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The following topics are dealt with: Web intelligence; World Wide Web; Web information retrieval; information filtering; ontology engineering; semantic Web; Web mining; social networks; ubiquitous intelligence; and Web agents.
This paper deals with large scale information retrieval aiming at contributing to web searching. The collections of documents considered are huge and not obvious to tackle with classical approaches. The greater the number of documents belonging to the collection, the more powerful approach required. A Bees Swarm Optimization algorithm called BSO-IR is designed to explore the prohibitive number of...
The target of many studies in the health sciences is the discovery of cause-effect relationships among observed variables of interest, for example: treatments, exposures, preconditions, and outcomes. Causal modeling and causal discovery are central to medical science. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulation...
Representing meaning is a major challenge facing Web 3.0. However, it is extremely difficult to excavate the meaning of a target concept from textual data as there is no one-to-one correspondence between the textual unit in which the target concept is embedded and the conceptual content that we would like to excavate. In this paper, we propose one possible approach for addressing this challenge, by...
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