This paper describes the possibilities of variable selection in large-scale industrial systems. It introduces knowledge-based, data-based and model-based methods for this purpose. As an example, Case-Based Reasoning application for the evaluation of the web break sensitivity in a paper machine is introduced. The application uses Linguistic Equations approach and basic Fuzzy Logic. The indicator...

This paper is a study of a certain type of collocations and implication and application to acquisition of lexical selection rules in transfer-approach MT systems. Collocations reveal the co-occurrence possibilities of linguistic units in one language, which often require lexical selection rules to enhance the natural flow and clarity of MT output. The study presents an automatic acquisition and...

This paper describes a novel feature selection algorithm for unsupervised clustering, that combines the clustering ensembles method and the population based incremental learning algorithm. The main idea of the proposed unsupervised feature selection algorithm is to search for a subset of all features such that the clustering algorithm trained on this feature subset can achieve the most similar ...

We show how to modify the model of knowledge based on interpreted systems developed by Halpern and Moses to give a new class of interpreted systems, representational interpreted systems, in which the fact that an agent knows that φ corresponds to a particular configuration in the agent’s internal state. This permits an objective and constructive test for the agent’s knowledge in a way similar t...

Based on some features of the immune system (the selection-based mechanism compatible with Edelman’s selectionist principle, self/nonself-reference and negative/positive selection), we proposed the immune algorithm. The algorithm proceeds in three steps: diversity generation, establishment of self-tolerance, and memorizing non-self. The algorithm may be used typically to deal with the system by...

We present a principled method of obtaining a weighted similarity metric for 3D image retrieval, rmly rooted in Bayes decision theory. The basic idea is to determine a set of most discriminative features by evaluating how well they perform on the task of classifying images according to prede ned semantic categories. We propose this indirect method as a rigorous way to solve the di cult feature ...

Conventional means of selecting a service are predominantly based on the results returned from service discovery. Typically most approaches employ a matchmaker which works in tandem with a service registry and user preferences based on the functionality of services. Nonfunctional attributes of services, such as reliability, timeliness and other quality of service criteria are typically not addr...

The current infrastructure for Web services supports service discovery based on a common repository. However, the key challenge is not discovery but selection: ultimately, the service user must select one good provider. Whereas service descriptions are given from the perspective of providers, service selection must take the perspective of users. In this way, service selection involves pragmatic...

In the design of complex systems serving a broad group of stakeholders, it can be difficult to prioritize objectives for the architecture. We postulate that it is possible to make architectural decisions based on consideration of stakeholder value delivery. We introduce the concept of using network models linked to architecture models to investigate value delivery. These models are used to exam...