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  • × theme_ss:"Retrievalalgorithmen"
  1. Mandl, T.: Tolerantes Information Retrieval : Neuronale Netze zur Erhöhung der Adaptivität und Flexibilität bei der Informationssuche (2001) 0.01 
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    Footnote
    Rez. in: nfd - Information 54(2003) H.6, S.379-380 (U. Thiel): "Kannte G. Salton bei der Entwicklung des Vektorraummodells die kybernetisch orientierten Versuche mit assoziativen Speicherstrukturen? An diese und ähnliche Vermutungen, die ich vor einigen Jahren mit Reginald Ferber und anderen Kollegen diskutierte, erinnerte mich die Thematik des vorliegenden Buches. Immerhin lässt sich feststellen, dass die Vektorrepräsentation eine genial einfache Darstellung sowohl der im Information Retrieval (IR) als grundlegende Datenstruktur benutzten "inverted files" als auch der assoziativen Speichermatrizen darstellt, die sich im Laufe der Zeit Über Perzeptrons zu Neuronalen Netzen (NN) weiterentwickelten. Dieser formale Zusammenhang stimulierte in der Folge eine Reihe von Ansätzen, die Netzwerke im Retrieval zu verwenden, wobei sich, wie auch im vorliegenden Band, hybride Ansätze, die Methoden aus beiden Disziplinen kombinieren, als sehr geeignet erweisen. Aber der Reihe nach... Das Buch wurde vom Autor als Dissertation beim Fachbereich IV "Sprachen und Technik" der Universität Hildesheim eingereicht und resultiert aus einer Folge von Forschungsbeiträgen zu mehreren Projekten, an denen der Autor in der Zeit von 1995 bis 2000 an verschiedenen Standorten beteiligt war. Dies erklärt die ungewohnte Breite der Anwendungen, Szenarien und Domänen, in denen die Ergebnisse gewonnen wurden. So wird das in der Arbeit entwickelte COSIMIR Modell (COgnitive SIMilarity learning in Information Retrieval) nicht nur anhand der klassischen Cranfield-Kollektion evaluiert, sondern auch im WING-Projekt der Universität Regensburg im Faktenretrieval aus einer Werkstoffdatenbank eingesetzt. Weitere Versuche mit der als "Transformations-Netzwerk" bezeichneten Komponente, deren Aufgabe die Abbildung von Gewichtungsfunktionen zwischen zwei Termräumen ist, runden das Spektrum der Experimente ab. Aber nicht nur die vorgestellten Resultate sind vielfältig, auch der dem Leser angebotene "State-of-the-Art"-Überblick fasst in hoch informativer Breite Wesentliches aus den Gebieten IR und NN zusammen und beleuchtet die Schnittpunkte der beiden Bereiche. So werden neben den Grundlagen des Text- und Faktenretrieval die Ansätze zur Verbesserung der Adaptivität und zur Beherrschung von Heterogenität vorgestellt, während als Grundlagen Neuronaler Netze neben einer allgemeinen Einführung in die Grundbegriffe u.a. das Backpropagation-Modell, KohonenNetze und die Adaptive Resonance Theory (ART) geschildert werden. Einweiteres Kapitel stellt die bisherigen NN-orientierten Ansätze im IR vor und rundet den Abriss der relevanten Forschungslandschaft ab. Als Vorbereitung der Präsentation des COSIMIR-Modells schiebt der Autor an dieser Stelle ein diskursives Kapitel zum Thema Heterogenität im IR ein, wodurch die Ziele und Grundannahmen der Arbeit noch einmal reflektiert werden. Als Dimensionen der Heterogenität werden der Objekttyp, die Qualität der Objekte und ihrer Erschließung und die Mehrsprachigkeit genannt. Wenn auch diese Systematik im Wesentlichen die Akzente auf Probleme aus den hier tangierten Projekten legt, und weniger eine umfassende Aufbereitung z.B. der Literatur zum Problem der Relevanz anstrebt, ist sie dennoch hilfreich zum Verständnis der in den nachfolgenden Kapitel oft nur implizit angesprochenen Designentscheidungen bei der Konzeption der entwickelten Prototypen. Der Ansatz, Heterogenität durch Transformationen zu behandeln, wird im speziellen Kontext der NN konkretisiert, wobei andere Möglichkeiten, die z.B. Instrumente der Logik und Probabilistik einzusetzen, nur kurz diskutiert werden. Eine weitergehende Analyse hätte wohl auch den Rahmen der Arbeit zu weit gespannt,
  2. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.01 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  3. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.01 
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    Date
    30. 3.2001 13:32:22
  4. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.01 
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    Date
    25. 8.2005 17:42:22
  5. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.00 
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    Date
    14. 6.2015 22:12:44
  6. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.00 
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    Date
    14. 6.2015 22:12:56
  7. 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
  8. Faloutsos, C.: Signature files (1992) 0.00 
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    Date
    7. 5.1999 15:22:48
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.00 
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    Date
    20. 3.2005 16:23:22
  15. 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
  16. Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996) 0.00 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  17. Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003) 0.00 
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    22. 3.2003 19:27:36
  18. 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
  19. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.00 
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    11. 9.2004 17:32:22
  20. Witschel, H.F.: Global term weights in distributed environments (2008) 0.00 
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    Date
    1. 8.2008 9:44:22

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