Search (18 results, page 1 of 1)

  • × theme_ss:"Suchmaschinen"
  • × type_ss:"el"
  1. Krempl, S.: Google muss zerschlagen werden (2007) 0.05
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    Content
    Vgl. die Studie "Maurer, H. et al: Report on dangers and opportunities posed by large search engines, particularly Google" unter: http://www.iicm.tugraz.at/iicm_papers/dangers_google.pdf.
  2. Baeza-Yates, R.; Boldi, P.; Castillo, C.: Generalizing PageRank : damping functions for linkbased ranking algorithms (2006) 0.02
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    Date
    16. 1.2016 10:22:28
  3. Dodge, M.: ¬A map of Yahoo! (2000) 0.02
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    Content
    "Introduction Yahoo! is the undisputed king of the Web directories, providing one of the key information navigation tools on the Internet. It has maintained its popularity over many Internet-years as the most visited Web site, against intense competition. This is because it does a good job of shifting, cataloguing and organising the Web [1] . But what would a map of Yahoo!'s hierarchical classification of the Web look like? Would an interactive map of Yahoo!, rather than the conventional listing of sites, be more useful as navigational tool? We can get some idea what a map of Yahoo! might be like by taking a look at ET-Map, a prototype developed by Hsinchun Chen and colleagues in the Artificial Intelligence Lab [2] at the University of Arizona. ET-Map was developed in 1995 as part of innovative research in automatic Internet homepage categorization and it charts a large chunk of Yahoo!, from the entertainment section representing some 110,000 different Web links. The map is a two-dimensional, multi-layered category map; its aim is to provide an intuitive visual information browsing tool. ET-Map can be browsed interactively, explored and queried, using the familiar point-and-click navigation style of the Web to find information of interest.
    The View From Above Browsing for a particular piece on information on the Web can often feel like being stuck in an unfamiliar part of town walking around at street level looking for a particular store. You know the store is around there somewhere, but your viewpoint at ground level is constrained. What you really want is to get above the streets, hovering half a mile or so up in the air, to see the whole neighbourhood. This kind of birds-eye view function has been memorably described by David D. Clark, Senior Research Scientist at MIT's Laboratory for Computer Science and the Chairman of the Invisible Worlds Protocol Advisory Board, as the missing "up button" on the browser [3] . ET-Map is a nice example of a prototype for Clark's "up-button" view of an information space. The goal of information maps, like ET-Map, is to provide the browser with a sense of the lie of the information landscape, what is where, the location of clusters and hotspots, what is related to what. Ideally, this 'big-picture' all-in-one visual summary needs to fit on a single standard computer screen. ET-Map is one of my favourite examples, but there are many other interesting information maps being developed by other researchers and companies (see inset at the bottom of this page). How does ET-Map work? Here is a sequence of screenshots of a typical browsing session with ET-Map, which ends with access to Web pages on jazz musician Miles Davis. You can also tryout ET-Map for yourself, using a fully working demo on the AI Lab's website [4] . We begin with the top-level map showing forty odd broad entertainment 'subject regions' represented by regularly shaped tiles. Each tile is a visual summary of a group of Web pages with similar content. These tiles are shaded different colours to differentiate them, while labels identify the subject of the tile and the number in brackets telling you how many individual Web page links it contains. ET-Map uses two important, but common-sense, spatial concepts in its organisation and representation of the Web. Firstly, the 'subject regions' size is directly related to the number of Web pages in that category. For example, the 'MUSIC' subject area contains over 11,000 pages and so has a much larger area than the neighbouring area of 'LIVE' which only has 4,300 odd pages. This is intuitively meaningful, as the largest tiles are visually more prominent on the map and are likely to be more significant as they contain the most links. In addition, a second spatial concept, that of neighbourhood proximity, is applied so 'subject regions' closely related in term of content are plotted close to each other on the map. For example, 'FILM' and 'YEAR'S OSCARS', at the bottom left, are neighbours in both semantic and spatial space. This make senses as many things in the real-world are ordered in this way, with things that are alike being spatially close together (e.g. layout of goods in a store, or books in a library). Importantly, ET-Map is also a multi-layer map, with sub-maps showing greater informational resolution through a finer degree of categorization. So for any subject region that contains more than two hundred Web pages, a second-level map, with more detailed categories is generated. This subdivision of information space is repeated down the hierarchy as far as necessary. In the example, the user selected the 'MUSIC' subject region which, not surprisingly, contained many thousands of pages. A second-level map with numerous different music categories is then presented to the user. Delving deeper, the user wants to learn more about jazz music, so clicking on the 'JAZZ' tile leads to a third-level map, a fine-grained map of jazz related Web pages. Finally, selecting the 'MILES DAVIS' subject region leads to more a conventional looking ranking of pages from which the user selects one to download.
    ET-Map was created using a sophisticated AI technique called Kohonen self-organizing map, a neural network approach that has been used for automatic analysis and classification of semantic content of text documents like Web pages. I do not pretend to fully understand how this technique works; I tend to think of it as a clever 'black-box' that group together things that are alike [5] . It is a real challenge to automatically classify pages from a very heterogeneous information collection like the Web into categories that will match the conceptions of a typical user. Directories like Yahoo! tend to rely on the skill of human editors to achieve this. ET-Map is an interesting prototype that I think highlights well the potential for a map-based approach to Web browsing. I am surprised none of the major search engines or directories have introduced the option of mapping results. Although, I am sure many are working on ideas. People certainly need all the help they get, as Web growth shows no sign of slowing. Just last month it was reported that the Web had surpassed one billion indexable pages [6].
  4. Bauckhage, C.: Marginalizing over the PageRank damping factor (2014) 0.01
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  5. Sander, M.; Cronimund, C.: Google anonym nutzen? : Wie ein Zürcher den Tech-Giganten austrickst (2021) 0.01
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  6. Leisinger, C.: Sobald die Konkurrenten eine faire Chance haben, wird Google auf einen Schlag 20 Prozent seines Marktanteils verlieren (2020) 0.01
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  7. Dunning, A.: Do we still need search engines? (1999) 0.01
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    Source
    Ariadne. 1999, no.22
  8. Franke-Maier, M.; Rüter, C.: Discover Sacherschließung! : Was machen suchmaschinenbasierte Systeme mit unseren inhaltlichen Metadaten? (2015) 0.01
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  9. Birmingham, J.: Internet search engines (1996) 0.01
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    Date
    10.11.1996 16:36:22
  10. El-Ramly, N.; Peterson. R.E.; Volonino, L.: Top ten Web sites using search engines : the case of the desalination industry (1996) 0.01
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    Abstract
    The desalination industry involves the desalting of sea or brackish water and achieves the purpose of increasing the worls's effective water supply. There are approximately 4.000 desalination Web sites. The six major Internet search engines were used to determine, according to each of the six, the top twenty sites for desalination. Each site was visited and the 120 gross returns were pared down to the final ten - the 'Top Ten'. The Top Ten were then analyzed to determine what it was that made the sites useful and informative. The major attributes were: a) currency (up-to-date); b) search site capability; c) access to articles on desalination; d) newsletters; e) databases; f) product information; g) online conferencing; h) valuable links to other sites; l) communication links; j) site maps; and k) case studies. Reasons for having a Web site and the current status and prospects for Internet commerce are discussed
  11. Bladow, N.; Dorey, C.; Frederickson, L.; Grover, P.; Knudtson, Y.; Krishnamurthy, S.; Lazarou, V.: What's the Buzz about? : An empirical examination of Search on Yahoo! (2005) 0.01
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  12. Schulzki-Haddouti, C.: Mit Google durchs WWW : Was die immer populärer werdende Suchmaschine vom Rest der Welt unterscheidet (2001) 0.01
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  13. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01
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    Date
    17.12.2013 11:02:22
  14. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.01
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    Date
    19. 2.2019 17:22:00
  15. mho: Google erweitert Suchfunktion um Informationsdatenbank (2012) 0.01
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    Content
    "Google hat seine Suchmaschine um eine Datenbank erweitert, die die Suchergebnisse um Fakten zu verschiedensten Objekten und Personen ergänzt. Diese semantische Suchfunktion, die vorerst nur Nutzern in den USA zur Verfügung steht, soll Suchbegriffe inhaltlich erkennen und Zusammenhänge zu anderen Themen herstellen. Damit soll Google noch besser erkennen, wonach die Nutzer suchen und möglichst auch gleich weitere Fragen beantworten. In einem Blogeintrag [http://googleblog.blogspot.de/2012/05/introducing-knowledge-graph-things-not.html] erläutert Google-Manager Amit Singhal die neue Funktion, die unter der Bezeichnung "Knowledge Graph" [http://www.google.com/insidesearch/features/search/knowledge.html] firmiert und in einem Video [http://www.youtube.com/watch?v=mmQl6VGvX-c] vorgestellt wird. Dabei handele es sich um eine große Informationsdatenbank, die derzeit über 500 Millionen Objekte und mehr als 3,5 Milliarden Informationen über die Beziehungen zwischen ihnen enthalte. Darunter fänden sich Sehenswürdigkeiten, berühmte Personen, Städte, Sportmannschaften, Gebäude, Orte, Filme, Himmelsobjekte, Kunstwerke oder Ähnliches. Anhand der Suchanfragen und der Ergebnisse wird die Datenbank immer weiter verbessert, verspricht Google. Dank dieser Neuerung verspricht Google seinen Nutzern drei merkliche Verbesserungen. So könne die Suchmaschine nun besser erkennen, wonach genau gesucht werde, beispielsweise das Gebäude Taj Mahal oder der US-Musiker mit gleichem Namen. Weiterhin könne Google durch den Knowledge Graph wichtige Inhalte besser zusammenfassen, beispielsweise die Lebensdaten einer berühmten Person und ihre Leistungen. Auch bereits getätigte Suchen andere Nutzer könnten künftige Suchergebnisse dadurch beeinflussen. So sei für für Suchende etwa von Interesse, welche Bücher Charles Dickens geschrieben habe. Bei dem Architekten Frank Lloyd Wright sei jedoch weniger die Literatur interessant, als die von ihm gestalteten Gebäude.
  16. Place, E.: Internationale Zusammenarbeit bei Internet Subject Gateways (1999) 0.00
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    Date
    22. 6.2002 19:35:09
  17. Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005) 0.00
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    Date
    16. 1.2016 10:22:28
  18. Gillitzer, B.: Yewno (2017) 0.00
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    Date
    22. 2.2017 10:16:49