Abstract: Verified snapshots are generated by obtaining, from one of a plurality of first nodes, a difference between a common data at a first time point and the common data at a second time point that is different from the first time point, generating a first snapshot of the common data at the first time point based on the difference, obtaining a hash of the common data at the first time point from one of the plurality of first nodes, and verifying the first snapshot at the first time point with the hash of the common data at the first time point.

Abstract: Verified snapshots are generated by obtaining, from one of a plurality of first nodes, a difference between a common data at a first time point and the common data at a second time point that is different from the first time point, generating a first snapshot of the common data at the first time point based on the difference, obtaining a hash of the common data at the first time point from one of the plurality of first nodes, and verifying the first snapshot at the first time point with the hash of the common data at the first time point.

Abstract: A method for emergency communication includes encoding a message for visual display including a message to field and a message from field. The visual display is revealed to a reading device in communication with a broadcast center, which stores the visual display. The messages are decoded and sorted from visual displays at the broadcast center. On an index channel, a time and channel number for when a message body of the message will be broadcast on a message channel is broadcasted. The message body is broadcasted on the message channel.

Abstract: A method for answering consecutive questions, using a system which can access a database is provided. The method includes retrieving a questioner identifier associated with a questioner in response to receipt of a question from the questioner. The method also includes obtaining, using the questioner identifier, a history on class labels which were assigned to questions made by the questioner in the past and choosing a class label among the class labels in the history. The method further includes obtaining a list of keywords of the question and judging whether or not each keyword in the keyword list matches a representative keyword in any node among one or more nodes which exist in a hierarchy level in the database, or matches a synonym of the representative keyword.

Abstract: A method for emergency communication includes encoding a message for visual display including a message to field and a message from field. The visual display is revealed to a reading device in communication with a broadcast center, which stores the visual display. The messages are decoded and sorted from visual displays at the broadcast center. On an index channel, a time and channel number for when a message body of the message will be broadcast on a message channel is broadcasted. The message body is broadcasted on the message channel.

Abstract: A method for emergency communication includes encoding a message for visual display including a message to field and a message from field. The visual display is revealed to a reading device in communication with a broadcast center, which stores the visual display. The messages are decoded and sorted from visual displays at the broadcast center. On an index channel, a time and channel number for when a message body of the message will be broadcast on a message channel is broadcasted. The message body is broadcasted on the message channel.

Abstract: A method, computer system, and computer program product for dividing a term with appropriate granularity includes extracting an element word specifying granularity from content by parsing, and, if the term includes at least one element word in a part thereof, dividing the term at a position where the at least one element word exists.

Abstract: A method for searching customer experience information that includes classifying customer experience data from a database of customer journey maps into customer segment groups and business industry groups. Terms may then be extracted from the customer segments groups and the business industry groups to provide a customer segment group dictionary, and a business industry specific dictionary. The method may continue with extracting keywords from a search customer experience using a hardware processor, and selecting from the keywords search terms using the business industry specific dictionary and the customer segment group dictionary to remove redundant terms. The customer experience data may then be searched with the search terms.

Abstract: A method for emergency communication includes encoding a message for visual display including a message to field and a message from field. The visual display is revealed to a reading device in communication with a broadcast center, which stores the visual display. The messages are decoded and sorted from visual displays at the broadcast center. On an index channel, a time and channel number for when a message body of the message will be broadcast on a message channel is broadcasted. The message body is broadcasted on the message channel.

Abstract: A method for emergency communication includes encoding a message for visual display including a message to field and a message from field. The visual display is revealed to a reading device in communication with a broadcast center, which stores the visual display. The messages are decoded and sorted from visual displays at the broadcast center. On an index channel, a time and channel number for when a message body of the message will be broadcast on a message channel is broadcasted. The message body is broadcasted on the message channel.

Abstract: Methods and systems for identifying conditional actions in a business process are disclosed. In accordance with one such method, text fragments are extracted from input documents. In addition, a plurality of pairs of the text fragments that respectively include text fragments that are similar according to a pre-defined similarity standard are determined. For each pair of at least a subset of the pairs, at least one difference between the text fragments of the corresponding pair is determined. Further, at least two particular pairs of the subset of the pairs are merged in response to determining that the particular pairs have at least one of the determined differences in common. Additionally, the merged particular pairs are output to indicate the conditional actions in the business process.

Abstract: To provide a technique for generating, at a high speed, a smaller-sized set that satisfies an intended property such as, for example, being pair-wise, and includes many test cases that match a set of existing test cases given as an input, candidates to be used from a set of existing input test cases are determined in the following manner: for some parameters, values to be held by test case candidates are determined; test cases having the determined values, among those included in the set of input test cases, are selected as the candidates. A test case having the highest score among one or more test case candidates generated with the method of the related art and one or more test case candidates selected from the set of input test cases is added to a set of output test cases.

Abstract: To provide a technique for generating, at a high speed, a smaller-sized set that satisfies an intended property such as, for example, being pair-wise, and includes many test cases that match a set of existing test cases given as an input, candidates to be used from a set of existing input test cases are determined in the following manner: for some parameters, values to be held by test case candidates are determined; test cases having the determined values, among those included in the set of input test cases, are selected as the candidates. A test case having the highest score among one or more test case candidates generated with the method of the related art and one or more test case candidates selected from the set of input test cases is added to a set of output test cases.

Abstract: Methods and systems for identifying conditional actions in a business process are disclosed. In accordance with one such method, text fragments are extracted from input documents. In addition, a plurality of pairs of the text fragments that respectively include text fragments that are similar according to a pre-defined similarity standard are determined. For each pair of at least a subset of the pairs, at least one difference between the text fragments of the corresponding pair is determined. Further, at least two particular pairs of the subset of the pairs are merged in response to determining that the particular pairs have at least one of the determined differences in common. Additionally, the merged particular pairs are output to indicate the conditional actions in the business process.

Abstract: Methods and systems for identifying conditional actions in a business process are disclosed. In accordance with one such method, text fragments are extracted from input documents. In addition, a plurality of pairs of the text fragments that respectively include text fragments that are similar according to a pre-defined similarity standard are determined. For each pair of at least a subset of the pairs, at least one difference between the text fragments of the corresponding pair is determined. Further, at least two particular pairs of the subset of the pairs are merged in response to determining that the particular pairs have at least one of the determined differences in common. Additionally, the merged particular pairs are output to indicate the conditional actions in the business process.

Abstract: A method, computer system, and computer program product for dividing a term with appropriate granularity includes extracting an element word specifying granularity from content by parsing, and, if the term includes at least one element word in a part thereof, dividing the term at a position where the at least one element word exists.

Abstract: A computer-implemented method, program, and system for identifying non-self-descriptive terms in electronic documents. The computer-implemented method for identifying a non-self-descriptive term in an electronic document, includes a memory and a processor communicatively coupled to the memory and configured to execute the steps of a method. The method includes acquiring a noun included in the corpus data. The method further includes calculating a qualifying level and a qualified level in the corpus data related to each known in the corpus data. The method further includes identifying one or more nouns included in the corpus data as having a qualifying level and/or qualified level satisfying a predetermined condition. The method further includes presenting a term related to one or more of the nouns in the electronic document as a candidate for the non-self-descriptive term in the electronic document.

Abstract: A method, apparatus, and computer program product for managing marketing impressions. An apparatus identifies utility of a seller and utility of a user. The apparatus generates an offer of a reward based on the utility of the seller and the utility of the user. The offer of the reward is for performing a social marketing task. The social marketing task is for generating a first number of marketing impressions to achieve a set of objectives of the seller. The apparatus activates the reward for the user when the social marketing task is completed. The social marketing task is completed when the apparatus determines that the user has accepted the offer and the performing of the social marketing task has generated the first number of marketing impressions.

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.