Search (65 results, page 1 of 4)

  • × theme_ss:"Retrievalalgorithmen"
  1. Stock, M.; Stock, W.G.: Internet-Suchwerkzeuge im Vergleich (IV) : Relevance Ranking nach "Popularität" von Webseiten: Google (2001) 0.00 
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    Abstract
    In unserem Retrievaltest von Suchwerkzeugen im World Wide Web (Password 11/2000) schnitt die Suchmaschine Google am besten ab. Im Vergleich zu anderen Search Engines setzt Google kaum auf Informationslinguistik, sondern auf Algorithmen, die sich aus den Besonderheiten der Web-Dokumente ableiten lassen. Kernstück der informationsstatistischen Technik ist das "PageRank"- Verfahren (benannt nach dem Entwickler Larry Page), das aus der Hypertextstruktur des Web die "Popularität" von Seiten anhand ihrer ein- und ausgehenden Links berechnet. Google besticht durch das Angebot intuitiv verstehbarer Suchbildschirme sowie durch einige sehr nützliche "Kleinigkeiten" wie die Angabe des Rangs einer Seite, Highlighting, Suchen in der Seite, Suchen innerhalb eines Suchergebnisses usw., alles verstaut in einer eigenen Befehlsleiste innerhalb des Browsers. Ähnlich wie RealNames bietet Google mit dem Produkt "AdWords" den Aufkauf von Suchtermen an. Nach einer Reihe von nunmehr vier Password-Artikeln über InternetSuchwerkzeugen im Vergleich wollen wir abschließend zu einer Bewertung kommen. Wie ist der Stand der Technik bei Directories und Search Engines aus informationswissenschaftlicher Sicht einzuschätzen? Werden die "typischen" Internetnutzer, die ja in der Regel keine Information Professionals sind, adäquat bedient? Und können auch Informationsfachleute von den Suchwerkzeugen profitieren?
  2. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.00 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  3. Archuby, C.G.: Interfaces se recuperacion para catalogos en linea con salidas ordenadas por probable relevancia (2000) 0.00 
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    Date
    29. 1.1996 18:23:13
    Source
    Ciencia da informacao. 29(2000) no.3, S.5-13
  4. Crestani, F.: Combination of similarity measures for effective spoken document retrieval (2003) 0.00 
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    Source
    Journal of information science. 29(2003) no.2, S.87-96
  5. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.00 
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    Date
    30. 3.2001 13:32:22
  6. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.00 
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    Date
    25. 8.2005 17:42:22
  7. Okada, M.; Ando, K.; Lee, S.S.; Hayashi, Y.; Aoe, J.I.: ¬An efficient substring search method by using delayed keyword extraction (2001) 0.00 
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    Date
    29. 3.2002 17:24:03
  8. Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998) 0.00 
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    Date
    11. 8.2001 14:48:29
  9. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.00 
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    Date
    14. 6.2015 22:12:44
  10. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.00 
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    Date
    14. 6.2015 22:12:56
  11. Wilhelmy, A.: Phonetische Ähnlichkeitssuche in Datenbanken (1991) 0.00 
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    Abstract
    In dialoggesteuerten Systemen zur Informationswiedergewinnung (Information Retrieval Systems, IRS) kann man - vergröbernd - das Wechselspiel zwischen Mensch und Computer als iterativen Prozess zur Erhöhung von Genauigkeit (Precision) auf der einen und Vollständigkeit (Recall) der Nachweise auf der anderen Seite verstehen. Vorgestellt wird ein maschinell anwendbares Verfahren, das auf phonologische Untersuchungen des Sprachwissenschaftlers Nikolaj S. Trubetzkoy (1890-1938) zurückgeht. In den Grundzügen kann es erheblich zur Verbesserung der Nachweisvollständigkeit beitragen. Dadurch, daß es die 'Ähnlichkeitsumgebungen' von Suchbegriffen in die Recherche mit einbezieht, zeigt es sich vor allem für Systeme mit koordinativer maschineller Indexierung als vorteilhaft. Bei alphabetischen Begriffen erweist sich die Einführung eines solchen zunächst nur auf den Benutzer hin orientierten Verfahrens auch aus technischer Sicht als günstig, da damit die Anzahl der Zugriffe bei den Suchvorgängen auch für große Datenvolumina niedrig gehalten werden kann
  12. Fichtner, K.: Boyer-Moore Suchalgorithmus (2005) 0.00 
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    Abstract
    Die Masse der Suchalgorithmen lässt sich in zwei grundlegend verschiedene Teilbereiche untergliedern. Auf der einen Seite stehen Algorithmen, die auf komplexen Datenstrukturen (häufig baumartig) ganze Datensätze unter Verwendung eines Indizes finden. Als geläufiger Vertreter sei hier die binäre Suche auf sortierten Arrays oder in binären Bäumen genannt. Die andere Gruppe, der sich diese Ausarbeitung widmet, dient dazu, Entsprechungen von Mustern in gegebenen Zeichenketten zu finden. Auf den folgenden Seiten werden nun zunächst einige Begriffe eingeführt, die für das weitere Verständnis und einen Vergleich verschiedener Suchalgorithmen nötig sind. Weiterhin wird ein naiver Suchalgorithmus dargestellt und mit der Idee von Boyer und Moore verglichen. Hierzu wird ihr Algorithmus zunächst informal beschrieben, dann mit Blick auf eine Implementation näher erläutert und anschließend einer Effizienzanalyse - sowohl empirisch als auch theoretisch - unterzogen. Abschließend findet eine kurze Bewertung mit Bezug auf Schwachstellen, Vorzüge und Verbesserungsmöglichkeiten statt, im Zuge derer einige prominente Modifikationen des Boyer-Moore Algorithmus vorgestellt werden.
  13. Zhang, W.; Korf, R.E.: Performance of linear-space search algorithms (1995) 0.00 
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    Date
    2. 8.1996 10:29:15
  14. Hüther, H.: Selix im DFG-Projekt Kascade (1998) 0.00 
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    Date
    25. 8.2000 19:55:29
  15. Langville, A.N.; Meyer, C.D.: Google's PageRank and beyond : the science of search engine rankings (2006) 0.00 
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    RSWK
    Google / Web-Seite / Rangstatistik (HEBIS)
    Subject
    Google / Web-Seite / Rangstatistik (HEBIS)
  16. Uratani, N.; Takeda, M.: ¬A fast string-searching algorithm for multiple patterns (1993) 0.00 
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    Source
    Information processing and management. 29(1993) no.6, S.775-791
  17. Chakrabarti, S.; Dom, B.; Kumar, S.R.; Raghavan, P.; Rajagopalan, S.; Tomkins, A.; Kleinberg, J.M.; Gibson, D.: Neue Pfade durch den Internet-Dschungel : Die zweite Generation von Web-Suchmaschinen (1999) 0.00 
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    Date
    31.12.1996 19:29:41
  18. Thompson, P.: Looking back: on relevance, probabilistic indexing and information retrieval (2008) 0.00 
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    Date
    31. 7.2008 19:58:29
  19. Vechtomova, O.; Karamuftuoglu, M.: Lexical cohesion and term proximity in document ranking (2008) 0.00 
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    Date
    1. 8.2008 12:29:05
  20. Maylein, L.; Langenstein, A.: Neues vom Relevanz-Ranking im HEIDI-Katalog der Universitätsbibliothek Heidelberg : Perspektiven für bibliothekarische Dienstleistungen (2013) 0.00 
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    Date
    29. 6.2013 18:06:23

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