Knowledge Representation and the Semantic Web

Google TechTalks
January 25, 2006

Peter Patel-Schneider
http://www-db.research.bell-labs.com/user/pfps/

ABSTRACT
The Semantic Web has been attracting considerable attention the last few years. From the point of view of Knowledge Representation, the Semantic Web affords opportunities for both research and application.

However, several aspects of the Semantic Web, as it has been envisioned, cause problems from the Knowledge Representation viewpoint. Overcoming some of these problems has resulted in a more formal basis for the Semantic Web and an increase in expressive power in Semantic Web languages.

 

Optimize visual image search for semantic web

Abstract: In today’s web image search engines find more irrelevances in the search result. By adding semantic meaning to the document this irrelevance can be reduced. SIEVE image search algorithm combine the text based and content based method and shows the result. Also “IN-Picture” search algorithm mixing the images higher level and lower level contents. In this paper it shows some image searching framework like “SAFE” describe how image are searched using its attributes. Also describes some semantic web technology, which helps in image search and shows how detailed indexing system can use SPARQL query and ontology of an image to build semantic web based framework.

View Full Paper : ijcsit_survey optimize visual image search for semantic web (size 375 KB)

 

Optimizing Query execution over Linked Data

Abstract Linked open data also known as web of linked data is a globally distributed database. The four fold increase in the use of linked open data shows its need in the future. This linked data can be queried with SPARQL protocol and RDF query language also known as SPARQL. Various optimization techniques have been proposed but just a couple implemented as yet. In this paper two most feasible query optimization methods are proposed. Solution one is applying federation and query rewriting. Solution two is expressing the RDF structure as a context graph and pruning intermediate results based on probability or selectivity of the result. The paper gives a brief understanding for both solutions.

View Full Paper: IJETAE_Optimizing Query execution over Linked Data (size 354 KB)

SEMANTIC WEB and COMPARATIVE ANALYSIS of INFERENCE ENGINES

Abstract Semantic Web is an emerging technology for efficient reasoning support over the knowledge represented on the Web. This paper presents the semantic web standards and survey a number of Inference Engines that supports reasoning with OWL. Also analyzed the reasoner with set of ontologies and based on supported features.

View Full paper: Survey Paper on Semantic Web and Inference Engine  (Size 567KB)

Semantic Web Google Tech Talk

The Semantic Web is a field aiming a the creation, deployment, and interoperation of machine readable data on the Internet. In the talk we present some projects in DERI on Semantic Web technologies – notably Semantic Interlinking of Online Community sites, Social Semantic Collaborative Filtering, and ActiveRDF, a library for Browsing, programming and navigating Semantic Web data.

The SIOC (Semantic Interlinking of Online Communities) project [1] is an effort aiming at establishing and deploying a metadata vocabulary for interlinking and connecting distributed conversation on blogs, bulletin boards, and mailing lists. The vocabulary has been implemented…

 

 

Making the Semantic Web Accessible to the Casual User

The Semantic Web presents the vision of a distributed, dynamically growing knowledge base founded on formal logic. Common users, however, seem to have problems even with the simplest Boolean
expression. So how can we help users to query a web of logic that they do not seem to understand? One frequently proposed solution to address this problem is the use of natural language (NL) for
knowledge specification and querying. We propose to regard formal query languages and NL as two extremes of a continuum, where semistructured languages lie somewhere in the middle.

To evaluate what degree of structuredness casual users prefer, we introduce four query interfaces, each at a different point in the continuum, and evaluate the users’ preference and their query performance in a study with 48 subjects. The results of the study reveal that while the users dislike the constraints of a fully
structured formal query language they also seem at a loss with the freedom of a full NLP approach. This suggests that restricted query languages will be preferred by casual users because of their
guidance effect, mirroring findings from social science theory on human activity in general.
Speaker: Prof. Bernstein
Abraham Bernstein is a full Professor at the Department of Information Technology (Institut für Informatik) of the University of Zurich. He conducts research on various aspects of supporting dynamic (intra- and inter-) organizational processes. His work draws from both social science (organizational psychology/sociology) and technical (computer science, artificial intelligence) foundations.

Before coming to Zurich he was an Assistant Professor, at the Information Systems Department in New York University’s Stern School of Business, and received a Ph.D. at MIT’s Sloan School of Management, where he worked with Prof. Thomas W. Malone at the Center for Coordination Science.