Abstract: A system for information retrieval within a database of large size includes a first module for extracting the descriptors associated with each object in the database, and for constructing a table containing the objects and the value of a descriptor associated with an object. The system also includes a second module for applying a number of classification algorithms, for each of the tables obtained from the module, a third module to fusion the results obtained from the module in order to determine, for each type of descriptor, a class number associated with an object, a fourth module for finding which column of a table is closest to the column obtained during the first fusion of the step, and for selecting the map that is closest contained in the table, or best map, and a fifth module to fusion the aggregate “best maps”, and applying an algorithm for searching for the best map to be transmitted to a display means.

Abstract: A method for clustering data or objects in an array, each element of the array corresponding to a similarity between the objects implemented within a computer linked with a database containing the data or objects The method includes determining a number of classes of objects based on values of the relationships computed between an object and a previously established class, for each class found, determining the value of each of the relationships between a class and the other classes, and merging certain classes, and taking each object of each class one by one, determining the value of the relationship of each object with each of the classes other than the class into which the object was initially classed, if the value of the relationship is greater then transferring the object to the new class, this is continued until all the values of the relationships are negative.

Abstract: A method of linear unsupervised classification allowing a database composed of objects and of descriptors to be structured, which is stable on the order of the objects, comprises an initial step for transformation of the qualitative, quantitative or textual data into presence-absence binary data. A structural threshold ?s function is determined of the n2 agreements between the objects to be classified with the structural threshold defining an optimization criterion adapted to the data. The descriptors are used as structuring and construction generators of a partition or set of classes. A class generated by a descriptor and a partition (40, 41, 42) progressively merged. For an optimization criterion involving a function ƒ(Cii,Ci?i?)=Min(Cii,Ci?i?), sums of Minimum functions are linearized.

Abstract: A system for information retrieval within a database of large size includes a first module for extracting the descriptors associated with each object in the database, and for constructing a table containing the objects and the value of a descriptor associated with an object. The system also includes a second module for applying a number of classification algorithms, for each of the tables obtained from the module, a third module to fusion the results obtained from the module in order to determine, for each type of descriptor, a class number associated with an object, a fourth module for finding which column of a table is closest to the column obtained during the first fusion of the step, and for selecting the map that is closest contained in the table, or best map, and a fifth module to fusion the aggregate “best maps”, and applying an algorithm for searching for the best map to be transmitted to a display means.

Abstract: A method for clustering data or objects taking the form of an array, each of the elements of said array corresponding to a value of similarity existing between said objects is implemented within a computer linked with a database containing the data or objects to be classified comprising a work memory, and a processor.

Abstract: Optimized method and system making it possible to manage named entities or proper names that are presented in a different graphical or syntactic form and contained in a database (3), characterized in that it comprises, in combination, the implementation of the Levenshtein method by using a measurement of similarity from the Levenshtein method and of the n-grams method in order to find a canonic entity that can replace a set of named entities in a database.

Abstract: A system for implementing a scoring method, wherein the system includes at least a data analyzer configured to: determine a plurality of scoring intervals dependent upon the data to be analyzed; assign an integer score and a decimal score within the scoring intervals to each data to be analyzed, the score dependent upon a frequency of appearance; search a database for pairings of (scored element, decimal score); and generate an alert if the pairing is found in the database.

Abstract: Optimized method and system making it possible to manage named entities or proper names that are presented in a different graphical or syntactic form and contained in a database (3), characterized in that it comprises, in combination, the implementation of the Levenshtein method by using a measurement of similarity from the Levenshtein method and of the n-grams method in order to find a canonic entity that can replace a set of named entities in a database.

Abstract: A method of linear unsupervised classification allowing a database composed of objects and of descriptors to be structured, which is stable on the order of the objects, comprises an initial step for transformation of the qualitative, quantitative or textual data into presence-absence binary data. A structural threshold ?s function is determined of the n2 agreements between the objects to be classified with the structural threshold defining an optimization criterion adapted to the data. The descriptors are used as structuring and construction generators of a partition or set of classes. A class generated by a descriptor and a partition (40, 41, 42) progressively merged. For an optimization criterion involving a function ƒ(Cii,Ci?i?)=Min(Cii,Ci?i?), sums of Minimum functions are linearized.

Abstract: A machine-implementable method and apparatus for automatic extension of results obtained by querying a database of relationally organized data and expressed in tabular row and column format. The method involves modifying the query by adding column variables to the query that show a high association with the initial query designated variables. The modified query is then used to access the table. This repeats until a stop condition is sensed. Tuples of values elicited responsive to the modified query are included in an extended response if they are significantly similar to tuples elicited by the original query. Several association and similarity modes are described by which the number of variables and tuples can be reiteratively extended.