Search (27 results, page 1 of 2)

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Abstract

Web search engines such as Google, Yahoo! MSN/Bing, and Ask are far from the consummate Web search solution: they do not typically produce direct answers to queries but instead typically recommend a selection of related documents from the Web. We note that in more recent years, search engines have begun to provide direct answers to prose queries matching certain common templates-for example, "population of china" or "12 euro in dollars"-but again, such functionality is limited to a small subset of popular user queries. Furthermore, search engines now provide individual and focused search interfaces over images, videos, locations, news articles, books, research papers, blogs, and real-time social media-although these tools are inarguably powerful, they are limited to their respective domains. In the general case, search engines are not suitable for complex information gathering tasks requiring aggregation from multiple indexed documents: for such tasks, users must manually aggregate tidbits of pertinent information from various pages. In effect, such limitations are predicated on the lack of machine-interpretable structure in HTML-documents, which is often limited to generic markup tags mainly concerned with document renderign and linking. Most of the real content is contained in prose text which is inherently difficult for machines to interpret.

Object

Semantic Web Search Engine

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Abstract

The degree of structure of Web content is the determining factor for the types of functionality that search engines can provide. The more well structured the Web content is, the easier it is for search engines to understand Web content and provide advanced functionality, such as faceted filtering or the aggregation of content from multiple Web sites, based on this understanding. Today, most Web sites are generated from structured data that is stored in relational databases. Thus, it does not require too much extra effort for Web sites to publish this structured data directly on the Web in addition to HTML pages, and thus help search engines to understand Web content and provide improved functionality. An early approach to realize this idea and help search engines to understand Web content is Microformats, a technique for markingup structured data about specific types on entities-such as tags, blog posts, people, or reviews-within HTML pages. As Microformats are focused on a few entity types, the World Wide Web Consortium (W3C) started in 2004 to standardize RDFa as an alternative, more generic language for embedding any type of data into HTML pages. Today, major search engines such as Google, Yahoo, and Bing extract Microformat and RDFa data describing products, reviews, persons, events, and recipes from Web pages and use the extracted data to improve the user's search experience. The search engines have started to aggregate structured data from different Web sites and augment their search results with these aggregated information units in the form of rich snippets which combine, for instance, data This chapter gives an overview of the topology of the Web of Data that has been created by publishing data on the Web using the microformats RDFa, Microdata and Linked Data publishing techniques.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Abstract

The Web has become the world's largest database, with search being the main tool that allows organizations and individuals to exploit its huge amount of information. Search on the Web has been traditionally based on textual and structural similarities, ignoring to a large degree the semantic dimension, i.e., understanding the meaning of the query and of the document content. Combining search and semantics gives birth to the idea of semantic search. Traditional search engines have already advertised some semantic dimensions. Some of them, for instance, can enhance their generated result sets with documents that are semantically related to the query terms even though they may not include these terms. Nevertheless, the exploitation of the semantic search has not yet reached its full potential. In this book, Roberto De Virgilio, Francesco Guerra and Yannis Velegrakis present an extensive overview of the work done in Semantic Search and other related areas. They explore different technologies and solutions in depth, making their collection a valuable and stimulating reading for both academic and industrial researchers. The book is divided into three parts. The first introduces the readers to the basic notions of the Web of Data. It describes the different kinds of data that exist, their topology, and their storing and indexing techniques. The second part is dedicated to Web Search. It presents different types of search, like the exploratory or the path-oriented, alongside methods for their efficient and effective implementation. Other related topics included in this part are the use of uncertainty in query answering, the exploitation of ontologies, and the use of semantics in mashup design and operation. The focus of the third part is on linked data, and more specifically, on applying ideas originating in recommender systems on linked data management, and on techniques for the efficiently querying answering on linked data.

Content

Inhalt: Introduction.- Part I Introduction to Web of Data.- Topology of the Web of Data.- Storing and Indexing Massive RDF Data Sets.- Designing Exploratory Search Applications upon Web Data Sources.- Part II Search over the Web.- Path-oriented Keyword Search query over RDF.- Interactive Query Construction for Keyword Search on the SemanticWeb.- Understanding the Semantics of Keyword Queries on Relational DataWithout Accessing the Instance.- Keyword-Based Search over Semantic Data.- Semantic Link Discovery over Relational Data.- Embracing Uncertainty in Entity Linking.- The Return of the Entity-Relationship Model: Ontological Query Answering.- Linked Data Services and Semantics-enabled Mashup.- Part III Linked Data Search engines.- A Recommender System for Linked Data.- Flint: from Web Pages to Probabilistic Semantic Data.- Searching and Browsing Linked Data with SWSE.

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Abstract

The birth of the Web has brought an exponential growth to the amount of the information that is freely available to the Internet population, overloading users and entangling their efforts to satisfy their information needs. Web search engines such Google, Yahoo, or Bing have become popular mainly due to the fact that they offer an easy-to-use query interface (i.e., based on keywords) and an effective and efficient query execution mechanism. The majority of these search engines do not consider information stored on the deep or hidden Web [9,28], despite the fact that the size of the deep Web is estimated to be much bigger than the surface Web [9,47]. There have been a number of systems that record interactions with the deep Web sources or automatically submit queries them (mainly through their Web form interfaces) in order to index their context. Unfortunately, this technique is only partially indexing the data instance. Moreover, it is not possible to take advantage of the query capabilities of data sources, for example, of the relational query features, because their interface is often restricted from the Web form. Besides, Web search engines focus on retrieving documents and not on querying structured sources, so they are unable to access information based on concepts.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Abstract

Search is the preferred method to access information in today's computing systems. The Web, accessed through search engines, is universally recognized as the source for answering users' information needs. However, offering a link to a Web page does not cover all information needs. Even simple problems, such as "Which theater offers an at least three-stars action movie in London close to a good Italian restaurant," can only be solved by searching the Web multiple times, e.g., by extracting a list of the recent action movies filtered by ranking, then looking for movie theaters, then looking for Italian restaurants close to them. While search engines hint to useful information, the user's brain is the fundamental platform for information integration. An important trend is the availability of new, specialized data sources-the so-called "long tail" of the Web of data. Such carefully collected and curated data sources can be much more valuable than information currently available in Web pages; however, many sources remain hidden or insulated, in the lack of software solutions for bringing them to surface and making them usable in the search context. A new class of tailor-made systems, designed to satisfy the needs of users with specific aims, will support the publishing and integration of data sources for vertical domains; the user will be able to select sources based on individual or collective trust, and systems will be able to route queries to such sources and to provide easyto-use interfaces for combining them within search strategies, at the same time, rewarding the data source owners for each contribution to effective search. Efforts such as Google's Fusion Tables show that the technology for bringing hidden data sources to surface is feasible.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

Footnote

Rez. in: JASIST 58(2007) no.3, S.457-458 (A.M.A. Ahmad): "The concept of the semantic web has emerged because search engines and text-based searching are no longer adequate, as these approaches involve an extensive information retrieval process. The deployed searching and retrieving descriptors arc naturally subjective and their deployment is often restricted to the specific application domain for which the descriptors were configured. The new era of information technology imposes different kinds of requirements and challenges. Automatic extracted audiovisual features are required, as these features are more objective, domain-independent, and more native to audiovisual content. This book is a useful guide for researchers, experts, students, and practitioners; it is a very valuable reference and can lead them through their exploration and research in multimedia content and the semantic web. The book is well organized, and introduces the concept of the semantic web and multimedia content analysis to the reader through a logical sequence from standards and hypotheses through system examples, presenting relevant tools and methods. But in some chapters readers will need a good technical background to understand some of the details. Readers may attain sufficient knowledge here to start projects or research related to the book's theme; recent results and articles related to the active research area of integrating multimedia with semantic web technologies are included. This book includes full descriptions of approaches to specific problem domains such as content search, indexing, and retrieval. This book will be very useful to researchers in the multimedia content analysis field who wish to explore the benefits of emerging semantic web technologies in applying multimedia content approaches. The first part of the book covers the definition of the two basic terms multimedia content and semantic web. The Moving Picture Experts Group standards MPEG7 and MPEG21 are quoted extensively. In addition, the means of multimedia content description are elaborated upon and schematically drawn. This extensive description is introduced by authors who are actively involved in those standards and have been participating in the work of the International Organization for Standardization (ISO)/MPEG for many years. On the other hand, this results in bias against the ad hoc or nonstandard tools for multimedia description in favor of the standard approaches. This is a general book for multimedia content; more emphasis on the general multimedia description and extraction could be provided.
The final part of the book discusses research in multimedia content management systems and the semantic web, and presents examples and applications for semantic multimedia analysis in search and retrieval systems. These chapters describe example systems in which current projects have been implemented, and include extensive results and real demonstrations. For example, real case scenarios such as ECommerce medical applications and Web services have been introduced. Topics in natural language, speech and image processing techniques and their application for multimedia indexing, and content-based retrieval have been elaborated upon with extensive examples and deployment methods. The editors of the book themselves provide the readers with a chapter about their latest research results on knowledge-based multimedia content indexing and retrieval. Some interesting applications for multimedia content and the semantic web are introduced. Applications that have taken advantage of the metadata provided by MPEG7 in order to realize advance-access services for multimedia content have been provided. The applications discussed in the third part of the book provide useful guidance to researchers and practitioners properly planning to implement semantic multimedia analysis techniques in new research and development projects in both academia and industry. A fourth part should be added to this book: performance measurements for integrated approaches of multimedia analysis and the semantic web. Performance of the semantic approach is a very sophisticated issue and requires extensive elaboration and effort. Measuring the semantic search is an ongoing research area; several chapters concerning performance measurement and analysis would be required to adequately cover this area and introduce it to readers."

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Abstract

The book covers multimedia ontology in heritage preservation with intellectual explorations of various themes of Indian cultural heritage. The result of more than 15 years of collective research, Multimedia Ontology: Representation and Applications provides a theoretical foundation for understanding the nature of media data and the principles involved in its interpretation. The book presents a unified approach to recent advances in multimedia and explains how a multimedia ontology can fill the semantic gap between concepts and the media world. It relays real-life examples of implementations in different domains to illustrate how this gap can be filled. The book contains information that helps with building semantic, content-based search and retrieval engines and also with developing vertical application-specific search applications. It guides you in designing multimedia tools that aid in logical and conceptual organization of large amounts of multimedia data. As a practical demonstration, it showcases multimedia applications in cultural heritage preservation efforts and the creation of virtual museums. The book describes the limitations of existing ontology techniques in semantic multimedia data processing, as well as some open problems in the representations and applications of multimedia ontology. As an antidote, it introduces new ontology representation and reasoning schemes that overcome these limitations. The long, compiled efforts reflected in Multimedia Ontology: Representation and Applications are a signpost for new achievements and developments in efficiency and accessibility in the field.

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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.

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Abstract

All the papers underwent a thorough and rigorous peer-review process. The review and selection this year was highly competitive and only papers containing significant research results, innovative methods, or novel and best practices were accepted for publication. Only 29 of 89 submissions were accepted as full papers, representing 32.5% of the total number of submissions. Additional contributions covering noteworthy and important results in special tracks or project reports were accepted, totaling 42 accepted contributions. This year's conference included two outstanding keynote speakers. Dr. Stefan Gradmann, a professor arts department of KU Leuven (Belgium) and director of university library, addressed semantic research drawing from his work with Europeana. The title of his presentation was, "Towards a Semantic Research Library: Digital Humanities Research, Europeana and the Linked Data Paradigm". Dr. Michail Salampasis, associate professor from our conference host institution, the Department of Informatics of the Alexander TEI of Thessaloniki, presented new potential, intersecting search and linked data. The title of his talk was, "Rethinking the Search Experience: What Could Professional Search Systems Do Better?"

Date

17.12.2013 12:51:22

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Footnote

Rez. in: JASIST 57(2006) no.8, S.1132-1133 (H. Che): "The World Wide Web has been the main source of an important shift in the way people communicate with each other, get information, and conduct business. However, most of the current Web content is only suitable for human consumption. The main obstacle to providing better quality of service is that the meaning of Web content is not machine-accessible. The "Semantic Web" is envisioned by Tim Berners-Lee as a logical extension to the current Web that enables explicit representations of term meaning. It aims to bring the Web to its full potential via the exploration of these machine-processable metadata. To fulfill this, it pros ides some meta languages like RDF, OWL, DAML+OIL, and SHOE for expressing knowledge that has clear, unambiguous meanings. The first steps in searing the Semantic Web into the current Web are successfully underway. In the forthcoming years, these efforts still remain highly focused in the research and development community. In the next phase, the Semantic Web will respond more intelligently to user queries. The first chapter gets started with an excellent introduction to the Semantic Web vision. At first, today's Web is introduced, and problems with some current applications like search engines are also covered. Subsequently, knowledge management. business-to-consumer electronic commerce, business-to-business electronic commerce, and personal agents are used as examples to show the potential requirements for the Semantic Web. Next comes the brief description of the underpinning technologies, including metadata, ontology, logic, and agent. The differences between the Semantic Web and Artificial Intelligence are also discussed in a later subsection. In section 1.4, the famous "laser-cake" diagram is given to show a layered view of the Semantic Web. From chapter 2, the book starts addressing some of the most important technologies for constructing the Semantic Web. In chapter 2, the authors discuss XML and its related technologies such as namespaces, XPath, and XSLT. XML is a simple, very flexible text format which is often used for the exchange of a wide variety of data on the Web and elsewhere. The W3C has defined various languages on top of XML, such as RDF. Although this chapter is very well planned and written, many details are not included because of the extensiveness of the XML technologies. Many other books on XML provide more comprehensive coverage.

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Abstract

We are witnessing a smooth evolution of the Web from a worldwide information space of linked documents to a global knowledge base, where resources are identified by means of uniform resource identifiers (URIs, essentially string identifiers) and are semantically described and correlated through resource description framework (RDF, a metadata data model) statements. With the size and availability of data constantly increasing (currently around 7 billion RDF triples and 150 million RDF links), a fundamental problem lies in the difficulty users face to find and retrieve the information they are interested in. In general, to access semantic data, users need to know the organization of data and the syntax of a specific query language (e.g., SPARQL or variants thereof). Clearly, this represents an obstacle to information access for nonexpert users. For this reason, keyword search-based systems are increasingly capturing the attention of researchers. Recently, many approaches to keyword-based search over structured and semistructured data have been proposed]. These approaches usually implement IR strategies on top of traditional database management systems with the goal of freeing the users from having to know data organization and query languages.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Abstract

With the advance of the semantic Web, increasing amounts of data are available in a structured and machine-understandable form. This opens opportunities for users to employ semantic queries instead of simple keyword-based ones to accurately express the information need. However, constructing semantic queries is a demanding task for human users [11]. To compose a valid semantic query, a user has to (1) master a query language (e.g., SPARQL) and (2) acquire sufficient knowledge about the ontology or the schema of the data source. While there are systems which support this task with visual tools [21, 26] or natural language interfaces [3, 13, 14, 18], the process of query construction can still be complex and time consuming. According to [24], users prefer keyword search, and struggle with the construction of semantic queries although being supported with a natural language interface. Several keyword search approaches have already been proposed to ease information seeking on semantic data [16, 32, 35] or databases [1, 31]. However, keyword queries lack the expressivity to precisely describe the user's intent. As a result, ranking can at best put query intentions of the majority on top, making it impossible to take the intentions of all users into consideration.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Abstract

This book describes proven methodologies for developing semantic applications: software applications which explicitly or implicitly uses the semantics (i.e., the meaning) of a domain terminology in order to improve usability, correctness, and completeness. An example is semantic search, where synonyms and related terms are used for enriching the results of a simple text-based search. Ontologies, thesauri or controlled vocabularies are the centerpiece of semantic applications. The book includes technological and architectural best practices for corporate use.

Content

Introduction.- Ontology Development.- Compliance using Metadata.- Variety Management for Big Data.- Text Mining in Economics.- Generation of Natural Language Texts.- Sentiment Analysis.- Building Concise Text Corpora from Web Contents.- Ontology-Based Modelling of Web Content.- Personalized Clinical Decision Support for Cancer Care.- Applications of Temporal Conceptual Semantic Systems.- Context-Aware Documentation in the Smart Factory.- Knowledge-Based Production Planning for Industry 4.0.- Information Exchange in Jurisdiction.- Supporting Automated License Clearing.- Managing cultural assets: Implementing typical cultural heritage archive's usage scenarios via Semantic Web technologies.- Semantic Applications for Process Management.- Domain-Specific Semantic Search Applications.

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Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

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Abstract

This book constitutes the refereed proceedings of the Second European Semantic Web Conference, ESWC 2005, heldin Heraklion, Crete, Greece in May/June 2005. The 48 revised full papers presented were carefully reviewed and selected from 148 submissions. The papers are organized in topical sections on semantic Web services, languages, ontologies, reasoning and querying, search and information retrieval, user and communities, natural language for the semantic Web, annotation tools, and semantic Web applications.

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Content

The papers are organized in several sessions and tracks: general track on ontology evolution, engineering, and frameworks, semantic Web and metadata extraction, modelling, interoperability and exploratory search, data analysis, reuse and visualization; track on digital libraries, information retrieval, linked and social data; track on metadata and semantics for open repositories, research information systems and data infrastructure; track on metadata and semantics for agriculture, food and environment; track on metadata and semantics for cultural collections and applications; track on European and national projects.

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