-
Koch, T.: Searching the Web : systematic overview over indexes (1995)
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-
Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013)
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- Abstract
- This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.
- Date
- 17.12.2013 11:02:22
- Theme
- Citation indexing
-
Page, L.; Brin, S.; Motwani, R.; Winograd, T.: ¬The PageRank citation ranking : Bringing order to the Web (1999)
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- Theme
- Citation indexing
-
Dunning, A.: Do we still need search engines? (1999)
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- Source
- Ariadne. 1999, no.22
-
Birmingham, J.: Internet search engines (1996)
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- Date
- 10.11.1996 16:36:22
-
Matrix of WWW indices : a comparison of Internet indexing tools (1995)
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-
Koch, T.: Literature about search services (1996)
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- Content
- Abschnitte: Search service comparisons; About search services and retrieval; Indexing the Internet; Collections and bibliographies
-
Radhakrishnan, A.: Swoogle : an engine for the Semantic Web (2007)
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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."
-
Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019)
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- Date
- 19. 2.2019 17:22:00
-
Entlich, R.: FAQ: Image Search Engines (2001)
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- Abstract
- Everyone loves images. The web wasn't anything until images came along, then it was an overnight success. So how does one find a specific image on the web? By using one of a burgeoning number of image-focused search engines. These search engines are simply optimized versions of typical web indexes, with crawlers that go around sucking down web content and indexing it. But with image search engines, they focus on images only, and the web page text that may describe them. As information professionals, we know that this is a clumsy approach at best, but as the author puts it, until more sophisticated methods become available, the tools profiled here will "have to suffice." Seven search engines are thoroughly tested in this review article, with Google's Image Search (http://www.google.com/imghp?hl=en) being the highest rated
-
Ding, L.; Finin, T.; Joshi, A.; Peng, Y.; Cost, R.S.; Sachs, J.; Pan, R.; Reddivari, P.; Doshi, V.: Swoogle : a Semantic Web search and metadata engine (2004)
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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.
-
Place, E.: Internationale Zusammenarbeit bei Internet Subject Gateways (1999)
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- Date
- 22. 6.2002 19:35:09
-
Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011)
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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.
-
Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005)
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- Date
- 16. 1.2016 10:22:28
-
Baeza-Yates, R.; Boldi, P.; Castillo, C.: Generalizing PageRank : damping functions for linkbased ranking algorithms (2006)
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- Date
- 16. 1.2016 10:22:28
-
Search Engines and Beyond : Developing efficient knowledge management systems, April 19-20 1999, Boston, Mass (1999)
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- Content
- Ramana Rao (Inxight, Palo Alto, CA) 7 ± 2 Insights on achieving Effective Information Access Session One: Updates and a twelve month perspective Danny Sullivan (Search Engine Watch, US / England) Portalization and other search trends Carol Tenopir (University of Tennessee) Search realities faced by end users and professional searchers Session Two: Today's search engines and beyond Daniel Hoogterp (Retrieval Technologies, McLean, VA) Effective presentation and utilization of search techniques Rick Kenny (Fulcrum Technologies, Ontario, Canada) Beyond document clustering: The knowledge impact statement Gary Stock (Ingenius, Kalamazoo, MI) Automated change monitoring Gary Culliss (Direct Hit, Wellesley Hills, MA) User popularity ranked search engines Byron Dom (IBM, CA) Automatically finding the best pages on the World Wide Web (CLEVER) Peter Tomassi (LookSmart, San Francisco, CA) Adding human intellect to search technology Session Three: Panel discussion: Human v automated categorization and editing Ev Brenner (New York, NY)- Chairman James Callan (University of Massachusetts, MA) Marc Krellenstein (Northern Light Technology, Cambridge, MA) Dan Miller (Ask Jeeves, Berkeley, CA) Session Four: Updates and a twelve month perspective Steve Arnold (AIT, Harrods Creek, KY) Review: The leading edge in search and retrieval software Ellen Voorhees (NIST, Gaithersburg, MD) TREC update Session Five: Search engines now and beyond Intelligent Agents John Snyder (Muscat, Cambridge, England) Practical issues behind intelligent agents Text summarization Therese Firmin, (Dept of Defense, Ft George G. Meade, MD) The TIPSTER/SUMMAC evaluation of automatic text summarization systems Cross language searching Elizabeth Liddy (TextWise, Syracuse, NY) A conceptual interlingua approach to cross-language retrieval. Video search and retrieval Armon Amir (IBM, Almaden, CA) CueVideo: Modular system for automatic indexing and browsing of video/audio Speech recognition Michael Witbrock (Lycos, Waltham, MA) Retrieval of spoken documents Visualization James A. Wise (Integral Visuals, Richland, WA) Information visualization in the new millennium: Emerging science or passing fashion? Text mining David Evans (Claritech, Pittsburgh, PA) Text mining - towards decision support
-
Gillitzer, B.: Yewno (2017)
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- Date
- 22. 2.2017 10:16:49
