Abstract: In an inverted list of each node in a taxonomy, among each node, an inverted list of the highest node is a list of integer values indicating an identifier of search subject data, and an inverted list of a node other than the highest node, in place of the identifier, is a list of integer values indicating a position in an inverted list corresponding to a node that is higher by one than the node. Furthermore, a list of integer values in an inverted list of each node is divided into two or more blocks, and a differential value between an integer value and an integer value directly before the integer value in the block is converted into a bit string of a variable length integer code.

Abstract: Facilitate the procedure of evaluating a predictor. This evaluation system comprises an input receiving unit via which elements constituting an evaluation index are specified and an evaluation-index calculation unit that calculates an evaluation-index value for a data set. The evaluation index comprises an element of a first type that evaluates the sample data, an element of a second type that applies weights to the sample data, and an element of a third type that performs a statistical process on a plurality of sample data based on information outputted by the element of the first type and the element of the second type. The evaluation-index calculation unit calculates the above-mentioned evaluation-index value based on the evaluation index comprising the elements received by the input receiving unit.

Abstract: Provided are a word latent topic estimation device and a word latent topic estimation method which are capable of hierarchically performing processing and which are capable of rapidly estimating latent topics of a word while taking into consideration a mixed state of topics.

Abstract: A model estimation device includes: a data input unit; a state number setting unit; an initialization unit which sets initial values of a variational probability of a latent variable, a parameter, and the type of each component; a latent variable variational probability computation unit which computes the variational probability of the latent variable so as to maximize a lower bound of a marginal model posterior probability; a component optimization unit which estimates an optimal type of each component and a parameter thereof so as to maximize the lower bound of the marginal model posterior probability separated for each component of the latent variable model; an optimality determination unit which determines whether or not to continue the maximization of the lower bound of the marginal model posterior probability; and a result output unit which outputs a result.

Abstract: A model estimation device includes: a data input unit 101; a state number setting unit; an initialization unit; a latent variable variational probability computation unit which computes a variational probability of a latent variable so as to maximize a lower bound of a model posterior probability limited in degree of freedom; a component optimization unit which estimates an optimal type of each component and a parameter thereof so as to maximize the lower bound of the model posterior probability limited in degree of freedom and separated for each component of a latent variable model; a free parameter selection variable computation unit which computes the free parameter selection variable; an optimality determination unit which determines whether or not to continue the maximization of the lower bound of the model posterior probability; and a result output unit.

Abstract: The prediction function creation device according to the present invention for creating a prediction function to derive an objective variable by using a set of samples that include explanatory variables and an objective variable, the device includes: a clustering unit that clusters the respective samples by giving labels, and assigns weights to each label in accordance with patterns of missing values for the explanatory variables in labeled samples; a child model creation unit that makes portions of the training data partial training data on the basis of the weights, and determines an explanatory variable that constitutes the prediction function on the basis of patterns of missing values for the explanatory variables in the samples; and a mixture model creation unit that creates the prediction function with respect to each pattern of missing values by using the explanatory variable and the determined partial training data.

Abstract: In order to accurately learn a function for evaluating documents, even in the case where sample documents having missing feature values are included as training data, a document evaluation apparatus is provided with a data classification unit (3) that classifies a set of sample documents based on missing patterns of a first feature vector, a first learning unit (4) that uses feature values that are not missing in the first feature vector and evaluation values to learn a first function for calculating a first score which is a weighted evaluation value for each classification, a feature vector generation unit (5) that computes a feature value corresponding to each classification using the first score, and generates a second feature vector having the computed feature values, and a second learning unit (6) that uses the second feature vector and the evaluation values to learn a second function for calculating a second score for evaluating documents targeted for evaluation.

Abstract: A linkage information output apparatus includes: a linkage information retrieval unit for acquiring, upon receiving source information, destination information linked with the source information, a frequency of occurrence of the source information, a frequency of occurrence of linked each of the destination information, and a frequency of occurrence of a link of the source information and each of the destination information from a linkage information accumulation unit; a recognition degree calculation unit calculating, based on each acquired frequency of occurrence, a recognition degree of the source information, a recognition degree of each acquired destination information, and a recognition degree of each link; and a high interest information narrowing unit selecting destination information to output from among each destination information based on a combination of two or more among a recognition degree of the source information, a recognition degree of the destination information, and a recognition degree

Abstract: [Problem] Since similarity of queries is determined on the basis of similarity of documents that are not related to a search intention, queries whose search intention is similar to each other cannot be determined. [Solution Means] A search result ranking means and a query similarity-degree calculating means are provided. The search result ranking means determines a first weight degree of each of a plurality of documents on the basis of respective evaluation results of the plurality of documents that have been retrieved by a first query, and determines a second weight degree of each of a plurality of documents on the basis of respective evaluation results of the plurality of documents that have been retrieved by a second query. The query similarity-degree calculating means calculates a similarity degree of two search results to which importance have been given, such that the similarity degree becomes larger as the documents of higher importance are similar to each other.

Abstract: Provided are a word latent topic estimation device and a word latent topic estimation method which are capable of hierarchically performing processing and which are capable of rapidly estimating latent topics of a word while taking into consideration a mixed state of topics.

Abstract: A model estimation device includes: a data input unit; a state number setting unit; an initialization unit which sets initial values of a variational probability of a latent variable, a parameter, and the type of each component; a latent variable variational probability computation unit which computes the variational probability of the latent variable so as to maximize a lower bound of a marginal model posterior probability; a component optimization unit which estimates an optimal type of each component and a parameter thereof so as to maximize the lower bound of the marginal model posterior probability separated for each component of the latent variable model; an optimality determination unit which determines whether or not to continue the maximization of the lower bound of the marginal model posterior probability; and a result output unit which outputs a result.

Abstract: A model estimation device includes: a data input unit 101; a state number setting unit; an initialization unit; a latent variable variational probability computation unit which computes a variational probability of a latent variable so as to maximize a lower bound of a model posterior probability limited in degree of freedom; a component optimization unit which estimates an optimal type of each component and a parameter thereof so as to maximize the lower bound of the model posterior probability limited in degree of freedom and separated for each component of a latent variable model; a free parameter selection variable computation unit which computes the free parameter selection variable; an optimality determination unit which determines whether or not to continue the maximization of the lower bound of the model posterior probability; and a result output unit.

Abstract: In order to calculate a reliability that serves as an index of reliableness of an evaluator who evaluated a document, a reliability calculation apparatus (2) is provided with a reliability calculation unit (21) that specifies an evaluation by each evaluator with respect to each author, based on first information specifying respective correspondence relationships between documents targeted for evaluation, evaluators who evaluated the documents and contents of the evaluations, and second information specifying respective correspondence relationships between the documents and authors of the documents, and calculates the reliability of each evaluator, based on the specified evaluation with respect to each author.

Abstract: In order to accurately learn a function for evaluating documents, even in the case where sample documents having missing feature values are included as training data, a document evaluation apparatus is provided with a data classification unit (3) that classifies a set of sample documents based on missing patterns of a first feature vector, a first learning unit (4) that uses feature values that are not missing in the first feature vector and evaluation values to learn a first function for calculating a first score which is a weighted evaluation value for each classification, a feature vector generation unit (5) that computes a feature value corresponding to each classification using the first score, and generates a second feature vector having the computed feature values, and a second learning unit (6) that uses the second feature vector and the evaluation values to learn a second function for calculating a second score for evaluating documents targeted for evaluation.

Abstract: The present invention more suitably determines whether a combination of words is an unexpected combination by the use of a smaller corpus. Disclosed is an unexpectedness determination system provided with: category identifying means which identifies a category to which a word belongs; category co-occurrence frequency identifying means which identifies a category co-occurrence frequency between two categories; unexpectedness index calculating means which calculates an index representing a degree of unexpectedness of a combination of two words.

Abstract: In an inverted list of each node in a taxonomy, among each node, an inverted list of the highest node is a list of integer values indicating an identifier of search subject data, and an inverted list of a node other than the highest node, in place of the identifier, is a list of integer values indicating a position in an inverted list corresponding to a node that is higher by one than the node. Furthermore, a list of integer values in an inverted list of each node is divided into two or more blocks, and a differential value between an integer value and an integer value directly before the integer value in the block is converted into a bit string of a variable length integer code.

Abstract: A linkage information output apparatus includes: a linkage information retrieval unit for acquiring, upon receiving source information, destination information linked with the source information, a frequency of occurrence of the source information, a frequency of occurrence of linked each of the destination information, and a frequency of occurrence of a link of the source information and each of the destination information from a linkage information accumulation unit; a recognition degree calculation unit calculating, based on each acquired frequency of occurrence, a recognition degree of the source information, a recognition degree of each acquired destination information, and a recognition degree of each link; and a high interest information narrowing unit selecting destination information to output from among each destination information based on a combination of two or more among a recognition degree of the source information, a recognition degree of the destination information, and a recognition degree

Abstract: A stage body has a holding surface for placing a substrate thereon. A predetermined embossed configuration is formed by embossing on the holding surface, and thereafter an alumina film in an amorphous state is formed by an anodic oxidation process on the holding surface. The alumina film having an amorphous structure is dense and strong to provide high wear resistance and to substantially prevent separation electrification. This provides a substrate stage having high wear resistance and capable of preventing separation electrification.

Abstract: A mixing valve assembly 42 is communicated with a dedicated tank 51D, storing therein a compatibilizer D, via an inlet valve 43 and is also communicated with dedicated tanks 51A-51C via three injection valves, the tanks storing therein auxiliaries A-C respectively. A chemical formulation is prepared by selectively injecting any one(s) of four chemical agents into the mixing valve assembly 42 by way of on-off control of the inlet valve 43 and the injection valves and blending together the injected chemical agents. Then, the chemical formulation is pumped into SCF by a high-pressure pump 45 such that the SCF and the chemical formulation are mixed together to form a process fluid. Thus, the number of components of a high-pressure portion can be reduced to achieve a cost reduction of an apparatus. Furthermore, a pipe line for pumping the chemical agents is simplified.

Abstract: Disclosed is a high pressure processing method for subjecting a processing object to a high pressure processing using a high pressure fluid. In this method, the high pressure fluid is brought into collision with the surface of the processing object placed in a high pressure processing chamber, and then distributed along the surface of the processing object in an outward direction beyond the processing object.