Abstract: An example operation may include one or more of storing chaincode comprising executable steps of a multi-party process generated from a state diagram in which a blockchain is an intermediary between a plurality of off-chain systems, receiving a request to execute the multi-party process, processing a step of the multi-party process based on the request via execution of the stored chaincode including the executable steps of the multi-party process to generate a processed result for the step, and storing an identification of the processed step and the generated processed result via a data block among a hash-linked chain of data blocks of the blockchain.

Abstract: A method is provided for anonymizing statistical data for a secure transfer. The method calculates statistical information for each of the statistical data. The method aggregates the statistical information to calculate a valid range for each of the statistical information. The method removes outlier data based on the valid range for each of the statistical data. The method creates pair lists from each of the statistical data and target data, the pair lists having a respective member from both the statistical data and the target data. The method replaces each respective member of the target data by a random number existing in a range of a corresponding one of a plurality of target data bins. The method swaps each pair in each pair list in a random order using the randomized number, wherein the random number used for swapping is different for different ones of the pair lists.

Abstract: Methods and systems for text classification include identifying a text sample, classified according to a first class in a set of hierarchical graphs of classes, that is more similar to a second class in the set of hierarchical graphs of classes than to the first class according to a similarity metric. A word is deleted from the identified text sample that is associated with the second class. A word is added to the identified text sample that is associated with the first class. A text classification model is trained using the text sample as training data. Text classification is performed on an input text using the trained text classification model implemented on a processor device.

Abstract: A computer-implemented method is provided for automatically transforming a Business Process Model (BPM) into a hierarchical statechart. The BPM has parallel paths with at least one FORK node and at least one JOIN node. The method includes, responsive to identifying each of the at least one FORK node in the BPM in a node analysis: (i) generating a FORK edge sub-statechart having an initial state and a working state for each of edges from the at least one FORK node, and attaching the FORK edge sub-statechart to a hierarchical state for the at least one FORK node; and (ii) generating a synchronizer sub-statechart corresponding to each JOIN node going through the FORK node to receive a synchronization event from each FORK edge sub-statechart, and attaching the synchronizer sub-statechart to the hierarchical state for the at least one FORK node to form an intermediate version of the hierarchical statechart.

Abstract: An example operation may include one or more of receiving an entry intended for a database, identifying a plurality of data fields associated with the entry, identifying a plurality of data fields associated with one or more previously committed entries, adding the entry to the database with a temporary status, determining whether one or more of the plurality of data fields associated with the entry match one or more of the plurality of data fields associated with the one or more previously committed entries, and responsive to determining whether the match occurred, determining whether to commit the entry to the database and a status to assign the entry.

Abstract: An example operation may include one or more of receiving a plurality of state representations of a plurality of off-chain systems for performing a multi-party process via a blockchain, wherein each state representation identifies send and receive events of a respective off-chain system, removing one or more events from a state representation of an off-chain system to generate a reduced state representation, generating executable chaincode for the blockchain based on the plurality of state representations including the reduced state representation, and storing the generated chaincode via a blockchain node of the blockchain.

Abstract: An example operation may include one or more of connecting, by a template generator node, to a blockchain that includes a plurality of user peers, retrieving, by the template generator node, a contract file from a ledger of the blockchain, executing, by the template generator node, chaincode to: extract a plurality of portions of the contract file based on a structure of a contract, determine common portions among the plurality of the portions, determine typical portions of the contract file from the common portions, generate a template based on the typical portions, format the template based on a state chart, and storing, by the template generator node, the template onto the ledger of the blockchain for access by the plurality of the user peers.

Abstract: An example operation may include one or more of receiving, by a participating peer, an accident certificate associated with a claim, extracting, by the participating peer, an accident type data from the accident certificate, receiving, by the participating peer, a repair estimate associated with the accident certificate, the repair estimate containing a value and repair steps, executing, by the participating peer, a smart contract to obtain from a blockchain an average value and a standard deviation for the value of the repair estimate based on the accident type data, subtracting, by the participating peer, the average value from the value of the repair estimate and dividing a subtraction result by the standard deviation to obtain a deviation of the value of the repair estimate, and in response to the deviation of the value of the repair estimate exceeding a threshold value, declining the repair estimate for the claim by the participating peer.

Abstract: A method is provided for anonymizing statistical data for a secure transfer. The method calculates statistical information for each of the statistical data. The method aggregates the statistical information to calculate a valid range for each of the statistical information. The method removes outlier data based on the valid range for each of the statistical data. The method creates pair lists from each of the statistical data and target data, the pair lists having a respective member from both the statistical data and the target data. The method replaces each respective member of the target data by a random number existing in a range of a corresponding one of a plurality of target data bins. The method swaps each pair in each pair list in a random order using the randomized number, wherein the random number used for swapping is different for different ones of the pair lists.

Abstract: An example operation may include one or more of connecting, by a template generator node, to a blockchain that includes a plurality of user peers, retrieving, by the template generator node, a contract file from a ledger of the blockchain, executing, by the template generator node, chaincode to: extract a plurality of portions of the contract file based on a structure of a contract, determine common portions among the plurality of the portions, determine typical portions of the contract file from the common portions, generate a template based on the typical portions, format the template based on a state chart, and storing, by the template generator node, the template onto the ledger of the blockchain for access by the plurality of the user peers.

Abstract: An example operation may include one or more of receiving, by a participating peer, an accident certificate associated with a claim, extracting, by the participating peer, an accident type data from the accident certificate, receiving, by the participating peer, a repair estimate associated with the accident certificate, the repair estimate containing a value and repair steps, executing, by the participating peer, a smart contract to obtain from a blockchain an average value and a standard deviation for the value of the repair estimate based on the accident type data, subtracting, by the participating peer, the average value from the value of the repair estimate and dividing a subtraction result by the standard deviation to obtain a deviation of the value of the repair estimate, and in response to the deviation of the value of the repair estimate exceeding a threshold value, declining the repair estimate for the claim by the participating peer.

Abstract: An example operation may include one or more of receiving an entry intended for a database, identifying a plurality of data fields associated with the entry, identifying a plurality of data fields associated with one or more previously committed entries, adding the entry to the database with a temporary status, determining whether one or more of the plurality of data fields associated with the entry match one or more of the plurality of data fields associated with the one or more previously committed entries, and responsive to determining whether the match occurred, determining whether to commit the entry to the database and a status to assign the entry.

Abstract: An example operation may include one or more of storing chaincode comprising executable steps of a multi-party process generated from a state diagram in which a blockchain is an intermediary between a plurality of off-chain systems, receiving a request to execute the multi-party process, processing a step of the multi-party process based on the request via execution of the stored chaincode including the executable steps of the multi-party process to generate a processed result for the step, and storing an identification of the processed step and the generated processed result via a data block among a hash-linked chain of data blocks of the blockchain.

Abstract: An example operation may include one or more of receiving a plurality of state representations of a plurality of off-chain systems for performing a multi-party process via a blockchain, wherein each state representation identifies send and receive events of a respective off-chain system, removing one or more events from a state representation of an off-chain system to generate a reduced state representation, generating executable chaincode for the blockchain based on the plurality of state representations including the reduced state representation, and storing the generated chaincode via a blockchain node of the blockchain.

Abstract: Methods and systems for text classification include identifying a text sample, classified according to a first class in a set of hierarchical graphs of classes, that is more similar to a second class in the set of hierarchical graphs of classes than to the first class according to a similarity metric. A word is deleted from the identified text sample that is associated with the second class. A word is added to the identified text sample that is associated with the first class. A text classification model is trained using the text sample as training data. Text classification is performed on an input text using the trained text classification model implemented on a processor device.

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: Provided is a method for controlling information shared in a virtual world by a server and a plurality of users' client terminals connected to each other through a network. In this information control method, a computer creates a third object between a first object and a second object in the virtual world when the first object and second object transmit communication information therebetween, and filters the information with the third object. In addition, when an object transmits visual information, the third object can be created around the object transmitting the visual information. The third object can be created as a pseudo wall.

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 computer implemented method, a program, and a system for effectively providing versatile non-text information suitable for use in a multi-language environment. The method includes the steps of: receiving search results of a database using a search criterion in a certain language and a search criterion in another language corresponding to the search criterion in which specific language attributes are associated with non-text elements that are included in the search results; scoring the non-text elements included in the search results depending on a similarity to another element with which a different language attribute is associated; and identifying at least one of the non-text elements included in the search results on the basis of the scores.

Abstract: Correcting data by expediting identification of a part of the data, which needs to be corrected. In response to receiving an instruction, outputting the information, and identifying the part which needs to be corrected. In response to a received instruction, expediting correction of the part by correcting the part and outputting the information.