The effort described in this paper introduces an indexing structure for path search in the graph structured data called rho-index. It is based on a graph segmentation S(G) that is meant to represent the indexed graph G in a simpler manor yet having similar properties as the graph G had. This is achieved using graph transformations and a special type of a matrix used to represent the transformed graph.

This paper presents BOLE — a new platform for bottomup generation and merging of bio-ontologies. In contrast to other ontology-learning systems that are currently available, BOLE can be characterized by the modular architecture enabling integrating and comparing various methods of the automatic acquisition of semantic relations. We introduce the architecture of the tool and discuss the methodology of the employed synthetic bottom-up approach. OLITE — the central component responsible for the automatic acquisition of semantic relations from texts is described in detail. The presented preliminary results prove the efficiency of the implemented framework. We also provide a brief comparative overview of other relevant approaches and outline the future work on representation of uncertain knowledge for bio-ontology merging.

This paper presents OLE — a new platform for bottom-up generation and merging of ontologies. In contrast to other ontology-learning systems that are currently available, OLE can be characterized by the modular architecture enabling integrating and comparing various methods of the automatic acquisition of semantic relations. We introduce the architecture of the tool and discuss the methodology of the employed synthetic bottom-up approach. OLITE — the central component responsible for the automatic acquisition of semantic relations from texts is described in detail. The presented preliminary results prove the efficiency of the implemented framework. We also provide a brief comparative overview of other relevant approaches and outline the future work on representation of uncertain knowledge for ontology merging.

The need of search mechanisms based on data content rather then attributes values has recently lead to formation of the metric-based similarity retrieval. The computational complexity of such retrieval and the large volume of processed data call for distributed processing. In this paper, we propose chiDistance, a distributed data structure for similarity search in metric spaces. The structure is based on the idea of a vectorbased index method iDistance which enables to transform the issue of similarity search into the one-dimensional range search problem. A Peerto-Peer system based on the Chord protocol is created to distribute the storage space and to parallelize the execution of similarity queries. In the experiments conducted on our prototype implementation we study the system performance concentrating on several aspects of parallelism of the range search algorithm.

This paper describes the exhaustive results obtained within IST 290388 Project Balkanet, which went on 2001-2004. The attention is paid to the restructuring and final shaping the individual Balkan WordNets. In comparison with the EuroWordNet Project some new results have been obtained: The sets of Base Concepts have been extended and a set of the Balkanet 1. Common Synsets has been introduced (8,000 synsets). These were relinked to Princeton WordNet 2.0 (PWN) and converted to XML standard format, 2. The language specific synsets that do not have translation equivalents in PWN 2.0 have been established for Balkanet languages, 3. Valency frames have been developed for Czech, Bulgarian and Romanian, 4. Domains have been added to Balkanet WordNets and implemented in the VisDic browser, 5. Integrating derivational relations into Czech WordNet and adding semantic relations into Turkish WordNet exploiting Turkish derivational morphology, 6. Links to the SUMO/MILO Ontology were added to and implemented in VisDic.