Abstract: [Object] To provide an information processing apparatus, an information processing method, and a program capable of efficiently using information regarding a user evaluation of a target vehicle. [Solution] An information processing apparatus including: a recognition section configured to automatically recognize information of a target vehicle from environment information of a user; an acquisition section configured to acquire a user evaluation of the recognized target vehicle; and a generation section configured to generate information for issuing a notification of the acquired user evaluation.

Abstract: [Object] To provide an information processing apparatus, an information processing method, and a program capable of providing more useful information to a driver. [Solution] An information processing apparatus including: a prediction section configured to predict accident probability of a vehicle driven by a user; and an output control section configured to cause information to be output to the user, the information corresponding to a factor that increases the accident probability predicted by the prediction section.

Abstract: A system that generates a first parameter corresponding to a type of an object; generates a second parameter corresponding to transaction information corresponding to the object; calculates a feature value corresponding to the object by applying a predetermined function to the first and second parameters; generates display data based on the calculated feature value; and outputs the display data to a device remotely connected to the system via a network.

Abstract: There is provided an information processing device capable of intuitively adding a hardware resource intended to execute the learning, the information processing device including: a display control unit configured to control display of information indicating progress of a learning process and an addition button used to add dynamically a second hardware resource intended to execute the learning process to a first hardware resource on which the learning process is being executed.

Abstract: [Object] To provide information useful to a variety of users engaged in real estate transactions. [Solution] Provided is an information processing device, including: an information extraction unit that extracts information related to a second real estate property or a second transaction similar to a first real estate property or a first transaction occurring with respect to the first real estate property, on a basis of features of a real estate property or a transaction with respect to a real estate property; and a transaction result prediction unit that predicts a transaction result including a first price associated with the first real estate property in the first transaction, on a basis of the extracted information.

Abstract: [Object] To be able to predict a change in condition of a user in a wider range. [Solution] Provided is an information processing apparatus including: a sensor information acquisition unit configured to acquire sensor information including at least biological information of a user; and a biological information change prediction unit configured to predict a change of the biological information from the sensor information in accordance with a framework based on knowledge concerning poor physical condition of the user.

Abstract: An information processing apparatus performs topic analysis on one or more collected documents to calculate a probability indicating the degree of fitness of each sentence constituting the collected document for each item of a local topic, performs linguistic analysis on the collected document to detect a unique expression pattern in each item of the local topic, sets topic usefulness for each sentence constituting the collected document on the basis of evaluation of the sentence by an evaluator, sets a total evaluation value with respect to each item of the local topic on the basis of the topic analysis result and the topic usefulness, selects an item of the local topic on the basis of the total evaluation values, and extracts an appropriate sentence for a unique expression pattern in the selected item of the local topic from the collected document as a profound text candidate.

Abstract: A hinge device has a base, a body removably provided at the base, and a mounting member rotatably connected to the body. The base has a base member, a first movable member disposed at the base member such that the first movable member is movable in a first direction and non-movable in a second direction orthogonal to the first direction, and a second movable member disposed at the first movable member such that the second movable member is movable in the second direction and non-movable in the first direction, and the body removably attached to the second movable member. A first position adjustment mechanism is provided between the base member and the first movable member. The first position adjustment mechanism adjusts position of the first movable member with respect to the base member in the first direction.

Abstract: An information processing device includes a collection section that collects log data of a plurality of users from a plurality of services, a publishing level setting section that is possible to set a publishing level of the collected log data to each service for each user, and a providing control section that controls provision of the collected log data to the plurality of services based on the publishing level that is set.

Abstract: An information processing apparatus includes: 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. The label granting unit acquires vocabulary syntax patterns included in the phrases including the pair of entities, acquires the appearing number of times the vocabulary syntax pattern appears in the document data from the document data, counts the number of pairs of entities, sets a probability model created from a probability density distribution, 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, and grants the relevance label on the evaluation result.

Abstract: A hinge device has a base, a body removably provided at the base, and a mounting member rotatably connected to the body. The base has a base member, a first movable member disposed at the base member such that the first movable member is movable in a first direction and non-movable in a second direction orthogonal to the first direction, and a second movable member disposed at the first movable member such that the second movable member is movable in the second direction and non-movable in the first direction, and the body removably attached to the second movable member. A first position adjustment mechanism is provided between the base member and the first movable member. The first position adjustment mechanism adjusts position of the first movable member with respect to the base member in the first direction.

Abstract: There is provided a learning apparatus including: a first data acquisition unit which acquires first user preference data belonging to a first data space; a second data acquisition unit which acquires second user preference data of a user in common with the first user preference data, the second user preference data belonging to a second data space which is different from the first data space; a compression unit which generates first compressed user preference data having less data item number from the first user preference data by utilizing a first set of parameters; and a learning unit which learns a second set of parameters utilized for generating second compressed user preference data having the same data item number as that of the first compressed user preference data from the second user preference data so that difference between the first compressed user preference data and the second compressed user preference data is to be small across a plurality of users.

Abstract: A text analysis device includes a storage unit configured to store opinions of users who participate in a discussion about a predetermined theme as text data and author information for specifying authors of the text data, a feature quantity data generation unit configured to generate feature quantity data of the text data stored in the storage unit, an observation time-series signal generation unit configured to generate observation time-series signals based on information obtained by performing a predetermined process with respect to the feature quantity data, a change point detection unit configured to detect a change point of the discussion based on the observation time-series signals, and an influence specifying unit configured to specify an opinion having influence on an opinion corresponding to the specified text data out of opinions of the discussion based on the detected change point and the author information.

Abstract: An information processing device includes: a user information obtaining unit configured to obtain information relating to data of content that a user has used; a meta information obtaining unit configured to obtain content meta information corresponding to content that the user has used; a first vector generating unit configured to generate a first user preference vector with each of the obtained content meta information as elements thereof; a second vector generating unit configured to generate a second user preference vector wherein the generated first user preference vector is analyzed and the number of elements of the first user preference vector is compressed; and a user identifying unit configured to identify a user corresponding to a second user preference vector having a high similarity to a second user preference vector determined beforehand from multiple second user preference vectors.

Abstract: An information processing apparatus performs topic analysis on one or more collected documents to calculate a probability indicating the degree of fitness of each sentence constituting the collected document for each item of a local topic, performs linguistic analysis on the collected document to detect a unique expression pattern in each item of the local topic, sets topic usefulness for each sentence constituting the collected document on the basis of evaluation of the sentence by an evaluator, sets a total evaluation value with respect to each item of the local topic on the basis of the topic analysis result and the topic usefulness, selects an item of the local topic on the basis of the total evaluation values, and extracts an appropriate sentence for a unique expression pattern in the selected item of the local topic from the collected document as a profound text candidate.

Abstract: An information processor carrying out statistical natural language processing for a document, the information processor includes a characteristic amount extraction unit configured to detect context information including a proper noun pair from the document and extract a characteristic amount of the detected context information; a characteristic amount analysis unit configured to, by analyzing the characteristic amount of the extracted context information using a probability model in which a document topic meaning an entire topic of the document and a context topic meaning a local topic of the document are considered, estimate a potential variable and a context topic ratio in the probability model; and a clustering unit configured to cluster the proper noun pair included in the context information based on the context topic ratio estimated regarding the characteristic amount of the respective context information.

Abstract: An information processing apparatus includes: 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. The label granting unit acquires vocabulary syntax patterns included in the phrases including the pair of entities, acquires the appearing number of times the vocabulary syntax pattern appears in the document data from the document data, counts the number of pairs of entities, sets a probability model created from a probability density distribution, 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, and grants the relevance label on the evaluation result.