Semantika informacinių technologijų kontekste yra duomenų apdorojimas pagal prasmę ir kontekstą. Tam įgyvendinti yra taikomas natūralios kalbos apdorojimas, pritaikytas informacijos paieškai, išrinkimui, analizavimui.Taikant semantines technologijas, kūrėjams dažnai kyla klausimas, kaip sukurti semantinės paieškos sąsają, kad ji būtų patogi ir duotų kuo tikslesnius atsakymus į vartotojų užklausas. Šiame darbe aprašomas sukurtas metodas, kuris padeda vartotojui palaipsniui formuoti SPARQL užklausą iš atskirų elementų, dinamiškai keičiant vartotojo sąsają. / Increasing popularity of Semantic Web raises a question how we could make a simple user interface for building semantic queries while keeping high precision of results returned. This thesis presents a method that helps users to create SPARQL queries by allowing to dynamically add components to user interface. The goal of the work is to improve of user interface model for semantic queries by allowing users to construct and change it dynamically till obtaining the desirable answer results. That model was created on the base of analysis of Semantic Web languages, tools and existing portals, their functions and user interfaces. Algorithms for dynamic user interface generation based on user actions were developed that allow creating queries of various complexities with minimal amount of user interface components. Implementation and testing the prototype of the system using movie and wine ontologies has shown that dynamic construction and generation of query interface has desirable functionality and is easily applicable to various ontologies. Experimental comparison with existing semantic search portals has shown that the proposed dynamic user interface generation method could improve precision and recall of semantic queries and may be applied in semantic search portal applications.

Data storing semantic technologies separate it from applications code and gives availability for computers as well as people understand and share semantics in real time. These technologies also enable to add new data source or link between software applications as easy as to draw new link in the model. Unfortunately these technologies are yet not developed and popular as we could notice strong benefits of them in daily life. Introduction of semantic search system is an attempt to show the strong points of semantic technologies. Semantic search is more precise because of its opportunities to narrow handled domain down, it gives more exact result than usual, keyword based search. This advantage is clearly shown when database is very large and is filled with plenty of data. It also gives possibility to retrieve results from multiple distant data sources and form custom or predefined result sets as a central hub for some data domain. Automatic ontology generation based on database schema and metadata is suggested in this work. Such solution ensures that semantic search, which uses generated ontology, serves up-to-date search services even when structure of database is changed.