The current World Wide Web is a web of pages. Users have to guess possible keywords that might lead through search engines to the pages that contain information of interest and browse hundreds or even thousands of the returned pages in order to obtain what they want. This frustrating problem motivates an approach to turn the web of pages into a web of knowledge, so that web users can query the information of interest directly. This dissertation provides a step in this direction and a way to partially overcome the challenges. Specifically, this dissertation shows how to turn machine-generated web pages like those on the hidden web into semantic web pages for the web of knowledge. We design and develop three systems to address the challenge of turning the web pages into web-of-knowledge pages: TISP (Table Interpretation for Sibling Pages), TISP++, and FOCIH (Form-based Ontology Creation and Information Harvesting). TISP can automatically interpret hidden-web tables. Given interpreted tables, TISP++ can generate ontologies and semantically annotate the information present in the interpreted tables automatically. This way, we can offer a way to make the hidden information publicly accessible. We also provide users with a way where they can generate personalized ontologies. FOCIH provides users with an interface with which they can provide their own view by creating a form that specifies the information they want. Based on the form, FOCIH can generate user-specific ontologies, and based on patterns in machine-generated pages, FOCIH can harvest information and annotate these pages with respect to the generated ontology. Users can directly query on the annotated information. With these contributions, this dissertation serves as a foundational pillar for turning the current web of pages into a web of knowledge.

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.