Ontology Creation Process in Knowledge Management Support System for a Research Institute

Though the issue of knowledge management is a hot subject of interest in nowadays market companies, integrated solutions fit to the specific needs of research institutes still require more attention. This paper documents a part of the research activities performed at National Institute of Telecommunications, related to development of research institute knowledge management support system. The ideas lying in the background of the system come from the recent theories of knowledge creation and creativity support and from experience with everyday practice of knowledge management in market companies. Main focus is put here on the issue of creation of a research topics ontology that is meant to be a semantic backbone of the system. Three-stage approach is proposed, aiming at the construction of ontologies for different levels of organizational hierarchy, from individual researcher, through group or unit, up to the whole institute. Created ontologies are linked to knowledge resources and support diverse activities performed at those levels

Personal Ontologies for Knowledge Acquisition and Sharing in Collaborative PrOnto Framework

This paper summarizes our preliminary experiences with implementing some of the ideas lying behind the concept of creative environment. Research group at the National Institute of Telecommunications has developed a prototype framework for collaborative knowledge acquisition and sharing, called PrOnto. At the moment the artifacts we organize and share are typical sources of scientific knowledge, namely journal papers and web pages. In PrOnto we introduce two interrelated explicit levels of knowledge representation: keywords and ontological concepts. Each user of the framework maintains his own ontological profile, consisting of concepts and each concept is, in turn, by subjective user's decision, related to a set of weighted keywords that define its meaning. Furthermore, dedicated indexing engine is responsible for objectively establishing correspondence between documents and keywords, or in other words, the measure of representativeness of the keyword to document's content. Developing an appropriate knowledge model is a preliminary step to share it efficiently. We believe that higher level representation facilitates exploration of other people's areas of interest. PrOnto gives an opportunity to browse knowledge artifacts from the conceptual point of view of any user registered in the system. The paper presents the ideas behind the PrOnto framework, gives an outline of its components and finalizes with a number of conclusions and proposals for futuren enhancements

Wykrywanie wiedzy w dużych zbiorach danych: przykład personalizacji inżynierii ontologicznej

W artykule, po przedyskutowaniu szeroko rozumianego pojęcia inżynierii wiedzy, a w szczególności inżynierii ontologicznej, koncentrującej się na wykrywaniu wiedzy w dużych zbiorach tekstu, omówiono rezultaty prac wykonanych w Instytucie Łączności PIB w ramach projektu badawczego zamawianego "Usługi i sieci teleinformatyczne następnej generacji - aspekty techniczne, aplikacyjne i rynkowe". Prace wstępne i rozpoznawcze doprowadziły do sformułowania założenia na przyjazny, spersonalizowany system wspomagania wyszukiwania wiedzy w dużych zbiorach tekstu. Efektem końcowym zaś jest pilotowy system PrOnto wykorzystujący narzędzia inżynierii ontologicznej w dwóch aspektach: jednym - wspomagającym wyszukiwanie informacji w dokumentach elektronicznych na podstawie osobistej ontologii użytkownika i drugim - wspomagającym współdzielenie źródeł wiedzy przy wykorzystaniu modeli ontologicznych. Artykuł kończą wnioski co do stosowalności różnych metod wykorzystania narzędzi inżynierii ontologicznej oraz sposobów kontynuacji prac

Personalized Knowledge Mining in Large Text Sets

The paper starts with a discussion of the concept of knowledge engineering, in particular ontological engineering. Consequently, the paper presents assumptions accepted as a basis for a group research on a radically personalized system of ontological knowledge mining, relying on the perspective of human centered computing and combining ontological concepts of the user with an ontology resulting from an automatic classification of a given set of textual data. The paper presents a pilot system PrOnto that supports research work in two aspects: searching for information interesting for a user according to her/his personalized ontological profile, and supporting research cooperation in a group of users (Virtual Research Community) according, e.g., to a comparison of such personalized ontological profiles. The paper concludes with suggestions concerning diverse applications of ontological engineering tools and future work

The Savings Motives: With Special Reference to Households in Kalutara District

AbstractThe household saving is a decision which is taken by the people to postpone their consumption of current income. Savings can be considered as one of the crucial tools which households utilized to accomplish their financial expectations in order to improve their financial wellbeing. There are many ways of accumulating or investing money, which can be identified as the deposits in bank accounts or building society accounts to saving in pensions, save in credit unions, invest in the stock market and many other saving sources. This study is an inspection of saving motives of Sri Lankan household in present economic situation. Briefly it can be explained, the harvest of the research will provid the answer to the question of what is the most significantly affected saving motive which stimulate/ encourage people to save money? And it will be further declared how do these saving motives vary when household characteristics differ? As a conclusion it can be stated that this study is seeking answers for why do people save money in a broader sense (Research Problem). And the answer for, of what is the most significantly affected saving motive to stimulate people, for savings? The main purpose of this paper is to examine the most significant savings motive among households in Kalutara District. Data were collected through questionnaires by using hundred respondents. The factor analysis is explored to examine, what is the most significant savings motive among pre-determined savings motives of bequest, precautionary and life cycle using SPSS 17. It has been identified the most significant savings motive of households in Kalutara district is the precautionary savings motiveKeywords: Savings Behavior, Savings Motives, Factor Analysi