Abstract: A system and associated method for tuning a data clustering program to a clustering task, determine at least one internal parameter of a data clustering program. The determination of one or more of the internal parameters of the data clustering program occurs before the clustering begins. Consequently, clustering does not need to be performed iteratively, thus improving clustering program performance in terms of the required processing time and processing resources. The system provides pairs of data records; the user indicates whether or not these data records should belong to the same cluster. The similarity values of the records of the selected pairs are calculated based on the default parameters of the clustering program. From the resulting similarity values, an optimal similarity threshold is determined. When the optimization criterion does not yield a single optimal similarity threshold range, equivalent candidate ranges are selected.

Abstract: A system and associated method for data mining prediction is presented according to which the user selects a database table by means of a graphical user interface. Some records in the table are complete, while other records are incomplete. A subset of records of the database table is determined wherein each record of the subset contains a data value in the column selected for prediction. This subset of records is used to generate a model by means of a data mining algorithm, such as linear regression, radial basis function, decision tree or neural network methods. The resulting model is then utilized to predict the empty data fields in the column. After completing the prediction, the predicted values are entered into the column for display to the user.

Abstract: A technique for determining an objective quality index for the result of a clustering operation is disclosed. This technique can be used to evaluate the result of different clustering algorithms or can itself be the basis for an iterative clustering algorithm. The invention can be implemented by means of a computer program running on a data processing system which can have parallel processing units for performing different clustering algorithms in parallel.

Abstract: An inherently serial program is processed in parallel, thus leading to higher processing speeds, while maintaining a close approximation to the specific result obtained through a serial running of the program. This goal has been attained based on the fact that the desired degree of closeness between a parallel result and the serial result depends on the particular inherently serial program being run and the type of analysis being performed. That is, some inherently serial processes require a “fine-tuned” result while for others a “coarser” result is acceptable. The frequency at which the parallel branches consolidate their respective results is changed accordingly to alter the degree of closeness between the parallel processed result and the serially processed result.

Abstract: A method and system for registration, authorization, and control of access rights in a computer system. Access rights of subjects on objects in a computer system are controlled using parameterized role types that can be instantiated into role instances equivalent to roles or groups. The required parameters are provided by the subject of the computer system, e.g. by a person, a job position, or an organization unit. Furthermore, relative resource sets are instantiated into concrete resource sets and individual resources by using the same parameter values as for instantiating the role types. Authorization and control of access rights include capability lists providing the access rights of the subjects on the objects of a computer system on a per subject basis. Furthermore, access control lists are derived from capability lists, so that access rights of the subjects on the respective objects are provided.