US 11,537,790 B2Granted

Word vector changing device, method, and program

AssigneeNippon Telegraph and Telephone Corporation

InventorsKatsuji Bessho, Hisako Asano, Junji Tomita

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Abstract

To arrange all words so that the distance of a given word pair will be appropriate. Using as input a concept base 22 which is a set of pairs of a word and a vector representing a concept of the word, and a dictionary 24 which is a set of semantically distant or close word pairs, when a word pair C being a pair of given words A, B in the concept base 22 is present in the dictionary 24, conversion means 30 associates with the word pair C a magnitude D of a difference vector between a difference vector V′ between a converted vector of the word A and a converted vector of the word B, and a vector kV determined by multiplying a difference vector V between the vector of the word A in the concept base 22 and the vector of the word B in the concept base 22 by a scalar value k. When the word pair C is not present in the dictionary 24, the conversion means 30 associates the magnitude D of the difference vector between the difference vector V′ and the difference vector V with the word pair C. The conversion means 30 converts the vector of a given word in the concept base 22 such that a total sum of the magnitude D corresponding to every word pair C is minimized.

Claims20

Dependent claims

A computer-implemented method for processing aspects of words, the method comprising:

receiving, from a concept base, a first concept of a first word, wherein the first concept includes a first pair of the first word and a first vector representation of the first word;
receiving, from the concept base, a second concept of a second word, wherein the second concept includes a second pair of the second word and the second vector representation of the second word, wherein the second word and the first word are distinct;
receiving, from a dictionary of words, a pair of words, wherein the pair of words represents a relationship between one word and the other word based on a semantic distance, wherein the semantic distance relates to a semantic relationship based on one of:
synonyms, antonyms, or co-hyponyms;
generating a first difference vector, wherein the first difference vector is a difference between the first vector representation of the first concept of the first word and the second vector representation of the second concept of the second word;
when the pair of words matches the first word and the second word:
determining, based on the pair of words, a coefficient value;
and
generating, based on a difference between the first vector representation and the second vector representation, a second difference vector, wherein a product of the second difference vector and the coefficient value differs from the first difference vector by a difference value;
when the pair of words does not match the first word or the second word:
generating, based on the difference between the first vector representation and the second vector representation, the second difference vector, wherein the second difference vector differs from the first difference vector by the difference value;
converting, the first vector representation and the second vector representation, wherein the conversion relates to minimizing a total sum of the difference value corresponding to each occurrence of the pair of words in the dictionary;
and
updating, based on the converted first vector representation and the second vector representation, the first concept and the second concept in the concept base.

11 more elements

A system for processing aspects of words, the system comprises:

a processor;
and
a memory storing computer-executable instructions that when executed by the processor cause the system to:
receive, from a concept base, a first concept of a first word, wherein the first concept includes a first pair of the first word and a first vector representation of the first word;
receive, from the concept base, a second concept of a second word, wherein the second concept includes a second pair of the second word and the second vector representation of the second word, wherein the second word and the first word are distinct;
receive, from a dictionary of words, a pair of words, wherein the pair of words represents a relationship between one word and the other word based on a semantic distance, wherein the semantic distance relates to a semantic relationship based on one of:
synonyms, antonyms, or co-hyponyms;
generate a first difference vector, wherein the first difference vector is a difference between the first vector representation of the first concept of the first word and the second vector representation of the second concept of the second word;
when the pair of words matches the first word and the second word:
determine, based on the pair of words, a coefficient value;
and
determine, based on a difference between the first vector representation and the second vector representation, a second difference vector, wherein a product of the second difference vector and the coefficient value differs from the first difference vector by a difference value;
when the pair of words does not match the first word or the second word:
determine, based on the difference between the first vector representation and the second vector representation, the second difference vector, wherein the second difference vector differs from the first difference vector by the difference value;
convert, the first vector representation and the second vector representation, wherein the conversion relates to minimizing a total sum of the difference value corresponding to each occurrence of the pair of words in the dictionary;
and
update, based on the converted first vector representation and the second vector representation, the first concept and the second concept in the concept base.

14 more elements

A computer-readable non-transitory recording medium storing computer-executable instructions that when executed by a processor cause a computer system to:

receive, from a concept base, a first concept of a first word, wherein the first concept includes a first pair of the first word and a first vector representation of the first word;
receive, from the concept base, a second concept of a second word, wherein the second concept includes a second pair of the second word and the second vector representation of the second word, wherein the second word and the first word are distinct;
receive, from a dictionary of words, a pair of words, wherein the pair of words represents a relationship between one word and the other word based on a semantic distance, wherein the semantic distance relates to a semantic relationship based on one of:
synonyms, antonyms, or co-hyponyms;
generate a first difference vector, wherein the first difference vector is a difference between the first vector representation of the first concept of the first word and the second vector representation of the second concept of the second word;
when the pair of words matches the first word and the second word:
determine, based on the pair of words, a coefficient value;
and
determine, based on a difference between the first vector representation and the second vector representation, a second difference vector, wherein a product of the second difference vector and the coefficient value differs from the first difference vector by a difference value;
when the pair of words does not match the first word or the second word:
determine, based on the difference between the first vector representation and the second vector representation, the second difference vector, wherein the second difference vector differs from the first difference vector by the difference value;
convert, the first vector representation and the second vector representation, wherein the conversion relates to minimizing a total sum of the difference value corresponding to each occurrence of the pair of words in the dictionary;
and
update, based on the converted first vector representation and the second vector representation, the first concept and the second concept in the concept base.

11 more elements

Dependencies are inferred from the claim text.