A business data processing system performing communication with a user device and a finance end device is provided. The business data processing system includes a data organizing subsystem and a data evaluation subsystem. The data organizing subsystem receives documents of a cargo transport task provided by the user device, and recognizes and organizes the contents of the documents. The data evaluation subsystem analyzes the contents of the documents to generate an evaluation of the transport task. The business data processing system transmits the evaluation of the transport task to the finance end device.

A business data processing system performing communication with a user device and a finance end device is provided. The business data processing system includes a data organizing subsystem and a data evaluation subsystem. The data organizing subsystem receives documents of a cargo transport task provided by the user device, and recognizes and organizes the contents of the documents. The data evaluation subsystem analyzes the contents of the documents to generate an evaluation of the transport task. The business data processing system transmits the evaluation of the transport task to the finance end device.

A vector generation unit derives a feature vector of a reference document and a feature vector of a population document. A feature quantity extraction unit performs a dimensionality reduction process to reduce dimensionality of the above feature vectors and sets a dimensional value obtained by the dimensionality reduction process as a first feature quantity, and derives a cosine similarity between the feature vector of the reference document and the feature vector of the population document as a second feature quantity. A retrieval range control unit extracts a specific number of population documents, starting from the population document with the shortest distance to the reference document in a feature quantity space of the first feature quantity, so as to limit a retrieval range. A training data extraction unit extracts, as training data, a specific number of documents from the extracted documents, starting from the document with the lowest cosine similarity.

[Problem(s)] To provide a text analysis system that is low cost and able to detect text with a normal expressive or structural features.

[Solution] A text analysis system 100 according to the present invention includes a text acquisition portion 110 for acquiring text data; a feature extraction portion 120 for converting the text data acquired by the text acquisition portion 110 into a time series signal to extract a feature from the converted time series signal; a feature storage portion 130 for storing the feature extracted by feature extraction portion 120; and an anomalous text detection portion 140 for detecting anomalous text based on the feature in the feature storage portion 130.

Embodiments of the invention are directed to a computer-implemented method of managing message relationships in a messaging system. The computer-implemented method includes receiving, using a processor system, a modification to a first message. The processor system is used to perform a significance-level evaluation of the modification to the first message. Based at least in part on a first result of the significance-level evaluation, the first message is deleted and the modification to the first message is maintained. Based at least in part on a second result of the significance-level evaluation, the first message is maintained; the modification to the first message is stored in a database; and the first message is associated with the modification to the first message in the database.

Embodiments of the invention are directed to a computer-implemented method of managing message relationships in a messaging system. The computer-implemented method includes receiving, using a processor system, a modification to a first message. The processor system is used to perform a significance-level evaluation of the modification to the first message. Based at least in part on a first result of the significance-level evaluation, the first message is deleted and the modification to the first message is maintained. Based at least in part on a second result of the significance-level evaluation, the first message is maintained; the modification to the first message is stored in a database; and the first message is associated with the modification to the first message in the database.

A system for performing one or more steps of a method is disclosed. The method includes receiving a first legal clause, generating, using a segmentation algorithm, a first hidden Markov chain comprising a plurality of first nodes based on the first legal clause, each of the plurality of first nodes corresponding to an element of the first legal clause, generating, using the segmentation algorithm, a second hidden Markov chain comprising a plurality of second nodes based on the second legal clause, each of the plurality of second nodes corresponding to an element of the second legal clause, comparing each of the plurality of first nodes with each of the plurality of second nodes to identify a difference for each of the plurality of first nodes, determine, based on the comparison, whether the difference for each of the plurality of first nodes exceeds a predetermined difference threshold.

A system for performing one or more steps of a method is disclosed. The method includes receiving a first legal clause, generating, using a segmentation algorithm, a first hidden Markov chain comprising a plurality of first nodes based on the first legal clause, each of the plurality of first nodes corresponding to an element of the first legal clause, generating, using the segmentation algorithm, a second hidden Markov chain comprising a plurality of second nodes based on the second legal clause, each of the plurality of second nodes corresponding to an element of the second legal clause, comparing each of the plurality of first nodes with each of the plurality of second nodes to identify a difference for each of the plurality of first nodes, determine, based on the comparison, whether the difference for each of the plurality of first nodes exceeds a predetermined difference threshold.

A screen discrimination device includes: a determination section which executes an automatic operation of a displayed screen of an application to cause screen transition to occur, and determines whether or not each screen at a transition destination is different from each post-transition screen based on a predetermined method; a reception section which outputs a result of the determination of whether or not each screen at the transition destination is different from each post-transition screen, and receives input of a condition for identifying a screen serving as a correction target based on the result of the determination; and a re-determination section which re-executes the automatic operation of the displayed screen of the application to cause the screen transition to occur, determines whether or not each screen at the transition destination meets the condition and, in a case where a first screen meeting the condition is present, when the post-transition screen includes a second screen meeting the condition, determines that the first screen and the second screen are identical to each other, whereby it becomes possible to correct an error in the discrimination of screen identity with a small amount of operation.

A screen discrimination device includes: a determination section which executes an automatic operation of a displayed screen of an application to cause screen transition to occur, and determines whether or not each screen at a transition destination is different from each post-transition screen based on a predetermined method; a reception section which outputs a result of the determination of whether or not each screen at the transition destination is different from each post-transition screen, and receives input of a condition for identifying a screen serving as a correction target based on the result of the determination; and a re-determination section which re-executes the automatic operation of the displayed screen of the application to cause the screen transition to occur, determines whether or not each screen at the transition destination meets the condition and, in a case where a first screen meeting the condition is present, when the post-transition screen includes a second screen meeting the condition, determines that the first screen and the second screen are identical to each other, whereby it becomes possible to correct an error in the discrimination of screen identity with a small amount of operation.