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.

The World Wide Web as a Resource for Example-Based Machine Translation Tasks

Abstract: The WWW is two orders of magnitude larger than the largest corpora. Although noisy, web text presents language as it is used, and statistics derived from the Web can have practical uses in many NLP applications. For this reason, the WWW should be seen and studied as any other computationally available linguistic resource. In this article, we illustrate this by showing that an Example-Based approach to lexical choice for machine translation can use the Web as an adequate and free resource.

Ranked Matching for Service Descriptions Using OWL-S

Abstract: Semantic Web services envision the automated discovery and selection of Web services. This can be realised by adding semantic information to advertised services and service requirements. The discovery and selection process finds matches between requirements and advertisements according to their semantic description. Based on the Web Ontology Language (OWL) an ontology for Web services (OWL-S) was introduced to standardise their semantic description. There are already some approaches available for matching of service requirements with service advertisements according to such an ontology.

Artificial Intelligence: Methodology, Systems, and Applications. 12th International Conference, AIMSA 2006, Varna, Bulgaria, September 12-15, 2006, Proceedings

Abstract: Invited Talks.- Exploiting Large-Scale Semantics on the Web.- Acquiring and Sharing Knowledge in Large Organizations: Issues, Requirements and Methodologies.- Agents.- Property Based Coordination.- A Formal General Setting for Dialogue Protocols.- OCC's Emotions: A Formalization in a BDI Logic.- Constraints and Optimization.- A Boolean Encoding Including SAT and n-ary CSPs.- A Constructive Hybrid Algorithm for Crew Pairing Optimization.- Using Local Search for Guiding Enumeration in Constraint Solving.- User Concerns.- Study on Integrating Semantic Applications with Magpie.- N-Gram Feature Selection for Authorship Identification.- Incorporating Privacy Concerns in Data Mining on Distributed Data.- Decision Support.- Multiagent Approach for the Representation of Information in a Decision Support System.- Flexible Decision Making in Web Services Negotiation.- On a Unified Framework for Sampling With and Without Replacement in Decision Tree Ensembles.- Models and Ontologies.- Spatio-temporal Proximities for Multimedia Document Adaptation.- Deep into Color Names: Matching Color Descriptions by Their Fuzzy Semantics.- Developing an Argumentation Ontology for Mailing Lists.- Machine Learning.- Clustering Approach Using Belief Function Theory.- Machine Learning for Spoken Dialogue Management: An Experiment with Speech-Based Database Querying.- Exploring an Unknown Environment with an Intelligent Virtual Agent.- Ontology Manipulation.- Case-Based Reasoning Within Semantic Web Technologies.- A Proposal for Annotation, Semantic Similarity and Classification of Textual Documents.- Cooking an Ontology.- Natural Language Processing.- Methodology for Bootstrapping Relation Extraction for the Semantic Web.- Using Verbs to Characterize Noun-Noun Relations.- Applications.- BEATCA: Map-Based Intelligent Navigation in WWW.- Model-Based Monitoring and Diagnosis Chip for Embedded Systems.- A Knowledge-Based Approach for Automatic Generation of Summaries of Behavior.- INFRAWEBS Designer - A Graphical Tool for Designing Semantic Web Services.

MEANS: A medical question-answering system combining NLP techniques and semantic Web technologies

Abstract: The Question Answering (QA) task aims to provide precise and quick answers to user questions from a collection of documents or a database. This kind of IR system is sorely needed with the dramatic growth of digital information. In this paper, we address the problem of QA in the medical domain where several specific conditions are met. We propose a semantic approach to QA based on (i) Natural Language Processing techniques, which allow a deep analysis of medical questions and documents and (ii) semantic Web technologies at both representation and interrogation levels. We present our Semantic Question-Answering System, called MEANS and our proposed method for “Answer Search” based on semantic search and query relaxation. We evaluate the overall system performance on real questions and answers extracted from MEDLINE articles. Our experiments show promising results and suggest that a query-relaxation strategy can further improve the overall performance.

How useful are natural language interfaces to the semantic web for casual end-users?

Abstract: Natural language interfaces offer end-users a familiar and convenient option for querying ontology-based knowledge bases. Several studies have shown that they can achieve high retrieval performance as well as domain independence. This paper focuses on usability and investigates if NLIs are useful from an end-user's point of view. To that end, we introduce four interfaces each allowing a different query language and present a usability study benchmarking these interfaces. The results of the study reveal a clear preference for full sentences as query language and confirm that NLIs are useful for querying Semantic Web data.