International Journal of Cooperative Information Systems

Ontobroker applies Artificial Intelligence techniques to improve access to heterogeneous, distributed and semi-structured information sources as they are presented in the World Wide Web or organization-wide intranets. It relies on the use of ontologies to annotate web pages, formulate queries and derive answers. In this paper we will briefly sketch Ontobroker. Then we will discuss its main shortcomings, i.e. we will share the lessons we learned from our exercise. We will also show how On2broker overcomes these limitations. Most important is the separation of the query and inference engines and the integration of new web standards like XML and RDF.

PICSEL is an information integration system over sources that are distributed and possibly heterogeneous. The approach which has been chosen in PICSEL is to define an information server as a knowledge-based mediator in which CARIN is used as the core logical formalism to represent both the domain of application and the contents of information sources relevant to that domain. In this paper, we describe the way the expressive power of the CARIN language is exploited in the PICSEL information integration system, while maintaining the decidability of query answering. We illustrate it on examples coming from the tourism domain, which is the first real case that we have to consider in PICSEL, in collaboration with the travel agency Degriftour. see

The World Wide Web is fast becoming a ubiquitous computing environment. Prevalent keyword-based search techniques are scalable, but are incapable of accessing information based on concepts. We investigate the use of concepts from multiple, real-world pre-existing, domain ontologies to describe the underlying data content and support information access at a higher level of abstraction. It is not practical to have a single domain ontology to describe the vast amounts of data on the Web. In fact, we expect multiple ontologies to be used as different world views and present an approach to "browse" ontologies as a paradigm for information access. A critical challenge in this approach is the vocabulary heterogeneity problem. Queries are rewritten using interontology relationships to obtain translations across ontologies. However, some translations may not be semantics preserving, leading to uncertainty or loss in the information retrieved. We present a novel approach for estimating loss of information based on the navigation of ontological terms. We define measures for loss of information based on intensional information as well as on well established metrics like precision and recall based on extensional information. These measures are used to select results having the desired quality of information.

This paper presents a formal framework for the combination of document representations based on evidential reasoning. Each indexing method is modelled by an agent referred to as an indexer. Indexing elements re modelled as sentences which are used to describe the content of a document. The modelling of the indexing and its uncertainty provides the document representation. The combination of document representations is expressed as the combination of the indexing and uncertainty as provided by two or more indexers. The resulting indexer is referred to as the combined indexer. The proposed framework allows the capture of the semantics of the indexing vocabularies associated with the indexers and the aggregation of the uncertainty associated with the indexing.

Requirements for continuing progress in Information Systems usability are surveyed and analyzed.