Abstract: In a plurality of sub-systems, a respective sub-system processes data according to a logic system specific to the respective sub-system. At least some of the sub-systems respectively include at least one acquisition unit which is configured in such a way that it acquires information relating to the processed data of the respective sub-system and converts it into a predefined data structure which is the same for at least some of the sub-systems. the acquisition units are connected to a common analysis unit which during operation of the communication system receives information from the acquisition units relating to the processed data in the predefined data structure and analyzes it in relation to predefined criteria.

Abstract: Computer-based method of detecting the guidance performance of an information driven web site for a user seeking a desired content, wherein a transition value is assigned to each click based on the effectiveness and efficiency of transition between web pages of such web site, and an indicator value is determined by combining these values into a metric, which reflects guidance performance of such web site.

Abstract: Computer-based method of detecting the guidance performance of an information driven web site for a user seeking a desired content, wherein a transition value is assigned to each click based on the effectiveness and efficiency of transition between web pages of such web site, and an indicator value is determined by combining these values into a metric, which reflects guidance performance of such web site.

Abstract: In a plurality of sub-systems, a respective sub-system processes data according to a logic system specific to the respective sub-system. At least some of the sub-systems respectively include at least one acquisition unit which is configured in such a way that it acquires information relating to the processed data of the respective sub-system and converts it into a predefined data structure which is the same for at least some of the sub-systems. the acquisition units are connected to a common analysis unit which during operation of the communication system receives information from the acquisition units relating to the processed data in the predefined data structure and analyzes it in relation to predefined criteria.

Abstract: Method of computer-based detection of discrepancy between a user's perception of web sites and an author's intention of these web sites, wherein user interactions are gathered and combined with the content of individual web pages, the combination thereof is clustered topically, and a respective topical distance of the web pages is compared to a structural distance of the web pages, which results from the author's elected arrangement of the web pages to each other, whereby the difference in both distances gives the discrepancy in the user's perception and the author's intention of the web pages, characterized in that at least parts of the text are extracted from the web pages for building keywords, which represent the contents of such web pages.

Abstract: The training phase of a neural network NN is stopped before an error function, which is to be minimized in the training phase, reaches a minimum (301). A first variable (EG) is defined using, for example, the optimal brain damage method or the optimal brain surgeon method, on the assumption that the error function is at the minimum. Furthermore, a second variable (ZG) is determined which provides an indication of the manner in which the value of the error function varies when a weight (wi) is removed from the neural network (NN). The first variable (EG) and the second variable (ZG) are used to classify the weight (wi) as being suitable or unsuitable for removal from the neural network (NN).

Abstract: A state vector (SVt) is determined with elements that characterize a financial market (101). Taking into account predetermined evaluation variables, an evaluation (Vt) is determined (102) for the state vector (SVt). In addition, a chronologically following state vector (SVt+1) is determined (103) and evaluated (Vt+1). On the basis of the two evaluations (Vt, Vt+1), weights (wi) of the neural network (NN) are adapted (104) using a reinforcement learning method (&Dgr;wi).