Search (93 results, page 1 of 5)

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Abstract

The advent of the Web in the mid-1990s followed by its fast adoption in a relatively short time, posed significant challenges to classical information retrieval methods developed in the 1970s and the 1980s. The major challenges include that the Web is massive, dynamic, and distributed. The two main types of tasks that are carried on the Web are searching and mining. Searching is locating information given an information need, and mining is extracting information and/or knowledge from a corpus. The metrics for success when carrying these tasks on the Web include precision, recall (completeness), freshness, and efficiency.

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Date

3. 5.1997 8:44:22

Theme

Data Mining

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Footnote

Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"

Theme

Data Mining

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Abstract

This project analyzed 541,920 user queries submitted to and executed in an academic Website during a four-year period (May 1997 to May 2001) using a relational database. The purpose of the study is three-fold: (1) to understand Web users' query behavior; (2) to identify problems encountered by these Web users; (3) to develop appropriate techniques for optimization of query analysis and mining. The linguistic analyses focus an query structures, lexicon, and word associations using statistical measures such as Zipf distribution and mutual information. A data model with finest granularity is used for data storage and iterative analyses. Patterns and trends of querying behavior are identified and compared with previous studies.

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Footnote

Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"

Theme

Data Mining

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Theme

Data Mining

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Footnote

Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"

Theme

Data Mining

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Date

27.11.2005 18:04:22

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Date

22. 6.2002 19:40:22

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Date

25. 8.2005 17:42:22

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Date

7. 6.2008 16:22:20

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Abstract

Purpose - This article is an edited version of a report commissioned by the British Library and JISC to identify how the specialist researchers of the future (those born after 1993) are likely to access and interact with digital resources in five to ten years' time. The purpose is to investigate the impact of digital transition on the information behaviour of the Google Generation and to guide library and information services to anticipate and react to any new or emerging behaviours in the most effective way. Design/methodology/approach - The study was virtually longitudinal and is based on a number of extensive reviews of related literature, survey data mining and a deep log analysis of a British Library and a JISC web site intended for younger people. Findings - The study shows that much of the impact of ICTs on the young has been overestimated. The study claims that although young people demonstrate an apparent ease and familiarity with computers, they rely heavily on search engines, view rather than read and do not possess the critical and analytical skills to assess the information that they find on the web. Originality/value - The paper reports on a study that overturns the common assumption that the "Google generation" is the most web-literate.

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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."

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Date

22. 6.2002 19:41:31

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Date

9. 7.2000 14:06:22

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Date

18. 1.1997 12:15:22

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Date

11.11.2001 17:25:22

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Date

9. 5.2002 21:21:22

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Content

Search engines now need to concentrate on addressing personalized searches by collecting more information on user habits, archive search information, style of search, location, educational and other background information before delivery of content. To satisfy a particular user, search engines need to generate a database of user characteristics (e.g., country, level of understanding of search technology, previous searches, applications he/she may use after the search, utility of the information, and the information life cycle), so that it can improve the quality of the content. More categorization of these characteristics will help delivery of appropriately relevant content. At present, browsers do not discriminate among users based upon any of these characteristics to improve content delivery. These additional features, if present in the browser, would form a good interactive interface between the World Wide Web and the user in the near future. Therefore, browser development should take the direction of technical integration with user characteristics and the constant updating of such information by a learning process associated with the user. This could improve the relevance of the retrieved content, i.e., the result set. The more a user browses, the more a browser would learn about that user. The next generation of browsers should have the capacity for intelligence to address issues related to content filtering, address blocking, user friendliness, and various levels of understanding. These browsers should also possess data mining tools so that the search engines could better facilitate user requirements. In such contexts, the browser would act as a self-reviewed catalyst to accelerate the delivery of quality content."

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Date

22. 6.2002 19:38:24