Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In our view of Information Retrieval on the Semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, our approach includes an ontology-based scheme for the semiautomatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. Experiments are shown where our approach is tested on corpora of significant scale, showing clear improvements with respect to keyword-based search.

In this paper, we describe a Semantic Web application that detects Conflict of Interest (COI) relationships among potential reviewers and authors of scientific papers. This application discovers various ‘semantic associations ’ between the reviewers and authors in a populated ontology to determine a degree of Conflict of Interest. This ontology was created by integrating entities and relationships from two social networks, namely “knows, ” from a FOAF (Friend-of-a-Friend) social network and “co-author, ” from the underlying co-authorship network of the DBLP bibliography. We describe our experiences developing this application in the context of a class of Semantic Web applications, which have important research and engineering challenges in common. In addition, we present an evaluation of our approach for real-life COI detection.

Abstract. Precisely identifying entities in web documents is essential for document indexing, web search and data integration. Entity disambiguation is the challenge of determining the correct entity out of various candidate entities. Our novel method utilizes background knowledge in the form of a populated ontology. Additionally, it does not rely on the existence of any structure in a document or the appearance of data items that can provide strong evidence, such as email addresses, for disambiguating person names. Originality of our method is demonstrated in the way it uses different relationships in a document as well as from the ontology to provide clues in determining the correct entity. We demonstrate the applicability of our method by disambiguating names of researchers appearing in a collection of DBWorld posts using a large scale, realworld ontology extracted from the DBLP bibliography website. The precision and recall measurements provide encouraging results. Keywords: Entity disambiguation, ontology, semantic web, DBLP, DBWorld. 1

The emergent Semantic Web community needs a common infrastructure for testing the scalability and quality of new techniques and software which use machine processable data. Since ontologies are a centerpiece of most approaches , we believe that for an accurate evaluation of tools for quality, scalability and performance, the research community needs a freely available ontology with a large description base. If the use of tools is to be for advanced semantic applications, such as those in business intelligence and national security, then instances in the knowledge base should be highly interconnected. Thus, we propose and describe a Semantic WEb Technology evaluation Ontology (SWETO) test-bed. In particular, we address the requirements of a test-bed to support research in semantic analytics , as well as the steps in its development, including, ontology creation, semi-automatic data extraction, and entity disambiguation.

Information retrieval over semantic metadata has recently received a great amount of interest in both industry and academia. In particular, discovering complex and meaningful relationships among this data is becoming an active research topic. Just as ranking of documents is a critical component of today's search engines, the ranking of relationships will be essential in tomorrow's semantic analytics engines. Building upon our recent work on specifying these semantic relationships, which we refer to as Semantic Associations, we demonstrate a system where these associations are discovered among a large semantic metabase represented in RDF. Additionally we employ ranking techniques to provide users with the most interesting and relevant results.

Abstract. The semantic web represents a major advance in web utility, but it is difficult to create semantic-web content because pages must be semantically annotated through processes that are mostly manual and require a high degree of engineering skill. Furthermore, users need an effective way to query the semantic web, but any burden we place on users to learn a query language is unlikely to garner sufficient user support and interest. If we want users to take advantage of the semantic web, we must devise a means for transforming existing (non-semantic) web pages into semantic web pages, and we must provide a simple and unrestricted interface for processing user queries. We propose using information extraction ontologies to handle both of these challenges. We show how a successful ontology-based data-extraction technique can (1) automatically generate semantic annotations for ordinary web pages, and (2) support free-form, textual queries. Our approach demonstrates how the semanticwebcanbecreatedforandusedbyordinarypeople.Wehave created an initial prototype to demonstrate that our proposal works.

Abstract. Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontologybased KBs to improve search over large document repositories. Our approach includes an ontology-based scheme for the semi-automatic annotation of documents, and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. Our proposal is illustrated with sample experiments showing improvements with respect to keyword-based search, and providing ground for further research and discussion. 1

Semantic Portal is the next generation of web portals that are powered by Semantic Web technologies for improved information sharing and exchange for a community of users. Current methods of searching in Semantic Portals are limited to keyword-based search using information retrieval (IR) techniques, ontology-based formal query and reasoning, or a simple combination of the two. In this paper, we propose an enhanced model that tightly integrates IR with formal query and reasoning to fully utilize both textual and semantic information for searching in Semantic Portals. The model extends the search capabilities of existing methods and can answer more complex search requests. The ideas in a fuzzy description logic (DL) IR model and a formal DL query method are employed and combined in our model. Based on the model, a semantic search service is implemented and evaluated. The evaluation shows very large improvements over existing methods.

Abstract. Verification of legitimate access of documents, which is one aspect of the umbrella of problems in the Insider Threat category, is a challenging problem. This paper describes the research and prototyping of a system that takes an ontological approach, and is primarily targeted for use by the intelligence community. Our approach utilizes the notion of semantic associations and their discovery among a collection of heterogeneous documents. We highlight our contributions in (graphically) capturing the scope of the investigation assignment of an intelligence analyst by referring to classes and relationships of an ontology; in computing a measure of the relevance of documents accessed by an analyst with respect to his/her assignment; and by describing the components of our system that have provided early yet promising results, and which will be further evaluated more extensively based on domain experts and sponsor inputs. 1.

The concept of automating Web services, specifically the brokering activities, is an active research topic. We need a comprehensive and overarching framework that handles the discovery, differentiation, negotiation and selection processing within the context of workflow management, and addresses the issues related to Virtual Organizations. The goal is to add semantics to Web services to endow them with capabilities currently lacking in the literature, but necessary for their successful deployment in future systems. This paper references how such a framework, called the KDSWS Framework, addresses in an integrated endto-end manner, the life-cycle of activities involved in brokering and managing Semantic Web Services. The following issues are addressed: semantic specification of services ’ capabilities; brokering the services, workflow management, resource management, interoperation and evolution of the Virtual Organization. 1.