Abstract: Provided is a composition for brazing containing a flux, a Zn metal powder, a (meth) acrylic resin, and an organic solvent, in which the organic solvent contains (A1) a monohydric alcohol having 1 to 5 carbon atoms; (A2) a monohydric alcohol having 6 to 8 carbon atoms; and (A3) a polyhydric alcohol having 3 or less carbon atoms that are bonded by a carbon-carbon bond.

Abstract: A system and method to estimate a location relating to a user who has not filled in information about the location in a profile field in social media such as a microblog. The system and method estimates association between a user in social media and a location includes the steps of acquiring a first content posted to the social media by a first user associated with a first location, determines regional localization of the first content on the basis of the first location, acquires a second content posted to the social media by a second user not associated with a location, determine the degree of a relationship between the first content and the second content, and associating the first location with the second user on the basis of the localization and the degree of the relationship.

Abstract: A system and method to estimate a location relating to a user who has not filled in information about the location in a profile field in social media such as a microblog. The system and method estimates association between a user in social media and a location includes the steps of acquiring a first content posted to the social media by a first user associated with a first location, determines regional localization of the first content on the basis of the first location, acquires a second content posted to the social media by a second user not associated with a location, determine the degree of a relationship between the first content and the second content, and associating the first location with the second user on the basis of the localization and the degree of the relationship.

Abstract: A method for generating training data for disambiguation of an entity comprising a word or word string related to a topic to be analyzed includes acquiring sent messages by a user, each including at least one entity in a set of entities; organizing the messages and acquiring sets, each containing messages sent by each user; identifying a set of messages including different entities, greater than or equal to a first threshold value, and identifying a user corresponding to the identified set as a hot user; receiving an instruction indicating an object entity to be disambiguated; determining a likelihood of co-occurrence of each keyword and the object entity in sets of messages sent by hot users; and determining training data for the object entity on the basis of the likelihood of co-occurrence of each keyword and the object entity in the sets of messages sent by the hot users.

Abstract: The present invention provides a method for selecting an identified message group from among the plurality of messages sent by a plurality of users of social media. For the messages sent by users other than the original user that quote the message sent by the original message user, the method provides: performing a primary evaluation of the potential for being further resent; identifying a single user who has sent a message for which the primary evaluation result was higher than a predetermined first threshold; identifying a message group similar to a resent messages group, based on a resent messages group that quotes the message send by the single user; performing a secondary evaluation for the potential that the similar message group will be further resent; and selecting a message group for which the secondary evaluation result was higher than a predetermined second threshold.

Abstract: The present invention provides at least a method includes: extracting a plurality of partial communities from a plurality of users, based on the relationships of companion messages; computing a first degree of similarity for showing the similarity of the companion partial communities, based on the relationship of a user belonging to one partial community with a user belonging to the other partial community, from among the plurality of communities; computing a second degree of similarity for showing the similarity of companion partial communities, based on words within the messages sent by users belonging to both partial communities and under the condition that the first similarity be higher than a predetermined first threshold value; and creating an integrated community by integrating the companion partial communities under the condition that the second similarity be higher than a predetermined second threshold value.

Abstract: The present invention provides at least a method includes: extracting a plurality of partial communities from a plurality of users, based on the relationships of companion messages; computing a first degree of similarity for showing the similarity of the companion partial communities, based on the relationship of a user belonging to one partial community with a user belonging to the other partial community, from among the plurality of communities; computing a second degree of similarity for showing the similarity of companion partial communities, based on words within the messages sent by users belonging to both partial communities and under the condition that the first similarity be higher than a predetermined first threshold value; and creating an integrated community by integrating the companion partial communities under the condition that the second similarity be higher than a predetermined second threshold value.

Abstract: A method for inferring a location where each textual message was posted by a test user. The method includes partitioning an area into plural sub-areas, associating each of textual messages posted by training users with a sub-area where each of the textual message was posted, extracting a keyword from the textual message associated with each sub-area, constructing a feature vector of each sub-area, based on the extracted keyword, computing a transition probability for each sub-area by time-series of location information associated with the textual messages posted by the training user, the transition probability being a probability of transition from a target sub-area to other sub-areas, computing plural scores of each location, using the feature vector, where each textual message was posted by the test user, and computing, based on the plural scores and the transition probability, time-series of locations where each textual message was posted by the test user.

Abstract: A method, a computer system, and a computer program product for determining an expertness level for a target keyword. The method includes preparing a document set associated with the target keyword, identifying, for each document in the document set, a category to which the document in the document set belongs, and determining an expertness level for the target keyword, based on a degree of dispersion of the identified categories. Each document in the document set may be associated with a category, and a graph which defines relations among the identified categories is generated from the identified categories to obtain the degree of dispersion of the identified categories. On condition that the degree of dispersion is lower, the expertness level for the target keyword may be determined to be higher or a higher expertness level is assigned to the target keyword.

Abstract: A system and computer implemented method for estimating difficulty of a document includes retrieving a subject document from a storage, setting difficulty of each keyword included in the subject document to locality of the keyword in the subject document as an initial value, estimating, by a processor, difficulty of each subject document by a statistical processing of the difficulties of keywords included in the subject document, and updating the difficulty of each keyword based on the difficulty of each subject document depending on a significance value of the keyword in the subject document.

Abstract: A method for generating training data for disambiguation of an entity comprising a word or word string related to a topic to be analyzed includes acquiring sent messages by a user, each including at least one entity in a set of entities; organizing the messages and acquiring sets, each containing messages sent by each user; identifying a set of messages including different entities, greater than or equal to a first threshold value, and identifying a user corresponding to the identified set as a hot user; receiving an instruction indicating an object entity to be disambiguated; determining a likelihood of co-occurrence of each keyword and the object entity in sets of messages sent by hot users; and determining training data for the object entity on the basis of the likelihood of co-occurrence of each keyword and the object entity in the sets of messages sent by the hot users.

Abstract: A clad material is composed of a core material, a first skin material covering one side of the core material, a second skin material covering the other side of the core material, and an intermediate material interposed between the core material and the first skin material. The core material is made of an Al alloy containing Cu (0.3 to 0.5 mass %), Mn (0.6 to 1.0 mass %), Ti (0.05 to 0.15 mass %). The first skin material is made of an Al alloy containing Si (7.9 to 9.5 mass %) and Fe (0.1 to 0.3 mass %). The second skin material is made of an Al alloy containing Si (4.5 to 5.5 mass %) and Cu (0.5 to 0.7 mass %). The intermediate material is made of an Al alloy containing Mn (0.2 to 0.4 mass %) and Zn (0.2 to 0.4 mass %).

Abstract: A system and method to estimate a location relating to a user who has not filled in information about the location in a profile field in social media such as a microblog. The system and method estimates association between a user in social media and a location includes the steps of acquiring a first content posted to the social media by a first user associated with a first location, determines regional localization of the first content on the basis of the first location, acquires a second content posted to the social media by a second user not associated with a location, determine the degree of a relationship between the first content and the second content, and associating the first location with the second user on the basis of the localization and the degree of the relationship.

Abstract: To provide a technique to estimate a location relating to a user who has not filled in information about the location in a profile field in social media such as a microblog. A method for estimating association between a user in social media and a location includes the steps of acquiring a first content posted to the social media by a first user associated with a first location, determining regional localization of the first content on the basis of the first location, acquiring a second content posted to the social media by a second user not associated with a location, determining the degree of a relationship between the first content and the second content, and associating the first location with the second user on the basis of the localization and the degree of the relationship.

Abstract: A method for generating training data for disambiguation of an entity comprising a word or word string related to a topic to be analyzed includes acquiring sent messages by a user, each including at least one entity in a set of entities; organizing the messages and acquiring sets, each containing messages sent by each user; identifying a set of messages including different entities, greater than or equal to a first threshold value, and identifying a user corresponding to the identified set as a hot user; receiving an instruction indicating an object entity to be disambiguated; determining a likelihood of co-occurrence of each keyword and the object entity in sets of messages sent by hot users; and determining training data for the object entity on the basis of the likelihood of co-occurrence of each keyword and the object entity in the sets of messages sent by the hot users.

Abstract: A method for generating training data for disambiguation of an entity comprising a word or word string related to a topic to be analyzed includes acquiring sent messages by a user, each including at least one entity in a set of entities; organizing the messages and acquiring sets, each containing messages sent by each user; identifying a set of messages including different entities, greater than or equal to a first threshold value, and identifying a user corresponding to the identified set as a hot user; receiving an instruction indicating an object entity to be disambiguated; determining a likelihood of co-occurrence of each keyword and the object entity in sets of messages sent by hot users; and determining training data for the object entity on the basis of the likelihood of co-occurrence of each keyword and the object entity in the sets of messages sent by the hot users.

Abstract: A method for processing a first and second message groups submitted by a user includes executing a learning operation and an estimating operation. The learning operation includes extracting a first location message having a specifiable location from the first message group, extracting a first expression message including a specific expression from the first message group; and associating the location and the expression on the basis of the date and time submitted with each message, and for generating learning data. The estimating operation includes extracting a second expression message including a predetermined expression from the second message group, accepting input of a specified date and time for estimating a location; associating the expressions with each other on the basis of the specified date and time; and estimating a location at the specified date and time using coordination filtering on the basis of the learning data and the input data.

Abstract: A computer system, method, and article of manufacture for extracting a term from electronic document data that includes a text segment. The system includes: a first extraction unit that uses a first text processing information to extract a noun word from the document data; a second extraction unit that uses a second text processing information to extract a term candidate in relation to the noun word or a corpus that includes text data described in the same language used in the document data; a weight assignment unit that uses a third text processing information to select which type to assign a weight from the plurality of types and assigns the weight to the selected type for each noun word and term candidate; a determination unit that determines the type to which the noun word and term candidate belong; and an output unit to output the noun word and term candidate.

Abstract: The present invention provides a method for selecting an identified message group from among the plurality of messages sent by a plurality of users of social media. For the messages sent by users other than the original user that quote the message sent by the original message user, the method provides: performing a primary evaluation of the potential for being further resent; identifying a single user who has sent a message for which the primary evaluation result was higher than a predetermined first threshold; identifying a message group similar to a resent messages group, based on a resent messages group that quotes the message send by the single user; performing a secondary evaluation for the potential that the similar message group will be further resent; and selecting a message group for which the secondary evaluation result was higher than a predetermined second threshold.

Abstract: A support apparatus, computer-implemented method, and article of manufacture for supporting a processing of a character string in a document. The support apparatus includes: a document storage unit; a designation reception unit; a document acquisition unit; a historical-information storage unit; a reference-information generator; and a presentation unit. The method includes: receiving designation from a user; acquiring a document from the document storage device based on the designation by the user; reading pieces of historical information related to the acquired document from the historical-information storage device, and thereby generating reference information for helping the user to select a processing of the character string in the document; and presenting, to the user, a screen for receiving the designation of the processing of the character string in the acquired document, together with the reference information.