Tag assignment model generation apparatus, tag assignment apparatus, methods and programs therefor using probability of a plurality of consecutive tags in predetermined order

A tagging model generation method comprising:

• a learning step of causing a learning section to generate a tagging model by using inputted learning data,
• the learning data being a plurality of pieces of text-related information corresponding to a plurality of pieces of text,
• each of the plurality of pieces of text-related information serving as information related to the text,
• each of the plurality of pieces of text-related information having word-related information,
• the word-related information serving as information related to each word included in the text and including at least part-of-speech information,
• each of the plurality of pieces of text-related information having a tag which is associated with the word-related information of each word and in which a phrase marked as including related words is taken into consideration,
• the tagging model including probability-related information and joint probability-related information,
• the probability-related information serving as information related to a probability that each tag is associated with each word-related information,
• the joint probability-related information serving as information related to a joint probability,
• the joint probability serving as a probability of appearance of a plurality of consecutive tags in a predetermined order, the plurality of consecutive tags being associated with pieces of word-related information of a plurality of consecutive words in each text;
• and
• a storage step of causing a storage section to store the generated tagging model.