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.

A framework for ontology evolution in collaborative environments

Abstract: With the wider use of ontologies in the Semantic Web and as part of production systems, multiple scenarios for ontology maintenance and evolution are emerging. For example, successive ontology versions can be posted on the (Semantic) Web, with users discovering the new versions serendipitously; ontology-development in a collaborative environment can be synchronous or asynchronous; managers of projects may exercise quality control, examining changes from previous baseline versions and accepting or rejecting them before a new baseline is published, and so on. In this paper, we present different scenarios for ontology maintenance and evolution that we have encountered in our own projects and in those of our collaborators. We define several features that categorize these scenarios. For each scenario, we discuss the high-level tasks that an editing environment must support. We then present a unified comprehensive set of tools to support different scenarios in a single framework, allowing users to switch between different modes easily.

Towards domain-independent information extraction from web tables

Abstract: Traditionally, information extraction from web tables has focused on small, more or less homogeneous corpora, often based on assumptions about the use of tags. A multitude of different HTML implementations of web tables make these approaches difficult to scale. In this paper, we approach the problem of domain-independent information extraction from web tables by shifting our attention from the tree-based representation of webpages to a variation of the two-dimensional visual box model used by web browsers to display the information on the screen. The there by obtained topological and style information allows us to fill the gap created by missing domain-specific knowledge about content and table templates. We believe that, in a future step, this approach can become the basis for a new way of large-scale knowledge acquisition from the current "Visual Web.

KAoS policy management for semantic Web services

Abstract: Web Services power through explicit representations of Web resources underlying semantics and the development of an intelligent Web infrastructure that can fully exploit them. Semantic Web languages, such as OWL, extend RDF to let users specify ontologies comprising taxonomies of classes and inference rules. Both people and software agents can effectively use Semantic Web Services.' Agents will increasingly use the combination of semantic markup languages and Semantic Web Services to understand and autonomously manipulate Web content in significant ways. Agents will discover, communicate, and cooperate with other agents and services and-as we' 11 describe -will rely on policy-based management and control mechanisms to ensure respect for human-imposed constraints on agent interaction. Policy-based controls of Semantic Web Services can also help govern interaction with traditional (nonagent) clients.

Authorization and privacy for semantic Web services

Abstract: Web services will soon handle users' private information. They'll need to provide privacy guarantees to prevent this delicate information from ending up in the wrong hands. More generally, Web services will need to reason about their users' policies that specify who can access private information and under what conditions. These requirements are even more stringent for semantic Web services that exploit the semantic Web to automate their discovery and interaction because they must autonomously decide what information to exchange and how. In our previous work, we proposed ontologies for modeling the high-level security requirements and capabilities of Web services and clients.1 This modeling helps to match a client's request with appropriate services-those based on security criteria as well as functional descriptions.

Learning to extract text-based information from the World Wide Web

Abstract: There is a wealth of information to be mined from narrative text on the World Wide Web. Unfortunately, standard natural language processing (NLP) extraction techniques expect full, grammatical sentences, and perform poorly on the choppy sentence fragments that are often found on web pages. This paper1 introduces Webfoot, a preprocessor that parses web pages into logically coherent segments based on page layout cues. Output from Webfoot is then passed on to CRYSTAL, an NLP system that learns text extraction rules from example. Webfoot and CRYSTAL transform the text into a formal representation that is equivalent to relational database entries. This is a necessary first step for knowledge discovery and other automated analysis of free text.