Search (43 results, page 2 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  1. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.00
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    Date
    20. 1.2007 18:30:22
  2. Faloutsos, C.: Signature files (1992) 0.00
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    Date
    7. 5.1999 15:22:48
  3. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.00
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    Date
    22. 3.2003 19:27:23
  4. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.00
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    Date
    22. 8.2014 17:05:18
  5. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.00
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    Date
    13. 9.2014 14:45:22
  6. Ravana, S.D.; Rajagopal, P.; Balakrishnan, V.: Ranking retrieval systems using pseudo relevance judgments (2015) 0.00
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    Date
    20. 1.2015 18:30:22
    18. 9.2018 18:22:56
  7. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.00
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    Date
    1. 8.1996 22:08:06
  8. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.00
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    Date
    20. 3.2005 16:23:22
  9. Ackermann, J.: Knuth-Morris-Pratt (2005) 0.00
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    Abstract
    Im Rahmen des Seminars Suchmaschinen und Suchalgorithmen beschäftigt sich diese Arbeit mit dem Auffinden bestimmter Wörter oder Muster in Texten. Der Begriff "Text" wird hier in einem sehr allgemeinen Sinne als strukturierte Folge beliebiger Länge von Zeichen aus einem endlichen Alphabet verstanden. Somit fällt unter diesen Bereich ganz allgemein die Suche nach einem Muster in einer Sequenz von Zeichen. Beispiele hierfür sind neben der Suche von Wörtern in "literarischen" Texten, z.B. das Finden von Pixelfolgen in Bildern oder gar das Finden von Mustern in DNS-Strängen. Das Anwendungsgebiet für eine solche Suche ist weit gefächert. Man denke hier allein an Texteditoren, Literaturdatenbanken, digitale Lexika oder die besagte DNADatenbank. Betrachtet man allein das 1989 publizierte Oxford English Dictionary mit seinen etwa 616500 definierten Stichworten auf gedruckten 21728 Seiten, so gilt es, einen möglichst effizienten Algorithmus für die Suche in Texten zu nutzen. Der in der Arbeit zugrunde liegende Datentyp ist vom Typ String (Zeichenkette), wobei hier offen gelassen wird, wie der Datentyp programmtechnisch realisiert wird. Algorithmen zur Verarbeitung von Zeichenketten (string processing) umfassen ein bestimmtes Spektrum an Anwendungsgebieten [Ot96, S.617 f.], wie z.B. das Komprimieren, das Verschlüssen, das Analysieren (parsen), das Übersetzen von Texten sowie das Suchen in Texten, welches Thema dieses Seminars ist. Im Rahmen dieser Arbeit wird der Knuth-Morris-Pratt Algorithmus vorgestellt, der wie der ebenfalls in diesem Seminar vorgestellte Boyer-Moore Algorithmus einen effizienten Suchalgorithmus darstellt. Dabei soll ein gegebenes Suchwort oder Muster (pattern) in einer gegeben Zeichenkette erkannt werden (pattern matching). Gesucht werden dabei ein oder mehrere Vorkommen eines bestimmten Suchwortes (exact pattern matching). Der Knuth-Morris-Pratt Algorithmus wurde erstmals 1974 als Institutbericht der Stanford University beschrieben und erschien 1977 in der Fachzeitschrift Journal of Computing unter dem Titel "Fast Pattern Matching in Strings" [Kn77]. Der Algorithmus beschreibt eine Suche in Zeichenketten mit linearer Laufzeit. Der Name des Algorithmus setzt sich aus den Entwicklern des Algorithmus Donald E. Knuth, James H. Morris und Vaughan R. Pratt zusammen.
  10. Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996) 0.00
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    Date
    12. 9.1996 13:56:22
  11. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.00
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    Date
    31. 5.2004 19:22:06
  12. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.00
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    Date
    11. 9.2004 17:32:22
  13. Witschel, H.F.: Global term weights in distributed environments (2008) 0.00
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    Date
    1. 8.2008 9:44:22
  14. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.00
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    Date
    16.11.2008 16:22:48
  15. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.00
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    Date
    22. 3.2003 19:30:19
  16. Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995) 0.00
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    Date
    22. 2.1996 11:20:06
  17. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.00
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    Date
    22. 2.1996 13:14:10
  18. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.00
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    Date
    22. 3.2003 19:35:46
  19. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.00
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    Date
    22. 7.2006 16:32:43
  20. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.00
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    Date
    22. 3.2008 12:26:32

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