Search (113 results, page 6 of 6)

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Abstract

Many Semantic Web applications provide access to their resources through text-based search queries, using explicit semantics to improve the search results. This paper provides an analysis of the current state of the art in semantic search, based on 35 existing systems. We identify different types of semantic search features that are used during query construction, the core search process, the presentation of the search results and user feedback on query and results. For each of these, we consider the functionality that the system provides and how this is made available through the user interface.

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Abstract

A broad range of approaches to semantic document retrieval has been developed in the context of the Semantic Web. This survey builds bridges among them. We introduce a classification scheme for semantic search engines and clarify terminology. We present an overview of ten selected approaches and compare them by means of our classification criteria. Based on this comparison, we identify not only common concepts and outstanding features, but also open issues. Finally, we give directions for future application development and research.

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Abstract

The Semantic Web realization depends on the availability of a critical mass of metadata for the web content, associated with the respective formal knowledge about the world. We claim that the Semantic Web, at its current stage of development, is in a state of a critical need of metadata generation and usage schemata that are specific, well-defined and easy to understand. This paper introduces our vision for a holistic architecture for semantic annotation, indexing, and retrieval of documents with regard to extensive semantic repositories. A system (called KIM), implementing this concept, is presented in brief and it is used for the purposes of evaluation and demonstration. A particular schema for semantic annotation with respect to real-world entities is proposed. The underlying philosophy is that a practical semantic annotation is impossible without some particular knowledge modelling commitments. Our understanding is that a system for such semantic annotation should be based upon a simple model of real-world entity classes, complemented with extensive instance knowledge. To ensure the efficiency, ease of sharing, and reusability of the metadata, we introduce an upper-level ontology (of about 250 classes and 100 properties), which starts with some basic philosophical distinctions and then goes down to the most common entity types (people, companies, cities, etc.). Thus it encodes many of the domain-independent commonsense concepts and allows straightforward domain-specific extensions. On the basis of the ontology, a large-scale knowledge base of entity descriptions is bootstrapped, and further extended and maintained. Currently, the knowledge bases usually scales between 105 and 106 descriptions. Finally, this paper presents a semantically enhanced information extraction system, which provides automatic semantic annotation with references to classes in the ontology and to instances. The system has been running over a continuously growing document collection (currently about 0.5 million news articles), so it has been under constant testing and evaluation for some time now. On the basis of these semantic annotations, we perform semantic based indexing and retrieval where users can mix traditional information retrieval (IR) queries and ontology-based ones. We argue that such large-scale, fully automatic methods are essential for the transformation of the current largely textual web into a Semantic Web.

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Abstract

This paper focuses on the optimization of the navigation through voluminous subsumption hierarchies of topics employed by Portal Catalogs like Netscape Open Directory (ODP). We advocate for the use of labeling schemes for modeling these hierarchies in order to efficiently answer queries such as subsumption check, descendants, ancestors or nearest common ancestor, which usually require costly transitive closure computations. We first give a qualitative comparison of three main families of schemes, namely bit vector, prefix and interval based schemes. We then show that two labeling schemes are good candidates for an efficient implementation of label querying using standard relational DBMS, namely, the Dewey Prefix scheme [6] and an Interval scheme by Agrawal, Borgida and Jagadish [1]. We compare their storage and query evaluation performance for the 16 ODP hierarchies using the PostgreSQL engine.

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Series

Lecture notes in computer science ; 4825

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Abstract

The first section of "Semantic Web and Education" surveys the basic aspects and features of the Semantic Web. After this basic review, the book turns its focus to its primary topic of how Semantic Web developments can be used to build attractive and more successful education applications. The book analytically discusses the technical areas of architecture, metadata, learning objects, software engineering trends, and more. Integrated with these technical topics are the examinations of learning-oriented topics such as learner modeling, collaborative learning, learning management, learning communities, ontological engineering of web-based learning, and related topics. The result is a thorough and highly useful presentation on the confluence of the technical aspects of the Semantic Web and the field of Education or the art of teaching. The book will be of considerable interest to researchers and students in the fields Information Systems, Computer Science, and Education.

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Abstract

This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO's precision at 95%-as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO's data.

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Abstract

Many Semantic Web initiatives improve the capabilities of machines to exchange the meaning of information with other machines. These efforts lead to an increased quality of the application's results, but their user interfaces take little or no advantage of the semantic richness. For example, an ontology-based search engine will use its ontology when evaluating the user's query (e.g. for query formulation, disambiguation or evaluation), but fails to use it to significantly enrich the presentation of the results to a human user. For example, one could imagine replacing the endless list of hits with a structured presentation based on the semantic properties of the hits. Another problem is that the modelling of a domain is done from a single perspective (most often that of the information provider). Therefore, presentation based on the resulting ontology is unlikely to satisfy the needs of all the different types of users of the information. So even assuming an ontology for the domain is in place, mapping that ontology to the needs of individual users - based on their tasks, expertise and personal preferences - is not trivial.

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Abstract

The OWL Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. OWL has three increasingly-expressive sublanguages: OWL Lite, OWL DL, and OWL Full. This document is written for readers who want a first impression of the capabilities of OWL. It provides an introduction to OWL by informally describing the features of each of the sublanguages of OWL. Some knowledge of RDF Schema is useful for understanding this document, but not essential. After this document, interested readers may turn to the OWL Guide for more detailed descriptions and extensive examples on the features of OWL. The normative formal definition of OWL can be found in the OWL Semantics and Abstract Syntax.

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Abstract

Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.

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Content

Table of Contents Part I: Accepted Papers Christoph Tempich and Raphael Volz: Towards a benchmark for Semantic Web reasoners - an analysis of the DAML ontology library M. Carmen Suarez-Figueroa and Asuncion Gomez-Perez: Results of Taxonomic Evaluation of RDF(S) and DAML+OIL ontologies using RDF(S) and DAML+OIL Validation Tools and Ontology Platforms import services Volker Haarslev and Ralf Möller: Racer: A Core Inference Engine for the Semantic Web Mikhail Kazakov and Habib Abdulrab: DL-workbench: a metamodeling approach to ontology manipulation Thorsten Liebig and Olaf Noppens: OntoTrack: Fast Browsing and Easy Editing of Large Ontologie Frederic Fürst, Michel Leclere, and Francky Trichet: TooCoM : a Tool to Operationalize an Ontology with the Conceptual Graph Model Naoki Sugiura, Masaki Kurematsu, Naoki Fukuta, Noriaki Izumi, and Takahira Yamaguchi: A domain ontology engineering tool with general ontologies and text corpus Howard Goldberg, Alfredo Morales, David MacMillan, and Matthew Quinlan: An Ontology-Driven Application to Improve the Prescription of Educational Resources to Parents of Premature Infants Part II: Experiment Contributions Domain natural language description for the experiment Raphael Troncy, Antoine Isaac, and Veronique Malaise: Using XSLT for Interoperability: DOE and The Travelling Domain Experiment Christian Fillies: SemTalk EON2003 Semantic Web Export / Import Interface Test Óscar Corcho, Asunción Gómez-Pérez, Danilo José Guerrero-Rodríguez, David Pérez-Rey, Alberto Ruiz-Cristina, Teresa Sastre-Toral, M. Carmen Suárez-Figueroa: Evaluation experiment of ontology tools' interoperability with the WebODE ontology engineering workbench Holger Knublauch: Case Study: Using Protege to Convert the Travel Ontology to UML and OWL Franz Calvo and John Gennari: Interoperability of Protege 2.0 beta and OilEd 3.5 in the Domain Knowledge of Osteoporosis

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Abstract

As the World Wide Web continues to expand, it becomes increasingly difficult for users to obtain information efficiently. Because most search engines read format languages such as HTML or SGML, search results reflect formatting tags more than actual page content, which is expressed in natural language. Spinning the Semantic Web describes an exciting new type of hierarchy and standardization that will replace the current "Web of links" with a "Web of meaning." Using a flexible set of languages and tools, the Semantic Web will make all available information - display elements, metadata, services, images, and especially content - accessible. The result will be an immense repository of information accessible for a wide range of new applications. This first handbook for the Semantic Web covers, among other topics, software agents that can negotiate and collect information, markup languages that can tag many more types of information in a document, and knowledge systems that enable machines to read Web pages and determine their reliability. The truly interdisciplinary Semantic Web combines aspects of artificial intelligence, markup languages, natural language processing, information retrieval, knowledge representation, intelligent agents, and databases.