Search (722 results, page 1 of 37)

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Content

Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.

Source

WWW '02: Proceedings of the 11th International Conference on World Wide Web, May 7-11, 2002, Honolulu, Hawaii, USA

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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.

Content

Vgl. unter: http://www.dblab.ntua.gr/~bikakis/LD/5.pdf Vgl. auch: http://swoogle.umbc.edu/. Vgl. auch: http://ebiquity.umbc.edu/paper/html/id/183/. Vgl. auch: Radhakrishnan, A.: Swoogle : An Engine for the Semantic Web unter: http://www.searchenginejournal.com/swoogle-an-engine-for-the-semantic-web/5469/.

Theme

Semantic Web

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Abstract

In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.

Object

Semantic Web Search Engine

Theme

Semantic Web

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Abstract

This article presents a semantic-based Web retrieval system that is capable of retrieving the Web pages that are conceptually related to the implicit concepts of the query. The concept of concept is managed from a fuzzy point of view by means of semantic areas. In this context, the proposed system improves most search engines that are based on matching words. The key of the system is to use a new version of the Fuzzy Interrelations and Synonymy-Based Concept Representation Model (FIS-CRM) to extract and represent the concepts contained in both the Web pages and the user query. This model, which was integrated into other tools such as the Fuzzy Interrelations and Synonymy based Searcher (FISS) metasearcher and the fz-mail system, considers the fuzzy synonymy and the fuzzy generality interrelations as a means of representing word interrelations (stored in a fuzzy synonymy dictionary and ontologies). The new version of the model, which is based on the study of the cooccurrences of synonyms, integrates a soft method for disambiguating word senses. This method also considers the context of the word to be disambiguated and the thematic ontologies and sets of synonyms stored in the dictionary.

Date

22. 7.2006 17:14:12

Footnote

Beitrag in einer Special Topic Section on Soft Approaches to Information Retrieval and Information Access on the Web

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Abstract

With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

In der heutigen Zeit nimmt die Flut an Informationen exponentiell zu. In dieser »Informationsexplosion« entsteht täglich eine unüberschaubare Menge an neuen Informationen im Web: Beispielsweise 430 deutschsprachige Artikel bei Wikipedia, 2,4 Mio. Tweets bei Twitter und 12,2 Mio. Kommentare bei Facebook. Während in Deutschland vor einigen Jahren noch Google als nahezu einzige Suchmaschine beim Zugriff auf Informationen im Web genutzt wurde, nehmen heute die u.a. in Social Media veröffentlichten Meinungen und damit die Vorauswahl sowie Bewertung von Informationen einzelner Experten und Meinungsführer an Bedeutung zu. Aber wie können themenspezifische Informationen nun effizient für konkrete Fragestellungen identifiziert und bedarfsgerecht aufbereitet und visualisiert werden? Diese Studie gibt einen Überblick über semantische Standards und Formate, die Prozesse der semantischen Suche, Methoden und Techniken semantischer Suchsysteme, Komponenten zur Entwicklung semantischer Suchmaschinen sowie den Aufbau bestehender Anwendungen. Die Studie erläutert den prinzipiellen Aufbau semantischer Suchsysteme und stellt Methoden der semantischen Suche vor. Zudem werden Softwarewerkzeuge vorgestellt, mithilfe derer einzelne Funktionalitäten von semantischen Suchmaschinen realisiert werden können. Abschließend erfolgt die Betrachtung bestehender semantischer Suchmaschinen zur Veranschaulichung der Unterschiede der Systeme im Aufbau sowie in der Funktionalität.

RSWK

Suchmaschine / Semantic Web / Information Retrieval
Suchmaschine / Information Retrieval / Ranking / Datenstruktur / Kontextbezogenes System

Subject

Suchmaschine / Semantic Web / Information Retrieval
Suchmaschine / Information Retrieval / Ranking / Datenstruktur / Kontextbezogenes System

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Theme

Semantic Web

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Abstract

This paper is about search of photos in photo databases of agencies which sell photos over the Internet. The problem is far from the behavior of photo databases managed by librarians and also far from the corpora generally used for research purposes. The descriptions use mainly single words and it is well known that it is not the best way to have a good search. This increases the problem of semantic ambiguity. This problem of semantic ambiguity is crucial for cross-language querying. On the other hand, users are not aware of documentation techniques and use generally very simple queries but want to get precise answers. This paper gives the experience gained in a 3 year use (2006-2008) of a cross-language access to several of the main international commercial photo databases. The languages used were French, English, and German.

Date

17. 4.2012 14:25:22

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

Over the last years, research and industry players have become increasingly interested in analyzing opinions and sentiments expressed on the social media web for product marketing and business intelligence. In order to adapt to this need search engines not only have to be able to retrieve lists of documents but to directly access, analyze, and interpret topics and opinions. This article covers an intermediate phase of the ongoing industrial research project 'DoXa' aiming at developing a semantic opinion and sentiment mining search engine for the French language. The DoXa search engine enables topic related opinion and sentiment extraction beyond positive and negative polarity using rich linguistic resources. Centering the work on two distinct business use cases, the authors analyze both unstructured Web 2.0 contents (e.g., blogs and forums) and structured questionnaire data sets. The focus is on discovering hidden patterns in the data. To this end, the authors present work in progress on opinion topic relation extraction and visual analytics, linguistic resource construction as well as the combination of OLAP technology with semantic search.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

The main goal of this book is to transfer new research results from the fields of advanced computer sciences and information science to the design of new search engines. The readers will have a better idea of the new trends in applied research. The achievement of relevant, organized, sorted, and workable answers- to name but a few - from a search is becoming a daily need for enterprises and organizations, and, to a greater extent, for anyone. It does not consist of getting access to structural information as in standard databases; nor does it consist of searching information strictly by way of a combination of key words. It goes far beyond that. Whatever its modality, the information sought should be identified by the topics it contains, that is to say by its textual, audio, video or graphical contents. This is not a new issue. However, recent technological advances have completely changed the techniques being used. New Web technologies, the emergence of Intranet systems and the abundance of information on the Internet have created the need for efficient search and information access tools.
Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.
With the rapid growth of web-based applications, such as search engines, Facebook, and Twitter, the development of effective and personalized information retrieval techniques and of user interfaces is essential. The amount of shared information and of social networks has also considerably grown, requiring metadata for new sources of information, like Wikipedia and ODP. These metadata have to provide classification information for a wide range of topics, as well as for social networking sites like Twitter, and Facebook, each of which provides additional preferences, tagging information and social contexts. Due to the explosion of social networks and other metadata sources, it is an opportune time to identify ways to exploit such metadata in IR tasks such as user modeling, query understanding, and personalization, to name a few. Although the use of traditional metadata such as html text, web page titles, and anchor text is fairly well-understood, the use of category information, user behavior data, and geographical information is just beginning to be studied. This book is intended for scientists and decision-makers who wish to gain working knowledge about search engines in order to evaluate available solutions and to dialogue with software and data providers.

Content

Enthält die Beiträge: Das, A., A. Jain: Indexing the World Wide Web: the journey so far. Ke, W.: Decentralized search and the clustering paradox in large scale information networks. Roux, M.: Metadata for search engines: what can be learned from e-Sciences? Fluhr, C.: Crosslingual access to photo databases. Djioua, B., J.-P. Desclés u. M. Alrahabi: Searching and mining with semantic categories. Ghorbel, H., A. Bahri u. R. Bouaziz: Fuzzy ontologies building platform for Semantic Web: FOB platform. Lassalle, E., E. Lassalle: Semantic models in information retrieval. Berry, M.W., R. Esau u. B. Kiefer: The use of text mining techniques in electronic discovery for legal matters. Sleem-Amer, M., I. Bigorgne u. S. Brizard u.a.: Intelligent semantic search engines for opinion and sentiment mining. Hoeber, O.: Human-centred Web search.
Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.

LCSH

Information retrieval
Information retrieval / Research
Information storage and retrieval systems / Research

Subject

Information retrieval
Information retrieval / Research
Information storage and retrieval systems / Research

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Content

"Swoogle, the Semantic web search engine, is a research project carried out by the ebiquity research group in the Computer Science and Electrical Engineering Department at the University of Maryland. It's an engine tailored towards finding documents on the semantic web. The whole research paper is available here. Semantic web is touted as the next generation of online content representation where the web documents are represented in a language that is not only easy for humans but is machine readable (easing the integration of data as never thought possible) as well. And the main elements of the semantic web include data model description formats such as Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, Turtle, N-Triples), and notations such as RDF Schema (RDFS), the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain (Wikipedia). And Swoogle is an attempt to mine and index this new set of web documents. The engine performs crawling of semantic documents like most web search engines and the search is available as web service too. The engine is primarily written in Java with the PHP used for the front-end and MySQL for database. Swoogle is capable of searching over 10,000 ontologies and indexes more that 1.3 million web documents. It also computes the importance of a Semantic Web document. The techniques used for indexing are the more google-type page ranking and also mining the documents for inter-relationships that are the basis for the semantic web. For more information on how the RDF framework can be used to relate documents, read the link here. Being a research project, and with a non-commercial motive, there is not much hype around Swoogle. However, the approach to indexing of Semantic web documents is an approach that most engines will have to take at some point of time. When the Internet debuted, there were no specific engines available for indexing or searching. The Search domain only picked up as more and more content became available. One fundamental question that I've always wondered about it is - provided that the search engines return very relevant results for a query - how to ascertain that the documents are indeed the most relevant ones available. There is always an inherent delay in indexing of document. Its here that the new semantic documents search engines can close delay. Experimenting with the concept of Search in the semantic web can only bore well for the future of search technology."

Source

http://www.searchenginejournal.com/swoogle-an-engine-for-the-semantic-web/5469/

Theme

Semantic Web

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Abstract

The World Wide Web is rapidly filling with more text than anyone could have imagined even a short time ago, but the task of isolating relevant parts of this vast information has become just that much more daunting. Richard Belew brings a cognitive perspective to the study of information retrieval as a discipline within computer science. He introduces the idea of Finding Out About (FDA) as the process of actively seeking out information relevant to a topic of interest and describes its many facets - ranging from creating a good characterization of what the user seeks, to what documents actually mean, to methods of inferring semantic clues about each document, to the problem of evaluating whether our search engines are performing as we have intended. Finding Out About explains how to build the tools that are useful for searching collections of text and other media. In the process it takes a close look at the properties of textual documents that do not become clear until very large collections of them are brought together and shows that the construction of effective search engines requires knowledge of the statistical and mathematical properties of linguistic phenomena, as well as an appreciation for the cognitive foundation we bring to the task as language users. The unique approach of this book is its even handling of the phenomena of both numbers and words, making it accessible to a wide audience. The textbook is usable in both undergraduate and graduate classes on information retrieval, library science, and computational linguistics. The text is accompanied by a CD-ROM that contains a hypertext version of the book, including additional topics and notes not present in the printed edition. In addition, the CD contains the full text of C.J. "Keith" van Rijsbergen's famous textbook, Information Retrieval (now out of print). Many active links from Belew's to van Rijsbergen's hypertexts help to unite the material. Several test corpora and indexing tools are provided, to support the design of your own search engine. Additional exercises using these corpora and code are available to instructors. Also supporting this book is a Web site that will include recent additions to the book, as well as links to sites of new topics and methods.

LCSH

World Wide Web / Computer programs
Web search engines

RSWK

Suchmaschine / World Wide Web / Information Retrieval

Subject

Suchmaschine / World Wide Web / Information Retrieval
World Wide Web / Computer programs
Web search engines

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Abstract

Presents a multimedia model which describes the various multimedia components, their structure and their relationships with a pre-defined taxonomy of concepts, in order to support search engine information retrieval process

Date

1. 8.1996 22:08:06

Footnote

Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia

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Abstract

The work we are presenting is devoted to the information collected on the WWW. By the term collected we mean the whole process of retrieving, extracting and presenting results to the user. This research is part of the RAP (Research, Analyze, Propose) project in which we propose to combine two methods: (i) query reformulation using linguistic markers according to a given point of view; and (ii) text semantic analysis by means of contextual exploration results (Descles, 1991). The general project architecture describing the interactions between the users, the RAP system and the WWW search engines is presented in Nait-Baha et al. (1998). We will focus this paper on showing how we use linguistic markers to reformulate the queries according to a given point of view

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Abstract

Describes the concept of a proxy based information classification and filtering utility, named Web Assistant. On the behalf of users a private view of the WWW is generated based on a previously determined profile. This profile is created by monitoring the user anf group activities when browsing WWW pages. Additional features are integrated to allow for easy interoperability workgroups with similar project interests, maintain personal and common hotlists with automatic modification checks and a sophisticated search engine front-end

Date

1. 8.1996 22:08:06

Footnote

Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia

Theme

Web-Agenten

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Abstract

The Wolverhampton Web Library (WWLib) is a WWW search engine that provides access to UK based information. The experimental version developed in 1995, was a success but highlighted the need for a much higher degree of automation. An interesting feature of the experimental WWLib was that it organised information according to DDC. Discusses the advantages of classification and describes the automatic classifier that is being developed in Java as part of the new, fully automated WWLib

Date

1. 8.1996 22:08:06

Footnote

Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia; vgl. auch: http://www7.scu.edu.au/programme/posters/1846/com1846.htm.

Theme

Klassifikationssysteme im Online-Retrieval

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Abstract

In diesem Kapitel wird ein Überblick über bestehende semantische Suchmaschinen gegeben. Insgesamt werden 95 solcher Suchdienste identifiziert und im Rahmen einer Inhaltsanalyse verglichen. Es kann festgestellt werden, dass die Semantische Suche sich wesentlich von den im Rahmen des Semantic Web propagierten Technologien unterscheidet und Semantik in den betrachteten Suchmaschinen weiter zu fassen ist. Die betrachteten Suchmaschinen werden in ein Stufenmodell, welches nach dem Grad der Semantik unterscheidet, eingeordnet. Das Kapitel schließt mit 8 Thesen zum aktuellen Stand der semantischen Suche.

Source

Handbuch Internet-Suchmaschinen, 2: Neue Entwicklungen in der Web-Suche. Hrsg.: D. Lewandowski

Theme

Semantic Web

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Abstract

Describes a search engine that integrate text and image search. 1 or more Web site can be indexed for both textual and image information, allowing the user to search based on keywords or images or both. Another problem with the current search engines is that they show the results as pages of scrolled lists; this is not very user-friendly. The search engine allows the user to visualise to results in various ways. Explains the indexing and searching techniques of the search engine and highlights several features of the querying interface to make the retrieval process more efficient. Use examples to show the usefulness of the technology

Date

1. 8.1996 22:08:06

Footnote

Contribution to a special issue of papers from the 6th International World Wide Web conference, held 7-11 Apr 1997, Santa Clara, California

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Abstract

The World Wide Web is a popular and interactive medium used to collect, disseminate, and access an increasingly huge amount of information, which constitutes the mainstay of the so-called information and knowledge society. Because of its spectacular growth, related to both Web resources (pages, sites, and services) and number of users, the Web is nowadays the main information repository and provides some automatic systems for locating, accessing, and retrieving information. However, an open and crucial question remains: how to provide fast and effective retrieval of the information relevant to specific users' needs. This is a very hard and complex task, since it is pervaded with subjectivity, vagueness, and uncertainty. The expression soft computing refers to techniques and methodologies that work synergistically with the aim of providing flexible information processing tolerant of imprecision, vagueness, partial truth, and approximation. So, soft computing represents a good candidate to design effective systems for information access and retrieval on the Web. One of the most representative tools of soft computing is fuzzy set theory. This special topic section collects research articles witnessing some recent advances in improving the processes of information access and retrieval on the Web by using soft computing tools, and in particular, by using fuzzy sets and/or integrating them with other soft computing tools. In this introductory article, we first review the problem of Web retrieval and the concept of soft computing technology. We then briefly introduce the articles in this section and conclude by highlighting some future research directions that could benefit from the use of soft computing technologies.

Date

22. 7.2006 16:59:33

Footnote

Beitrag in einer Special Topic Section on Soft Approaches to Information Retrieval and Information Access on the Web