In this paper, we tackle the issues of analyzing the struc- tural evolution of the metric social network. The metric social network operates in a P2P environment where peers maintain their own data and the relationships among them are formed on the basis of the pro- cessed similarity queries. The evolution is analyzed by traditional social networking tools the characteristic path length and the clustering co- efficient. Nonetheless, due to the special structure of the metric social network, own designed gauges the average overlap and robustness of description coefficients are presented to analyze the structure of emerg- ing communities encompassing similar data.

The similarity search has become a fundamental computational task in many applications. One of the mathematical models of the similarity the metric space has drawn attention of many researchers resulting in several sophisticated metric-indexing techniques. An important part of a research in this area is typically a prototype implementation and subsequent experimental evaluation of the proposed data structure. This paper describes an implementation framework called MESSIF that eases the task of building such prototypes. It provides a number of modules from basic storage management to automatic collecting of performance statistics. Due to its open and modular design it is also easy to implement additional modules if necessary. The MESSIF also offers several ready-to-use generic clients that allow to control and test the index structures and also measure its performance.

This paper examines some issues involved in building a corpus-based ontology for use in determining the meaning of words in text, in the context of creating a “pattern dictionary”. How do words cluster in paradigmatic lexical sets in actual usage (as reflected in a large corpus), and can these clusters be mapped onto a semantically structured ontology? What semantic notions need to be distinguished for this purpose, and what are the appropriate theoretical foundations? What other elements are needed for the application of determining meaning in text?

In the paper we deal with the derivational relations in Czech that form typical derivational nests (or subnets). Derivational relations are mostly of semantic nature and their regularity in Czech allows us to describe them in a way suitable for computer processing and then add them to the electronic databases such as WordNet almost automatically. For this purpose we have used the derivational version of morphological analyzer Ajka that is able to handle the basic and most productive derivational relations in Czech. A special derivational interface has been developed in our NLP Lab at FI MU by means of which we have explored the semantic nature of the selected noun derivational suffixes (22) as well as verb prefixes and established a set of the semantically labeled derivational relations, presently 14. With regard to the verbs we have paid attention to the selected verb semantic classes in connection with the derivational relations between selected prefixes (4) and corresponding Czech verbs. As an application we have added the selected derivational relations to the Czech WordNet and in this way enriched it with approx. 30 000 new Czech synsets.

This paper presents a new implementation of administration framework for the DEBII dictionary writing system. We present the details and examples of the user management part as well as graphical scenarios for dictionary service setup, adaptation and automatic generation of user application based on the dictionary XML schema. Tento článek představuje novou implementaci administračního rozhraní systému pro tvorbu slovníků DEBII. V článku je podrobně popsán systém správy uživatelů a také grafikou doplněný postup vytvoření nového slovníku, jeho přizpůsobení a automatické generování uživatelské aplikace pomocí XML schématu slovníku.

In this paper, we summarize the latest development regarding the client dictionary writing applications based on the DEB development platform. The DEB framework is nowadays used in several full grown projects for preparation of high quality lexicographic data created within (possibly distant) teams of researchers. We briefly present the current list of DEB applications with the relevant projects and their phases. For each of the applications, we offer display the view of the interface with overview description of the most important features.

In the paper, we introduce new dictionary management interface for design, preparation and presentation of generic electronic XML dictionaries using the DEB (Dictionary Editing and Browsing) development platform. The DEB platform provides a strict client-server environment for general dictionary writing systems. So far several successful NLP tools have been implemented on this platform, one of the most known being the DEBVisDic tool for wordnet semantic network editing and visualization. This paper describes a new part of the DEB platform -- the Administration interface that is shared by all DEB applications running on one server machine. Článek představuje nové rozhraní pro správu slovníků, které umožňuje návrh, přípravu a prezentaci obecných elektronických slovníků ve formátu XML s použitím vývojové platformy DEB (Dictionary Editing and Browsing). Platforma DEB poskytuje prostředí v architektuře klient-server pro obecné systémy pro vytváření slovníků. V současné době bylo na této platformě implementováno několik úspěšných NLP nástrojů, nejznámnější je nástroj DEBVisDic pro editaci a vizualizaci sémantických sítí typu wordnet. Tento článek popisuje novou součást platformy DEB -- administrační rozhraní, které sdílí všechny DEB aplikace spuštěné na jednom serveru.

In the paper, we present the results of an experiment with comparing the effectiveness of real text parsers of Czech language based on completely different approaches stochastic parsers that provide dependency trees as their outputs and a meta-grammar parser that generates a resulting chart structure representing a packed forest of phrasal derivation trees. We describe and formulate main questions and problems accompanying such experiment, try to offer answers to these questions and finally display also factual results of the tests measured on 10 thousand Czech sentences.

In the paper, we present the beautified chart method used for reducing the number of output derivation trees for the Czech syntax parser synt. We show the evaluation results of the method, describe the appropriate algorithms and the parser internal data structures as well as problems with their implementation. Článek popisuje metodu beautified chart pro omezení počtu výstupních derivačních stromů syntaktického analyzátoru češtiny synt. Je popsána naměřená úspěšnost metody, příslušné algoritmy, datové struktury a některé problémy při implementaci.

Exploiting the concepts of social networking represents a novel approach to the approximate similarity query processing. We present an unstructured and dynamic P2P environment in which a metric social network is built. Social communities of peers giving similar results to specific queries are established and such ties are exploited for answering future queries. Based on the universal law of generalization, a new query forwarding algorithmis introduced and evaluated. The same principle is used to manage query histories of individual peers with the possibility to tune the tradeoff between the extent of the history and the level of the queryanswer approximation. All proposed algorithms are tested on real data and medium-sized P2P networks consisting of tens of computers.

In this paper we tackle the issues of exploiting the concepts of social networking in processing similarity queries in the environment of a P2P network. The processed similarity queries are laying the base on which the relationships among peers are created. Consequently, the communities encompassing similar data emerge in the network. The architecture of the presented metric social network is formally defined using the acquaintance and friendship relations. Two version of the navigation algorithm are presented and thoroughly experimentally evaluated. Finally, learning ability of the metric social network is presented and discussed.

Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm. Similarity searching has become afundamental computational task in a variety of application areas, including multimedia information retrieval, data mining, pattern recognition, machine learning, computer vision, biomedical databases, data compression and statistical data analysis. In such environments, an exact match has little meaning, and proximity/distance (similarity/dissimilarity) concepts are typically much more fruitful for searching. In this tutorial, we review the state of the art in developing similarity search mechanisms that accept the metric space paradigm. We explain the high extensibility of the metric space approach and demonstrate its capability with examples of distance functions. The efforts to further speed up retrieval are demonstrated by a class of approximated techniques and the very recent proposals of scalable and distributed structures based on the P2P communication paradigm.