Problem statement: Currently advertising networks connects Web site owners (Publishers) that want to host advertisements with advertisers who want to run advertisements. Advertising networks' reliance on only the keywords in the content without an accurate interpretation of the context of the page, results in displaying irrelevant and unappealing ads on the web page. Approach: Ontologies provided a shared and common understanding of a domain that can be communicated between people and across application systems. Our objective was to create a domain-dependent Ontology to play a major role in supporting information exchange processes in semantic advertising networks. Results: Results for the prototype of matching ads with publishers had been presented in terms of precision and recall. High precision was shown and analysis of results was given in detail. Conclusion: The proposed Ontology is effective for advertising networks at a semantic level.

Semantic indexing of a video document is a process that performs the identification of elementary and complex semantic units in the indexed document in order to create a semantic index defined as a mapping of semantic units into the sequences of video frames. Semantic content-based video retrieval system is a software system that uses a semantic index built over a collection of video documents to retrieve the sequences of video frames that satisfy the given conditions. This work introduces a new multilevel view of data for the semantic content-based video retrieval systems. At the topmost level, we define an abstract view of data and we express it in a notation of enhanced conceptual modeling suitable for the formal representation of the semantic contents of video documents. A semistructured data model is proposed for the middle level representation of data. At the bottom level we implement a semistructured data model as an object-relational database. The completeness of the proposed approach is demonstrated through the mappings of a conceptual level into a semistructured level and into an object-relational organization of data. The paper describes a system of operations on semistructured data and shows how a sample query can be represented as an expression built from the operations.