Search (61 results, page 2 of 4)

  • × theme_ss:"Retrievalalgorithmen"
  1. Zhang, D.; Dong, Y.: ¬An effective algorithm to rank Web resources (2000) 0.00 
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    Theme
    Internet
  2. Notess, G.R.: Search engine relevance : the never-ending quest (2000) 0.00 
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    Abstract
    Bericht über verschiedene Relevanzverfahren der Suchdienste des Internet
  3. Mandl, T.: Web- und Multimedia-Dokumente : Neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen (2003) 0.00 
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    Abstract
    Die Menge an Daten im Internet steigt weiter rapide an. Damit wächst auch der Bedarf an qualitativ hochwertigen Information Retrieval Diensten zur Orientierung und problemorientierten Suche. Die Entscheidung für die Benutzung oder Beschaffung von Information Retrieval Software erfordert aussagekräftige Evaluierungsergebnisse. Dieser Beitrag stellt neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen vor und zeigt den Trend zu Spezialisierung und Diversifizierung von Evaluierungsstudien, die den Realitätsgrad derErgebnisse erhöhen. DerSchwerpunkt liegt auf dem Retrieval von Fachtexten, Internet-Seiten und Multimedia-Objekten.
  4. 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
  5. Oberhauser, O.; Labner, J.: Relevance Ranking in Online-Katalogen : Informationsstand und Perspektiven (2003) 0.00 
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    Abstract
    Bekanntlich führen Suchmaschinen wie Google &Co. beider Auflistung der Suchergebnisse ein "Ranking" nach "Relevanz" durch, d.h. die Dokumente werden in absteigender Reihenfolge entsprechend ihrer Erfüllung von Relevanzkriterien ausgeben. In Online-Katalogen (OPACs) ist derlei noch nicht allgemein übliche Praxis, doch bietet etwa das im Österreichischen Bibliothekenverbund eingesetzte System Aleph 500 tatsächlich eine solche Ranking-Option an (die im Verbundkatalog auch implementiert ist). Bislang liegen allerdings kaum Informationen zur Funktionsweise dieses Features, insbesondere auch im Hinblick auf eine Hilfestellung für Benutzer, vor. Daher möchten wir mit diesem Beitrag versuchen, den in unserem Verbund bestehenden Informationsstand zum Thema "Relevance Ranking" zu erweitern. Sowohl die Verwendung einer Ranking-Option in OPACs generell als auch die sich unter Aleph 500 konkret bietenden Möglichkeiten sollen im folgenden näher betrachtet werden.
  6. 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
  7. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.00 
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    Date
    14. 6.2015 22:12:44
  8. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.00 
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    Date
    14. 6.2015 22:12:56
  9. Wills, R.S.: Google's PageRank : the math behind the search engine (2006) 0.00 
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    Abstract
    Approximately 91 million American adults use the Internet on a typical day The number-one Internet activity is reading and writing e-mail. Search engine use is next in line and continues to increase in popularity. In fact, survey findings indicate that nearly 60 million American adults use search engines on a given day. Even though there are many Internet search engines, Google, Yahoo!, and MSN receive over 81% of all search requests. Despite claims that the quality of search provided by Yahoo! and MSN now equals that of Google, Google continues to thrive as the search engine of choice, receiving over 46% of all search requests, nearly double the volume of Yahoo! and over four times that of MSN. I use Google's search engine on a daily basis and rarely request information from other search engines. One day, I decided to visit the homepages of Google. Yahoo!, and MSN to compare the quality of search results. Coffee was on my mind that day, so I entered the simple query "coffee" in the search box at each homepage. Table 1 shows the top ten (unsponsored) results returned by each search engine. Although ordered differently, two webpages, www.peets.com and www.coffeegeek.com, appear in all three top ten lists. In addition, each pairing of top ten lists has two additional results in common. Depending on the information I hoped to obtain about coffee by using the search engines, I could argue that any one of the three returned better results: however, I was not looking for a particular webpage, so all three listings of search results seemed of equal quality. Thus, I plan to continue using Google. My decision is indicative of the problem Yahoo!, MSN, and other search engine companies face in the quest to obtain a larger percentage of Internet search volume. Search engine users are loyal to one or a few search engines and are generally happy with search results. Thus, as long as Google continues to provide results deemed high in quality, Google likely will remain the top search engine. But what set Google apart from its competitors in the first place? The answer is PageRank. In this article I explain this simple mathematical algorithm that revolutionized Web search.
  10. 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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  11. Abdelali, A.; Cowie, J.; Soliman, H.S.: Improving query precision using semantic expansion (2007) 0.00 
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    Abstract
    Query Expansion (QE) is one of the most important mechanisms in the information retrieval field. A typical short Internet query will go through a process of refinement to improve its retrieval power. Most of the existing QE techniques suffer from retrieval performance degradation due to imprecise choice of query's additive terms in the QE process. In this paper, we introduce a novel automated QE mechanism. The new expansion process is guided by the semantics relations between the original query and the expanding words, in the context of the utilized corpus. Experimental results of our "controlled" query expansion, using the Arabic TREC-10 data, show a significant enhancement of recall and precision over current existing mechanisms in the field.
  12. Torra, V.; Miyamoto, S.; Lanau, S.: Exploration of textual document archives using a fuzzy hierarchical clustering algorithm in the GAMBAL system (2005) 0.00 
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    Abstract
    The Internet, together with the large amount of textual information available in document archives, has increased the relevance of information retrieval related tools. In this work we present an extension of the Gambal system for clustering and visualization of documents based on fuzzy clustering techniques. The tool allows to structure the set of documents in a hierarchical way (using a fuzzy hierarchical structure) and represent this structure in a graphical interface (a 3D sphere) over which the user can navigate. Gambal allows the analysis of the documents and the computation of their similarity not only on the basis of the syntactic similarity between words but also based on a dictionary (Wordnet 1.7) and latent semantics analysis.
  13. Mandl, T.: Tolerantes Information Retrieval : Neuronale Netze zur Erhöhung der Adaptivität und Flexibilität bei der Informationssuche (2001) 0.00 
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    Abstract
    Ein wesentliches Bedürfnis im Rahmen der Mensch-Maschine-Interaktion ist die Suche nach Information. Um Information Retrieval (IR) Systeme kognitiv adäquat zu gestalten und sie an den Menschen anzupassen bieten sich Modelle des Soft Computing an. Ein umfassender state-of-the-art Bericht zu neuronalen Netzen im IR zeigt dass die meisten bestehenden Modelle das Potential neuronaler Netze nicht ausschöpfen. Das vorgestellte COSIMIR-Modell (Cognitive Similarity learning in Information Retrieval) basiert auf neuronalen Netzen und lernt, die Ähnlichkeit zwischen Anfrage und Dokument zu berechnen. Es trägt somit die kognitive Modellierung in den Kern eines IR Systems. Das Transformations-Netzwerk ist ein weiteres neuronales Netzwerk, das die Behandlung von Heterogenität anhand von Expertenurteilen lernt. Das COSIMIR-Modell und das Transformations-Netzwerk werden ausführlich diskutiert und anhand realer Datenmengen evaluiert
  14. Martin-Bautista, M.J.; Vila, M.-A.; Larsen, H.L.: ¬A fuzzy genetic algorithm approach to an adaptive information retrieval agent (1999) 0.00 
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    Abstract
    We present an approach to a Genetic Information Retrieval Agent filter (GIRAF) for documents from the Internet using a genetic algorithm (GA) with fuzzy set genes to learn the user's information needs. The population of chromosomes with fixed length represents such user's preferences. Each chromosome is associated with a fitness that may be considered the system's belief in the hypothesis that the chromosome, as a query, represents the user's information needs. In a chromosome, every gene characterizes documents by a keyword and an associated occurence frequency, represented by a certain type of a fuzzy subset of the set of positive integers. Based on the user's evaluation of the documents retrieved by the chromosome, compared to the scores computed by the system, the fitness of the chromosomes is adjusted. A prototype of GIRAF has been developed and tested. The results of the test are discussed, and some directions for further works are pointed out
  15. Stock, M.; Stock, W.G.: Internet-Suchwerkzeuge im Vergleich (IV) : Relevance Ranking nach "Popularität" von Webseiten: Google (2001) 0.00 
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  16. Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000) 0.00 
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    Abstract
    The rapid development of the Internet and World Wide Web has caused some critical problem for information retrieval. Researchers have made several attempts to solve these problems. Thesauri and subject heading lists as traditional information retrieval tools have been criticised for their efficiency to tackle these newly emerging problems. This paper proposes an information retrieval tool generated by cocitation analysis, comprising keyword clusters with relationships based on the co-occurrences of keywords in the literature. Such a tool can play the role of an associative thesaurus that can provide information about the keywords in a domain that might be useful for information searching and query expansion
  17. 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
  18. Faloutsos, C.: Signature files (1992) 0.00 
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    Date
    7. 5.1999 15:22:48
  19. 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
  20. 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

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