The Semantic Web is not widespread as it has been expected by its founders. This is partially caused by lack of standard and working infrastructure for the Semantic Web. We have built a working, portable, stable, highperformance infrastructure for the Semantic Web. This paper is focused on tasks performed by the infrastructure.

The Semantic Web is not widespread as it has been expected by its founders. This is partially caused by lack of standard and working infrastructure for the Semantic Web. We have built a working, portable, stable, high-performance infrastructure for the Semantic Web. This enables various experiments with the Semantic Web in the real world.

Uncertainty querying of large data can be solved by providing top-k answers according to a user fuzzy ranking/scoring function. Usually different users have different fuzzy scoring function a user preference model. Main goal of this paper is to assign a user a preference model automatically. To achieve this we decompose user’s fuzzy ranking function to ordering of particular attributes and to a combination function. To solve the problem of automatic assignment of user model we design two algorithms, one for learning user preference on particular attribute and second for learning the combination function. Methods were integrated into a Fagin-like top-k querying system with some new heuristics and tested.

User preferences became recently a hot topic. The massive use of internet shops and social webs require the presence of a user modelling, which helps users to orient them selfs on a page. There are many different approaches to model user preferences. In this paper, we will overview the current state-of-the-art in the area of acquisition of user preferences and their induction. Main focus will be on the models of user preferences and on the induction of these models, but also the process of extracting preferences from the user behaviour will be studied. We will also present our contribution to the probabilistic user models.

We discuss models of user preferences in Web environment. We construct a model for user preference querying over a number of data sources and ordering of answers by a combination of particular attribute rankings. We generalize Fagin's algorithm in two directions - we develop some new heuristics for top-k search in the model without random access and propose a method of ordering lists of objects by user fuzzy function. To enable different user preferences our system does not require objects to be sorted - instead we use a B+- tree on each of the attribute domains. This leads to a more realistic model of Web services. We implement our methods and heuristics for search of top-k answers into Tokaf middleware framework prototype. We describe experiments with Tokaf and compare different performance measures with some other methods.

Web search heuristics based on Fagin’s threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering .

EGOTHOR is a search engine that indexes the Web and allows us to search the Web documents. Its hit list contains URL and title of the hits, and also some snippet which tries to shortly show a match. The snippet can be almost always assembled by an algorithm that has a full knowledge of the original document (mostly HTML page). It implies that the search engine is required to store the full text of the documents as a part of the index. Such a requirement leads us to pick up an appropriate compression algorithm which would reduce the space demand. One of the solutions could be some use of common compression methods, for instance gzip or bzip2, but it might be preferable to develop a new method which would take advantage of the document structure, or rather, the textual character of the documents. There already exist special compression text algorithms and methods for a compression of XML documents. The aim of this paper is an integration of the two approaches to achieve an optimal level of the compression ratio.

Syllable based text compression is a new approach to compression by symbols. In this concept syllables are used as the compression symbols instead of the more common characters or words. This new technique has proven itself worthy especially on short to middle-length text files. The effectiveness of the compression is greatly affected by the quality of dictionaries of syllables characteristic for the certain language. These dictionaries are usually created with a straight-forward analysis of text corpora. In this paper we would like to introduce an other way of obtaining these dictionaries using genetic algorithm. We believe, that dictionaries built this way, may help us lower the compress ratio. We will measure this effect on a set of Czech and English texts.

The Burrows-Wheeler Transform (BWT) is a compression method which reorders an input string into the form, which is preferable to another compression. Usually Move-To-Front transform and then Huffman coding is used to the permutated string. The original method [3] from 1994 was designed for an alphabet compression. In 2001, versions working with word and n-grams alphabet were presented. The newest version copes with the syllable alphabet [7]. The goal of this article is to compare the BWT compression working with alphabet of letters, syllables, words, 3-grams and 5-grams.

A key point in modern automated data processing is metadata semantics representation. Employing Semantic Web existing features - ontologies - is a promising option. Ontologies open a novel approach to knowledge representation. The paper presents a GIS (Geographic Information System) domain application illustrating ontological approach to data integration and data processing automation in the specific system. This VirGIS system is an integration system that works with spatio-temporal data. We start our study with developing the data representation based on common Semantic Web techniques and build a VirGIS ontology.

Data integration usually provides a unified global view over several data sources. A crucial part of the task is the establishment of the connection between the global view and the local sources. For this purpose, two basic mapping approaches have been proposed: GAV (Global As View) and LAV (Local As View). On the Semantic Web, there can be considered also an ontological approach. In this paper, data integration is solved using ontologies of the sources. To express relationships between the global view and local source schemas, an ontology for the integration system is built. Thus, a schema integration task is transformed to an ontology merging task.

The paper deals with one step of non-materialized data integration - schema matching task. It works with data sources on the Semantic Web; the crucial assumption for the considered task is available ontologies describing data to integrate. Source ontologies are used to find correspondences between source schemas elements. For this, also techniques known from ontology alignment and ontology merging field are used.

Článek se zabývá úlohami, které je třeba řešit při nematerializované integraci dat. Zaměřuje se na hledání korespondencí mezi schématy a mapování schémat. Návrh přístupu řešení těchto úloh na Sémantickém webu těží z dostupných ontologiích popisujících integrované zdroje. Ontologie jsou využity jak k hledání mapování, tak i při jejich popisu.

As XML has undoubtedly become a standard for data representation, it is inevitable to propose and implement techniques for efficient managing of XML data. A natural alternative is to exploit features and functions of (object-)relational database systems, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an appropriate XML-to-relational mapping strategy. In this paper we focus on enhancing of user-driven techniques which leave the mapping decisions in hands of users. We propose an algorithm which exploits the user-given annotations more deeply searching the user-specified "hints" in the rest of the schema and applies an adaptive method on the remaining schema fragments. We describe the proposed algorithm, the similarity measure designed for this purpose, sample implementation of key features of the proposal called UserMap, and results of experimental testing on real XML data.

As the XML has become a standard for data representation, it is inevitable to propose and implement techniques for efficient managing of XML data. A natural alternative is to exploit features of (object-)relational database systems, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an appropriate XML-to-relational mapping strategy. In this paper we focus on enhancing of user-driven techniques which leave the mapping decisions in hands of users who specify their requirements using schema annotations.We describe our prototype implementation called UserMap which is able to exploit the annotations more deeply searching the user-specified “hints” in the rest of the schema and applies an adaptive method on the remaining schema fragments. Using a sample set of supported fixed mapping methods we discuss problems related to query evaluation for storage strategies generated by the system, in particular correction of the candidate set of annotations and related query translation. And finally, we describe the architecture of the whole system.

We propose a new conceptual model for XML data called XSEM as a combination of several approaches in the area of the conceptual modeling for XML. The model divides the conceptual modeling process of XML data to two levels. On the first level, a designer designs an overall non-hierarchical conceptual schema of a domain. On the second level, he or she derives different hierarchical representations of parts of the overall conceptual schema using transformation op- erators. These hierarchical representations describe how the data is organized in an XML form.

In this paper we briefly describe a new conceptual model for XML data called XSEM and how to use it for modeling XML interfaces of services in service oriented architecture (SOA). The model is a combination of several approaches in the area of conceptual modeling of XML data. It divides the process of conceptual modeling of XML data to two levels. The first level consists of designing an overall non-hierarchical conceptual schema of the domain. The second level consists of deriving different hierarchical representations of parts of the overall conceptual schema using transformation operators. Each hierarchical representation models an XML schema describing the structure of the data exchanged between a service interface and external services.

The paper resumes recent advances in the field of logic of preference and presents their application in the field of database queries. Namely, non-monotonic reasoning mechanisms including various kinds of preferences are reviewed, and a way of suiting them to practical database applications is shown: reasoning including sixteen strict and non-strict kinds of preferences, inclusive of ceteris paribus preferences, is feasible. However, to make the mechanisms useful for practical applications, the assumption of preference specification consistency has to be relinquished. This is achieved in two steps: firstly, all the kinds of preferences are de- fined so that some uncertainty is inherent, and secondly, not a notion of a total pre-order but a partial pre-order is used in the semantics, which enables to indicate some kind of conflict among preferences. Most importantly, the semantics of a set of preferences is related to that of a disjunctive logic program.

The paper resumes a logical framework for formulating preferences and proposes their embedding into relational algebra through a single preference operator parameterized by a set of user preferences of sixteen various kinds, inclusive of ceteris paribus preferences, and returning only the most preferred subsets of its argument relation. Most importantly, conflicting set of preferences is permitted and preferences between sets of elements can be expressed. Formal foundation for algebraic optimization, applying heuristics like push preference, also is provided: abstract properties of the preference operator and a variety of algebraic laws describing its interaction with other relational algebra operators are presented.

The paper compares features of learning and querying process in the situation, when values in the input data set are annotated by attributes or this information is not available. The attribute annotation enables to consider global relationships, which are useful to express the data semantics in a explicit way. It will be shown data can be accessed with no semantic interpretation and then, after the evaluation process, the result can be interpreted.

Machine learning methods can be seen as an optimalisation task reducing differences between an expected and returned result on a given data set. A corresponding knowledge base can be expressed in many ways, for example, by a binary predicate formalism. The talk deals with a minimalisation of predicate ammount in such a repository, which is enabled by a transitivity. The transitive reduction algorithm will be detaily given for an incremental (attribute annotated data driven) building of a knowledge base; a base model with higher expressiveness will be prefered. Finally, an effect of the selected model to estimated explicit semantic definitions of symbols (internal base interpretation) will be mentioned as well.

Přıspěvek se zabývá aspekty optimalizace paměťových nároků binárního úložiště atributově anotovaných dat na základě transitivní redukce zobecněného systému funkčních závislostí. Tento systém buď může být předem daný modelem, v tomto případě se ukazuje, že je možné optimalizaci použít jednorázově; a nebo tento model je inkremetálním způsobem odhadován a pak se ukazuje vhodným pouze již jednou naoptimalizované úložiště pouze upravovat opět inkrementálním způsobem. V poslední sekci se příspěvek zaobírá rozborem nejednoznačnosti výsledku včetně detailního rozboru vlastností základních konfigurací částí modelu způsobující tuto nejednoznačnost. V neposlední řadě je analyzována složitost dílčích operací v úložišti.

Cílem příspěvku je předložit vizi nových přístupů pro sdílení a vyhledávání dat na internetu. Opírá se o prověřené technologie pracující nad textovými webovými dokumenty a propojuje je se sémantickým webem, moderním prostředkem pro výměnu dat a aktuálními trendy ve vývoji internetu jako celku.

The vision of the semantic web as a distributed and trusted environment for data sharing together with related issues are presented. The paper brings a basic binary matrix formalism for the internal representation of sources and shows the clasical issues as a data inconsistency and a data integration. Aspects of these issues lead to the binary formalism to be generalised into the <0,1> interval one to enable the consideration of uncertainty at various level. Finally, the need of a source trust definition is presented and discussed with respect to a semantic web.

The paper describes a new approach for treating trust in reconfigurable groups of users with special accent on trust in the next generations of the Internet. The proposed model uses properties of weighted hypergraphs. Model flexibility enables description of relations between nodes such that these relations are preserved under frequent changes. The ideas can be straightforwardly generalized to other concepts describable by weighted hypergraphs. The consistency of the proposal was verified in a couple of experiments with our pilot implementation SecGRID.

The paper presents the BlueGame project an ad-hoc multiplayer mobile game based on the Dungeons&Dragons board game. The main idea lies in the adoption of Bluetooth Piconet configuration and direct face to face contact of players in real environments.

Internet je ohromným zdrojem provázaných, ale většinou neuspořádaných dat. Sémantický web, jako rozšíření webu současného, se snaží tuto neuspořádanost řešit a to nejen bezprostředně pro lidského uživatele, ale zejména z hlediska možnosti strojového zpracování informací. Cílem je doplnit data o metadata, která mají být srozumitelná jak pro člověka, tak pro počítač. Tato metadata jsou nejčastěji vyjádřena pomocí ontologií, které jsou jedním ze základních stavebních prvků sémantického webu. V příspěvku se snažím nastínit některé z možností integrace (slučování) ontologií za účelem sdílení informací.

Amorphous computing differs from the classical ideas about computations almost in every aspect. The architecture of amorphous computers is random, since they consist of a plethora of identical computational units spread randomly over a given area. Within a limited radius the units can communicate wirelessly with their neighbors via a single-channel radio. We consider a model whose assumptions on the underlying computing and communication abilities are among the weakest possible: all computational units are finite state probabilistic automata working asynchronously, there is no broadcasting collision detection mechanism and no network addresses. We show that under reasonable probabilistic assumptions such amorphous computing systems can possess universal computing power with a high probability. The underlying theory makes use of properties of random graphs and that of probabilistic analysis of algorithms. To the best of our knowledge this is the first result showing the universality of such computing systems.