Semantic Web

About: Semantic Web is a research topic. Over the lifetime, 26987 publications have been published within this topic receiving 534275 citations. The topic is also known as: Sem Web & SemWeb.

Description logics for matchmaking of services

Abstract: Matchmaking is an important aspect of E-Commerce interactions. The current trend in B2B E-Commerce automation is towards complex interactions for service provision. In this context, matchmaking services require rich and flexible metadata as well as matching algorithms. The Semantic Web initiative at W3C is gaining momentum and generating suitable technologies and tools to cover both the metadata and the algorithmic aspects. In this paper we describe our experience in building a matchmaking prototype. We choose to base our prototype on a Description Logic (DL) reasoner, operating on service descriptions in DAML+OIL. We report on our investigation of DAML+OIL to express service descriptions and on our experience on existing DL reasoners, in particular assessing RACER and FACT.

SEWeP: using site semantics and a taxonomy to enhance the Web personalization process

Abstract: Web personalization is the process of customizing a Web site to the needs of each specific user or set of users, taking advantage of the knowledge acquired through the analysis of the user's navigational behavior. Integrating usage data with content, structure or user profile data enhances the results of the personalization process. In this paper, we present SEWeP, a system that makes use of both the usage logs and the semantics of a Web site's content in order to personalize it. Web content is semantically annotated using a conceptual hierarchy (taxonomy). We introduce C-logs, an extended form of Web usage logs that encapsulates knowledge derived from the link semantics. C-logs are used as input to the Web usage mining process, resulting in a broader yet semantically focused set of recommendations.

RDFa in XHTML: Syntax and Processing

Abstract: The current Web is primarily made up of an enormous number of documents that have been created using HTML. These documents contain significant amounts of structured data, which is largely unavailable to tools and applications. When publishers can express this data more completely, and when tools can read it, a new world of user functionality becomes available, letting users transfer structured data between applications and web sites, and allowing browsing applications to improve the user experience: an event on a web page can be directly imported into a user's desktop calendar; a license on a document can be detected so that users can be informed of their rights automatically; a photo's creator, camera setting information, resolution, location and topic can be published as easily as the original photo itself, enabling structured search and sharing. RDFa is a specification for attributes to express structured data in any markup language. This document specifies how to use RDFa with XHTML. The rendered, hypertext data of XHTML is reused by the RDFa markup, so that publishers don't need to repeat significant data in the document content. The underlying abstract representation is RDF [RDF-PRIMER], which lets publishers build their own vocabulary, extend others, and evolve their vocabulary with maximal interoperability over time. The expressed structure is closely tied to the data, so that rendered data can be copied and pasted along with its relevant structure. The rules for interpreting the data are generic, so that there is no need for different rules for different formats; this allows authors and publishers of data to define their own formats without having to update software, register formats via a central authority, or worry that two formats may interfere with each other. RDFa shares some use cases with microformats [MICROFORMATS]. Whereas microformats specify both a syntax for embedding structured data into HTML documents and a vocabulary of specific terms for each microformat, RDFa specifies only a syntax and relies on independent specification of terms (often called vocabularies or taxonomies) by others. RDFa allows terms from multiple independently-developed vocabularies to be freely intermixed and is designed such that the language can be parsed without knowledge of the specific term vocabulary being used. This document is a detailed syntax specification for RDFa, aimed at: those looking to create an RDFa parser, and who therefore need a detailed description of the parsing rules; those looking to recommend the use of RDFa within their organisation, and who would like to create some guidelines for their users; anyone familiar with RDF, and who wants to understand more about what is happening 'under the hood', when an RDFa parser runs. For those looking for an introduction to the use of RDFa and some real-world examples, please consult the RDFa Primer.

Learning to attach semantic metadata to web services

Abstract: Emerging Web standards promise a network of heterogeneous yet interoperable Web Services. Web Services would greatly simplify the development of many kinds of data integration and knowledge management applications. Unfortunately, this vision requires that services describe themselves with large amounts of semantic metadata "glue". We explore a variety of machine learning techniques to semi-automatically create such metadata. We make three contributions. First, we describe a Bayesian learning and inference algorithm for classifying HTML forms into semantic categories, as well as assigning semantic labels to the form's fields. These techniques are important as legacy HTML interfaces are migrated to Web Services. Second, we describe the application of the Naive Bayes and SVM algorithms to the task of Web Service classification. We show that an ensemble approach that treats Web Services as structured objects is more accurate than an unstructured approach. Finally, we describe a clustering algorithm that automatically discovers the semantic categories of Web Services. All of our algorithms are evaluated using large collections of real HTML forms and Web Services.