Information processing apparatus, information processing method, and program

An information processing apparatus, comprising:

• a processor serving as:
• a document analyzing unit that extracts phrases including a pair of entities, to which a relevance label is granted, from document data, and
• a label granting unit that grants the relevance label indicating relevance between the pair of entities,
• wherein the label granting unit:
• acquires vocabulary syntax patterns included in the phrases including the pair of entities and acquires the appearing number of times the vocabulary syntax pattern appears in the document data from the document data by analyzing registration information regarding an existing relevance database having registration information regarding the pair of entities and the relevance label and the document data in which at least one phrase including the pair of entities registered in a relevance database is present, for a pair of the vocabulary syntax patterns, counts the number of pairs of entities appearing concurrently with both of each pair of the vocabulary syntax patterns in the document data, and
• sets a probability model created from a probability density distribution, which includes the counted number of pairs of entities, a parameter “Z” indicating validity of the granting of the relevance label, and a parameter “a” indicating a probability of rightly granting the relevance label, calculates the parameters Z and a for which a likelihood is maximum in the probability model, evaluates the validity of the granting of the relevance label for the pair of entities extracted from the document data, and grants the relevance label based on the evaluation result, and
• the label granting unit:
• acquires the vocabulary syntax patterns included in the phrases including the pair of entities by analyzing the registration information regarding the existing relevance database having the registration information regarding the pair of entities and the relevance label and the document data in which at least one phrase including the pair of entities registered in the relevance database is present,
• acquires the number N1 of pairs of entities belonging to a set which has the pairs of entities appearing in the phrases having a vocabulary syntax pattern A, the number N3 of pairs of entities belonging to a set which has the pairs of entities appearing in the phrases having a vocabulary syntax pattern B different from the vocabulary syntax pattern A, and the overlapping number N2 of pairs of entities belonging to a set of an overlapping portion between the set of the pairs of entities appearing in the phrases having the vocabulary syntax pattern A and the set of the pairs of entities appearing in the phrases having the vocabulary syntax pattern B, and then creates an overlapping ratio matrix M having ratio information regarding the three numbers of entities as elements, and
• evaluates the validity of the granting of the relevance label for the pair of entities extracted from the document data using a probability model of using the overlapping ratio matrix M and grants the relevance label based on the evaluation result.

An information processing apparatus, comprising:

• a processor serving as:
• a document analyzing unit that extracts phrases including a pair of entities, to which a relevance label is granted, from document data, and
• a label granting unit that grants the relevance label indicating relevance between the pair of entities,
• wherein the label granting unit:
• acquires vocabulary syntax patterns included in the phrases including the pair of entities and acquires the appearing number of times the vocabulary syntax pattern appears in the document data from the document data by analyzing registration information regarding an existing relevance database having registration information regarding the pair of entities and the relevance label and the document data in which at least one phrase including the pair of entities registered in a relevance database is present,
• for a pair of the vocabulary syntax patterns, counts the number of pairs of entities appearing concurrently with both of each pair of the vocabulary syntax patterns in the document data, and
• sets a probability model created from a probability density distribution, which includes the counted number of pairs of entities, a parameter “Z” indicating validity of the granting of the relevance label, and a parameter “a” indicating a probability of rightly granting the relevance label, calculates the parameters Z and a for which a likelihood is maximum in the probability model, evaluates the validity of the granting of the relevance label for the pair of entities extracted from the document data, and grants the relevance label based on the evaluation result, and
• executes an estimation algorithm of maximum likelihood estimation as a process of estimating the parameters Z and a, the estimation algorithm which (i) initializes the parameters Z and a at random and (ii) alternately repeats updating following parameters until convergence whereby there is no variation in the parameter Z and a variation in the parameter a after a steepest ascending method is equal to or less than 0.001, and which (ii-i) estimates the parameter a by the steepest ascending method after the parameter Z is fixed and (ii-ii), sorts the parameters Z for c at random after fixing the parameter a and sequentially resets a value of each parameter Zc while fixing another parameter Zc so that the likelihood is maximum, and repeats the sorting and resetting until there is no variation in the parameter Z.

An information processing method which is executed in an information processing apparatus, the method comprising:

• extracting phrases including a pair of entities, to which a relevance label is granted, from document data;
• and
• granting the relevance label indicating a kind of relevance between the pair of entities,
• wherein the granting of the relevance label includes
• acquiring vocabulary syntax patterns included in the phrases including the pair of entities and acquiring the appearing number of times the vocabulary syntax pattern appears in the document data from the document data by analyzing registration information regarding an existing relevance database having registration information regarding the pair of entities and the relevance label and the document data in which at least one phrase including the pair of entities registered in a relevance database is present,
• for a pair of the vocabulary syntax patterns, counting the number of pairs of entities appearing concurrently with both of each pair of the vocabulary syntax patterns in the document data, and
• setting a probability model created from a probability density distribution, which includes the counted number of pairs of entities, a parameter “Z” indicating validity of the granting of the relevance label, and a parameter “a” indicating a probability of rightly granting the relevance label, calculating the parameters Z and a for which a likelihood is maximum in the probability model, evaluating the validity of the granting of the relevance label for the pair of entities extracted from the document data, and granting the relevance label based on the evaluation result.

A memory having recorded therein a computer program for causing an information processing apparatus to execute information processing comprising:

• extracting phrases including a pair of entities, to which a relevance label is granted, from document data;
• and
• granting the relevance label indicating a kind of relevance between the pair of entities,
• wherein the granting of the relevance label includes
• acquiring vocabulary syntax patterns included in the phrases including the pair of entities and acquiring the appearing number of times the vocabulary syntax pattern appears in the document data from the document data by analyzing registration information regarding an existing relevance database having registration information regarding the pair of entities and the relevance label and the document data in which at least one phrase including the pair of entities registered in a relevance database is present,
• for a pair of the vocabulary syntax patterns, counting the number of pairs of entities appearing concurrently with both of each pair of the vocabulary syntax patterns in the document data, and
• setting a probability model created from a probability density distribution, which includes the counted number of pairs of entities, a parameter “Z” indicating validity of the granting of the relevance label, and a parameter “a” indicating a probability of rightly granting the relevance label, calculating the parameters Z and a for which a likelihood is maximum in the probability model, evaluating the validity of the granting of the relevance label for the pair of entities extracted from the document data, and granting the relevance label based on the evaluation result.