INFORMATION OUTPUT APPARATUS, QUESTION GENERATION APPARATUS, AND NON-TRANSITORY COMPUTER READABLE MEDIUM
An information output apparatus includes: a processor configured to: calculate a difference between (i) a semantic representation of a specific user known word obtained from a first model that has learned semantic representations of words using a specific set of example sentences and (ii) a semantic representation of the specific user known word obtained from a second model that has learned semantic representations of words using a part of the specific set of example sentences excluding a target word; and output information on a possibility that the target word is a user known word based on the difference.
1 . An information output apparatus comprising:
a processor configured to:
calculate a difference between (i) a semantic representation of a specific user known word obtained from a first model that has learned semantic representations of words using a specific set of example sentences and (ii) a semantic representation of the specific user known word obtained from a second model that has learned semantic representations of words using a part of the specific set of example sentences excluding a target word; and
output information on a possibility that the target word is a user known word based on the difference.
2 . The information output apparatus according to claim 1 , wherein
the processor is configured to:
calculate a plurality of differences by calculating the difference for each of a plurality of the target words; and
output the plurality of target words arranged in order based on the differences for the respective target words, as information on the possibilities that the target words are the user known words.
3 . The information output apparatus according to claim 2 , wherein the order based on the differences is descending order of the difference.
4 . The information output apparatus according to claim 1 , wherein
the second model is a model obtained by causing an unlearned model to newly learn semantic representations of words using the part of the specific set of example sentences excluding the target word.
5 . The information output apparatus according to claim 4 , wherein
the part of the specific set of example sentences excluding the target word is a part of an element, which includes at least one of the specific user known word or the target word, of the specific set of example sentences excluding the target word.
6 . The information output apparatus according to claim 1 , wherein
the second model is a model obtained by causing a learned model to further learn semantic representations of words using the part of the specific set of example sentences excluding the target word.
7 . The information output apparatus according to claim 6 , wherein
the part of the specific set of example sentences excluding the target word is a part of an element, which includes the target word, of the specific set of example sentences excluding the target word.
8 . A question generation apparatus comprising:
a processor configured to:
calculate a plurality of differences by calculating, for each of a plurality of target words, a difference between (i) a semantic representation of a specific user known word obtained from a first model that has learned semantic representations of words using a specific set of example sentences and (ii) a semantic representation of the specific user known word obtained from a second model that has learned semantic representations of words using a part of the specific set of example sentences excluding the target word; and
generate a question using the plurality of target words based on the plurality of differences.
9 . The question generation apparatus according to claim 8 , wherein
the processor is configured to:
calculate the plurality of differences using another user known word recognized from an answer of a user to the question in place of the specific user known word; and
regenerate a question using the plurality of target words based on the plurality of differences.
10 . A non-transitory computer readable medium storing a program that causes a computer to execute an information output process, the information output process comprising:
calculating a difference between (i) a semantic representation of a specific user known word obtained from a first model that has learned semantic representations of words using a specific set of example sentences and (ii) a semantic representation of the specific user known word obtained from a second model that has learned semantic representations of words using a part of the specific set of example sentences excluding a target word; and
outputting information on a possibility that the target word is a user known word based on the difference.