating a similarity core of each of a plurality of words relative to the seed word for each of a plurality of models to calculate a weighted sum of the similarity scores for each of the plurality of words;
• outputting a plurality of candidate words among the plurality of words;
• acquiring annotations indicating one or more preferred words among the plurality of candidate words;
• updating weights of the plurality of models in a manner to cause weighted sums of similarity scores for the preferred to be relatively larger than weighted sums of similarity scores for non-annotated words, the non-annotated words being non-preferred words;
• and
• grouping the plurality of candidate words output based on the weighted of similarity scores calculated with updated weights of the plurality of models.