Abstract. During the last few years, a number of works aiming at interfacing ontologies and lexical resources have been initiated. This paper aims at clarifying the current picture of this domain. It compares ontologies built following different methodologies and analyses their combination with lexical resources. A point defended in the paper is that different methodologies lead to very different characteristics for the resulting systems. We classify these methodologies and show how actual projects fit into this classification. We also take a more applicative viewpoint by presenting a PROTÉGÉ-based platform that can be exploited in the general task of interfacing ontologies and lexical resources along the different methodological lines. 1

In this paper we describe first results of our research on the disambiguation of user queries using ontologies for categorization. We present an approach to cluster search results by using classes or ‘Sense Folders’ (prototype categories) derived from the concepts of an assigned ontology, here Multi-WordNet. Using the semantic relations provided from such a resource, we can assign categories to prior not annotated documents and thus help the user in

The problem of word sense disambiguation in lexical resources is one of the most important tasks in order to recognize and disambiguate the most significant word senses of a term. Lexicographers have to decide how to structure information in order to describe the world in an objective way. However, the introduced distinctions between word meanings are very often too fine grained for specific applications. If we want to use or even combine lexical resources within information retrieval systems, for example, we might want to apply the lexical resources in order to disambiguate documents (retrieved from the web within an information retrieval system) given the different meanings (retrieved from lexical resources) of a search term having unambiguous description. Therefore, we are usually interested in a small list of meanings with very distinctive features. Since many lexical resources, especially WordNet, provide frequently too fine grained word sense distinctions, we implemented the tool LexiRes that gives the possibility to navigate lexical information, helping authors of already available lexical resources in deleting or restructuring concepts using automatic merging methods.

In this paper, we explore an architecture, called K-Trek, that enables mobile users to travel across knowledge distributed over a large geographical area (ranging from large public buildings to a national park). Our aim is providing, distributing, and enriching the environment with location-sensitive information for use by agents on board of mobile and static devices. Local interactions among KTrek devices and the distribution of information in the larger environment adopt some typical peer-to-peer patterns and techniques. We introduce the architecture, discuss some of its potential knowledge management applications, and present a few experimental results obtained with simulation.

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The emergence and growth of the Internet and vast corporate intranets as information sources has resulted in new challenges with regard to scale, heterogeneity, and distribution of content. Semantics is emerging as the critical tool for enabling more scalable and automated approaches to achieve interoperability and analysis of such content. This chapter discusses how a Semantic Enterprise Content Management system employs metadata and ontologies to effectively overcome these challenges.

The discipline of knowledge engineering grew out of the early work on expert systems in the seventies. With the growing popularity of knowledge-based systems (as these were by then called), there arose also a need for a systematic approach for building such systems, similar to methodologies in main-stream software engineering. Over the years, the