Abstract: A response generation apparatus ensures accurate output. A computer stores graph knowledge including a response generation module generating a response to an input document including a plurality of sentences, the graph knowledge database includes graph data that manages a structure of each type of graph knowledge, and the response generation module generates a first graph knowledge from each of the sentences; searches a second graph knowledge similar to each of the plurality of first graph knowledge while referring to the graph data on the basis of the plurality of first graph knowledge; identifies the plurality of second graph knowledge included in a dense location where a density of the second graph knowledge is high in a graph space; searches third graph knowledge for generating the response while referring to the graph data on the basis of the identified second graph knowledge; and generates the response using the third graph knowledge.

Abstract: An information processing system includes a storing unit that stores evaluation data in which a plurality of subjects are associated with a plurality of evaluation expressions respectively and evaluation expression relationship data indicating relationships between the evaluation expressions, a question generating unit that generates and outputs questions on the basis of the evaluation data and the evaluation expression relationship data, and a matching unit that outputs information relating to the subject included in the evaluation data on the basis of responses when the responses with respect to the questions are input.

Abstract: A sentence creation system, which outputs an opinion sentence on an agenda, includes: an input unit into which the agenda is input; an agenda analyzing unit analyzing the agenda and judging the polarity of the agenda and a keyword used for searching; a searching unit searching for articles using the keyword and a disputed point word showing a disputed point in the discussion; a disputed point determining unit for determining the disputed point used for creating the opinion sentence; a sentence extracting unit for extracting sentences in which the disputed point is described among the articles output by the searching unit; a sentence sorting unit for creating sentences by sorting the extracted sentences; an evaluating unit for evaluating the sentences; a paraphrasing unit for inserting appropriate conjunctions into the sentences; and an output unit for outputting the most highly evaluated sentence among the plural sentences as the opinion sentence.

Abstract: Sentence polarity determination is used to assess whether a sentence is an affirmative expression or a negative expression, and is applied for reputation analysis, etc. Polarity determination determines whether an input sentence is affirmative or negative. When some subject is being talked about, it is sometimes desired to determine whether what is being referred to in the sentence is affirmative or negative, rather than the polarity of the sentence per se. The present invention provides a method for determining the polarity of the sentence by applying a recursive polarity rule based on a dependency structure of the sentence, taking into consideration the portion of the sentence that is being referred to. Use of a recursive rule makes it possible to prevent the number of rules from becoming huge, and thereby to perform efficient polarity determination in terms of memory amount and calculation amount. The length of the dependency needed for polarity determination can also be efficiently controlled.

Abstract: A probabilistic inference system is provided with: a pre-modification model input unit that receives the input of a probabilistic inference model; a model modification execution unit that outputs a modified probabilistic inference model; an inference calculation cost estimation unit that calculates a calculation cost when a probabilistic inference process is performed; an inference error estimation unit that estimates the magnitude of inference error that could be caused in a certain designated random variable in the probabilistic inference model when the probabilistic inference process is performed using the modified probabilistic inference model, compared with when the probabilistic inference process is performed using the probabilistic inference model; an adopted model selection unit that selects the probabilistic inference model to be adopted based on a probabilistic inference condition regarding the calculation cost and the inference error; and a modified model output unit that outputs the adopted probab

Abstract: A chronological change prediction system stores a graphical model which an evidence set at a first time is inputted in and outputs information about states of random variables at a second time when a first period has passed from the first time, determines whether to convert each probability distribution in the first evidence set based on a feature value calculated from the probability distributions and/or a feature value calculated from a random variable associated with the probability distributions in the graphical model, converts each probability distribution determined to be converted into a particular state of a random variable corresponding to each probability distribution determined to be converted, creates a second evidence set from the first evidence set by replacing each probability distribution determined to be converted and included in the first evidence set with the first particular state, and inputs the second evidence set to the graphical model.

Abstract: It is provided an analysis system comprising: a causation/transition structure calculating unit generating a graph structure including a node and a probability variable relating to item, and a probabilistic dependency defined by one of a directed link or an undirected link between the nodes; a node generating unit generating an event space of the nodes; a probability calculating unit calculating a conditional probability of the graph structure; a state transition model reconstructing unit reconstructing a state transition model with a graph structure, an event space and a conditional probability including specified probability variables based on a state transition model; a disease state transition estimating unit estimating a disease state transition probability based on the reconstructed state transition model; and a health guidance supporting unit selecting a subject for health guidance and a content of health guidance based on the estimated disease state transition probability.

Abstract: It is provided an analysis system comprising a processor executing a program and a memory storing the program. The analysis system further comprises a data mapping unit controlling the processor to set an attractive force and a repulsive force acting between the instances based on the similarity information between data, and arranging the instances in a vector space having a certain number of dimensions so that an energy caused by the attractive force and the repulsive force is less than a threshold defined in advance, and a clustering unit classifying the instances arranged in the vector space. The data mapping unit is configured to virtually add one dimension to the vector space, add a minute fluctuation to coordinates of the instances in a direction of the added dimension, and calculate a minimum number of dimensions of the vector space where the instances are stable with respect to the minute fluctuation.

Abstract: The present invention solves a problem that there may be a case that an estimated value of regression cannot be calculated depending on a discrimination result when a regression method is applied after a discrimination method, and has a purpose to obtain an estimating equation with high accuracy even when the number of sample groups to which the regression method is applied is small. An estimating equation that satisfies the regression and discrimination at the same time can be obtained by combining a discrimination evaluation function that evaluates discrimination accuracy and a regression evaluation function that evaluates regression accuracy, calculating a combination evaluation function, and optimizing the combination evaluation function.