Abstract: A forensic system includes a result information receiving unit that receives result information which is a determination result of connection between a lawsuit and a document group including a predetermined number of documents, which is extracted from document data included in digital information, by a user, an element selection unit that calculates evaluation values of elements which commonly appear in the document group in each result information item from the characteristics of the elements and selects the elements on the basis of the evaluation values, a score calculation unit that calculates a score of each document in the document data from the selected elements included in each document of the document data and the evaluation values of the selected elements, and a recall ratio calculation unit that calculates a recall ratio related to the determination of the connection to the lawsuit on the basis of the score.

Abstract: A document analysis system includes an investigation basic database that stores information related to litigation or fraud investigation, an input-of-investigation category accepting unit that accepts the input of a category of the litigation or fraud investigation, and an investigation type determining unit that determines an investigation category as an investigation target based on the category accepted by the input-of-investigation category accepting unit to extract the type of necessary information from the investigation basic database.

Abstract: A forensic system includes a result information receiving unit that receives result information which is a determination result of connection between a lawsuit and a document group including a predetermined number of documents, which is extracted from document data included in digital information, by a user, an element selection unit that calculates evaluation values of elements which commonly appear in the document group in each result information item from the characteristics of the elements and selects the elements on the basis of the evaluation values, a score calculation unit that calculates a score of each document in the document data from the selected elements included in each document of the document data and the evaluation values of the selected elements, and a recall ratio calculation unit that calculates a recall ratio related to the determination of the connection to the lawsuit on the basis of the score.

Abstract: A document classification and inspection system obtains digital information recorded in plural computers or servers, extracts a document from document information configured by plural documents, included in the obtained digital information, calculates a score indicating the strength of connection between the document and a classification code for the extracted document in a time-series manner, detects a time-series score change from the calculated score, and inspects the degree of relevance between an inspection case and the extracted document from the detected time-series score change.

Abstract: It is possible to analyze digitized document information gathered to be provided as evidence in a legal action and to classify the document information to be easily accessible in the legal action.

Abstract: A forensic system including: a determination acquiring unit that acquires, as performance information, at least one of result information indicating a result of determination of relevance of plural pieces of document data included in digital information to a lawsuit performed by a user and progress information indicating information relating to a progress speed of the determination of relevance performed by the user; a recording unit that records the performance information acquired by the determination acquiring unit; a prediction information generating unit that generates prediction information relating to at least one of the result information and the progress information; an information comparing unit that compares the performance information with the prediction information; and an icon generating unit that generates an icon for presenting an evaluation of the determination of relevance performed by the user based on a comparison result by the information comparing unit.

Abstract: It is possible to reduce a review load of a reviewer. A document management system acquires digital information recorded in a plurality of computers or a server and analyzes the acquired digital information for relevance to a lawsuit. The document management system includes a thread classification unit that verifies supplementary information of each piece of document data included in the digital information and classifies the document data into threads based on the supplementary information, a similarity analysis unit that extracts elements included in the supplementary information of the classified document data for each thread and analyzes similarity between the threads based on the extracted elements, and an integration unit that integrates the threads based on the similarity.

Abstract: It is possible to analyze digitized document information gathered to be provided as evidence in a legal action and to classify the document information to be easily accessible in the legal action.

Abstract: A digital information analysis system includes a target selection unit that selects target digital information, a combination storage unit that stores each of a plurality of word combinations related to a predetermined specific item, a search unit that searches whether the plurality of word combinations stored in the combination storage unit are included in the target digital information selected by the target selection unit, a relation determination unit that determines the relation of the target digital information to the predetermined specific item on the basis of a morphological analysis result when the plurality of word combinations stored in the combination storage unit are included in the target digital information, and a determination result setting unit that associates the determination result of the relation determination unit with the target digital information.

Abstract: Disclosed is a forensic system capable of enhancing the accuracy and efficiency of classification work of whether to submit document information as evidence in a lawsuit by highlighting a portion including a specific keyword in a unit of a sentence. The forensic system includes: a database that registers a keyword for determining by a user whether a plurality of pieces of document information included in the digital information is related to a lawsuit; a retrieving unit that retrieves the keyword registered in the database from the document information; a sentence extracting unit that extracts a sentence including the retrieved keyword from the document information; a score calculating unit that calculates a score indicating a degree of relevance to the lawsuit using a feature value extracted from the sentence extracted by the sentence extracting unit; and a highlighting unit that changes a degree of highlighting of the sentence according to the score.

Abstract: It is possible to analyze digitized document information gathered to be provided as evidence in a legal action and to classify the document information to be easily accessible in the legal action.

Abstract: A document classification system is provided. The document classification system analyzes digital document information which is collected to be submitted as evidence in a lawsuit and classifies the digital document information.

Abstract: A forensic system includes a result information receiving unit that receives result information which is a determination result of connection between a lawsuit and a document group including a predetermined number of documents, which is extracted from document data included in digital information, by a user, an element selection unit that calculates evaluation values of elements which commonly appear in the document group in each result information item from the characteristics of the elements and selects the elements on the basis of the evaluation values, a score calculation unit that calculates a score of each document in the document data from the selected elements included in each document of the document data and the evaluation values of the selected elements, and a recall ratio calculation unit that calculates a recall ratio related to the determination of the connection to the lawsuit on the basis of the score.

Abstract: A patent evaluating device comprises a data acquiring section (105) for acquiring items of patent data and patent attribute information on each item of patent data in a predetermined technical field from a patent database, a data classifying section (115) for classifying the acquired items of patent data into groups within a predetermined period of time, and an evaluation value calculating section (120) for calculating the evaluation value of each item of the patent data by using the patent attribute information on each of the patent data belonging to each group and by using the value determined for each group. With this, the value of a patent application or a patent right is adequately evaluated according to numerical information objectively determined and according to the progress information of the patent application or the patent right or the content information.

Abstract: A company technical document group analysis supporting device comprises index term extracting means for extracting an index term from a group of documents of a subject company including a technical document group, clustering means for classifying the document group of the subject company under given conditions to acquire multiple clusters, number-of-documents determination means for determining the number of documents belong to each cluster, appearance frequency calculating means for calculating a function value of an appearance frequency of each extracted index term in each cluster, per-cluster keyword point calculating means for calculating the keyword point in each cluster by dividing the function value of the appearance frequency of each index term in each cluster by the number of documents belonging to each cluster, and entire-cluster keyword point calculating means for calculating the total for the entire clusters of the results of the calculation by the per-cluster keyword point calculating means for e

Abstract: Data on a group of technical documents having an attribute X and an attribute Y is acquired and a score corresponding to the data on the technical documents belonging to the combination of the attribute X and attribute Y is calculated. The attribute X is placed on the horizontal axis and the attribute Y is placed on the vertical axis. The scores are placed in a matrix manner. According to the scores belonging to each column of the arrangement in the matrix, a group of vectors Xj are generated. According to the scores belonging to each row, a group of vectors Yk are generated. For each of the groups of vectors Xj, Yk, vectors having higher association with each other are placed nearer to each other.

Abstract: A document correlation diagram drawing device includes extracting means (20, 30) for extracting content data and time data of document elements (E) each including one or more documents, dendrogram drawing means (50) for drawing a dendrogram showing a correlation between documents on the basis of the content data of the document elements, clustering means (70) for cutting the dendrogram in accordance with a predetermined rule and extracting clusters, and intra-cluster arranging means (90) for determining an intra-cluster arrangement of the document elements belonging to each cluster on the basis of the time data of the document elements. Accordingly, a dendrogram adequately showing the chronological development in each field can be automatically drawn.

Abstract: Upon selecting the stock portfolio, a plurality of corporate valuation index related data containing an intellectual asset related index is acquired (steps S1 to S6), analysis is performed with the acquired corporate valuation index related data and a company ranking corresponding to at least one prescribed index is created (steps S7 to S13 and S19), a prescribed number of companies is selected from the created company ranking (step S14), an investment ratio is selected in relation to each of the selected companies (step S15), and, based on the obtained distribution result of the investment ratio, a stock portfolio corresponding to the selected company is created and output (steps S16, S17). Therefore, a device for automatically selecting a more preferable stock portfolio based on the results upon performing a comprehensive valuation of companies using a corporate valuation index containing an intellectual asset related index is provided.

Abstract: A keyword extracting device includes high-frequency term extracting means (30) for extracting high-frequency terms which are index terms having a great weight among the index terms in a document group (E) including a plurality of documents (D), the weight including evaluation on the level of an appearance frequency of each index term, clustering means (50) for clustering the high-frequency terms on the basis of a co-occurrence degree C. which is based on the presence/absence of the co-occurrence of each document with the index terms (w) in the document group (E) in each document, score calculating means (70) for calculating a score key(w) of each index term (w) such that a high score is given to the index term among the index terms (w) that co-occurs with the high-frequency term belonging to more clusters (g) and that co-occurs with the high-frequency term in more documents (D), and keyword extracting means (90) for extracting keywords on the basis of the scores.

Abstract: Input of cause-and-effect model information where the coefficients at which three evaluated values, i.e., the evaluated values of business strategy, research-and-development strategy, and intellectual property strategy influence the company evaluated value, the coefficients at which the three evaluated values and the company evaluated value influence the observable indexes respectively, the error variables with which the factors other than the three evaluated values and the company evaluated value give variations to the company evaluated value and the observable indexes respectively are assumed is received. From the inputted the cause-and-effect model information and the observable indexes, the estimates of the coefficients are calculated by covariance structure analysis. From the coefficients and the observable indexes, the three evaluated values and the company evaluated value are calculated. With this, the relationship among the three strategies which are directly nonobservable abstract factors, i.e.