Search (358 results, page 1 of 18)

  • × theme_ss:"Retrievalalgorithmen"
  1. Hüther, H.: Selix im DFG-Projekt Kascade (1998) 0.07 
    0.06660439 = product of:
  0.09990658 = sum of:
    0.035016708 = weight(_text_:h in 5151) [ClassicSimilarity], result of:
      0.035016708 = score(doc=5151,freq=4.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.3881952 = fieldWeight in 5151, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.078125 = fieldNorm(doc=5151)
    0.04301058 = weight(_text_:u in 5151) [ClassicSimilarity], result of:
      0.04301058 = score(doc=5151,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.3617784 = fieldWeight in 5151, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.078125 = fieldNorm(doc=5151)
    0.0053332755 = weight(_text_:a in 5151) [ClassicSimilarity], result of:
      0.0053332755 = score(doc=5151,freq=2.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.12739488 = fieldWeight in 5151, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.078125 = fieldNorm(doc=5151)
    0.016546011 = product of:
      0.04963803 = sum of:
        0.04963803 = weight(_text_:29 in 5151) [ClassicSimilarity], result of:
          0.04963803 = score(doc=5151,freq=2.0), product of:
            0.12771805 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03630739 = queryNorm
            0.38865322 = fieldWeight in 5151, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.078125 = fieldNorm(doc=5151)
      0.33333334 = coord(1/3)
  0.6666667 = coord(4/6)
    Date
    25. 8.2000 19:55:29
    Source
    Knowledge Management und Kommunikationssysteme: Proceedings des 6. Internationalen Symposiums für Informationswissenschaft (ISI '98) Prag, 3.-7. November 1998 / Hochschulverband für Informationswissenschaft (HI) e.V. Konstanz ; Fachrichtung Informationswissenschaft der Universität des Saarlandes, Saarbrücken. Hrsg.: Harald H. Zimmermann u. Volker Schramm
    Type
    a
  2. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.05 
    0.0468651 = product of:
  0.0937302 = sum of:
    0.06021481 = weight(_text_:u in 2134) [ClassicSimilarity], result of:
      0.06021481 = score(doc=2134,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.50648975 = fieldWeight in 2134, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.109375 = fieldNorm(doc=2134)
    0.010559348 = weight(_text_:a in 2134) [ClassicSimilarity], result of:
      0.010559348 = score(doc=2134,freq=4.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.25222903 = fieldWeight in 2134, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.109375 = fieldNorm(doc=2134)
    0.022956034 = product of:
      0.0688681 = sum of:
        0.0688681 = weight(_text_:22 in 2134) [ClassicSimilarity], result of:
          0.0688681 = score(doc=2134,freq=2.0), product of:
            0.1271423 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03630739 = queryNorm
            0.5416616 = fieldWeight in 2134, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.109375 = fieldNorm(doc=2134)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Date
    30. 3.2001 13:32:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  3. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.04 
    0.043589376 = product of:
  0.06538406 = sum of:
    0.017332384 = weight(_text_:h in 1319) [ClassicSimilarity], result of:
      0.017332384 = score(doc=1319,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.19214681 = fieldWeight in 1319, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1319)
    0.030107405 = weight(_text_:u in 1319) [ClassicSimilarity], result of:
      0.030107405 = score(doc=1319,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.25324488 = fieldWeight in 1319, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1319)
    0.0064662537 = weight(_text_:a in 1319) [ClassicSimilarity], result of:
      0.0064662537 = score(doc=1319,freq=6.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.1544581 = fieldWeight in 1319, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1319)
    0.011478017 = product of:
      0.03443405 = sum of:
        0.03443405 = weight(_text_:22 in 1319) [ClassicSimilarity], result of:
          0.03443405 = score(doc=1319,freq=2.0), product of:
            0.1271423 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03630739 = queryNorm
            0.2708308 = fieldWeight in 1319, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1319)
      0.33333334 = coord(1/3)
  0.6666667 = coord(4/6)
    Abstract
    Keyword based querying has been an immediate and efficient way to specify and retrieve related information that the user inquired. However, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given. Proposes an idea to integrate 2 existing techniques, query expansion and relevance feedback to achieve a concept-based information search for the Web
    Date
    1. 8.1996 22:08:06
    Footnote
    Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  4. Faloutsos, C.: Signature files (1992) 0.03 
    0.02802972 = product of:
  0.05605944 = sum of:
    0.03440846 = weight(_text_:u in 3499) [ClassicSimilarity], result of:
      0.03440846 = score(doc=3499,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.28942272 = fieldWeight in 3499, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0625 = fieldNorm(doc=3499)
    0.008533241 = weight(_text_:a in 3499) [ClassicSimilarity], result of:
      0.008533241 = score(doc=3499,freq=8.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.20383182 = fieldWeight in 3499, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0625 = fieldNorm(doc=3499)
    0.013117734 = product of:
      0.039353203 = sum of:
        0.039353203 = weight(_text_:22 in 3499) [ClassicSimilarity], result of:
          0.039353203 = score(doc=3499,freq=2.0), product of:
            0.1271423 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03630739 = queryNorm
            0.30952093 = fieldWeight in 3499, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=3499)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Abstract
    Presents a survey and discussion on signature-based text retrieval methods. It describes the main idea behind the signature approach and its advantages over other text retrieval methods, it provides a classification of the signature methods that have appeared in the literature, it describes the main representatives of each class, together with the relative advantages and drawbacks, and it gives a list of applications as well as commercial or university prototypes that use the signature approach
    Date
    7. 5.1999 15:22:48
    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
    Type
    a
  5. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.03 
    0.027894596 = product of:
  0.05578919 = sum of:
    0.029712658 = weight(_text_:h in 58) [ClassicSimilarity], result of:
      0.029712658 = score(doc=58,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.32939452 = fieldWeight in 58, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.09375 = fieldNorm(doc=58)
    0.0063999314 = weight(_text_:a in 58) [ClassicSimilarity], result of:
      0.0063999314 = score(doc=58,freq=2.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.15287387 = fieldWeight in 58, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.09375 = fieldNorm(doc=58)
    0.0196766 = product of:
      0.0590298 = sum of:
        0.0590298 = weight(_text_:22 in 58) [ClassicSimilarity], result of:
          0.0590298 = score(doc=58,freq=2.0), product of:
            0.1271423 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03630739 = queryNorm
            0.46428138 = fieldWeight in 58, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=58)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Date
    14. 6.2015 22:12:44
    Source
    Deutscher Dokumentartag 1985, Nürnberg, 1.-4.10.1985: Fachinformation: Methodik - Management - Markt; neue Entwicklungen, Berufe, Produkte. Bearb.: H. Strohl-Goebel
    Type
    a
  6. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.03 
    0.026744664 = product of:
  0.053489327 = sum of:
    0.036495686 = weight(_text_:u in 2419) [ClassicSimilarity], result of:
      0.036495686 = score(doc=2419,freq=4.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.30697915 = fieldWeight in 2419, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.046875 = fieldNorm(doc=2419)
    0.007155341 = weight(_text_:a in 2419) [ClassicSimilarity], result of:
      0.007155341 = score(doc=2419,freq=10.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.1709182 = fieldWeight in 2419, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=2419)
    0.0098383 = product of:
      0.0295149 = sum of:
        0.0295149 = weight(_text_:22 in 2419) [ClassicSimilarity], result of:
          0.0295149 = score(doc=2419,freq=2.0), product of:
            0.1271423 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03630739 = queryNorm
            0.23214069 = fieldWeight in 2419, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2419)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Abstract
    The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
    Date
    16.11.2008 16:22:48
    Source
    Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  7. Reimer, U.: Empfehlungssysteme (2023) 0.03 
    0.025586542 = product of:
  0.051173083 = sum of:
    0.017332384 = weight(_text_:h in 519) [ClassicSimilarity], result of:
      0.017332384 = score(doc=519,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.19214681 = fieldWeight in 519, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0546875 = fieldNorm(doc=519)
    0.030107405 = weight(_text_:u in 519) [ClassicSimilarity], result of:
      0.030107405 = score(doc=519,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.25324488 = fieldWeight in 519, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0546875 = fieldNorm(doc=519)
    0.0037332932 = weight(_text_:a in 519) [ClassicSimilarity], result of:
      0.0037332932 = score(doc=519,freq=2.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.089176424 = fieldWeight in 519, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0546875 = fieldNorm(doc=519)
  0.5 = coord(3/6)
    Abstract
    Mit der wachsenden Informationsflut steigen die Anforderungen an Informationssysteme, aus der Menge potenziell relevanter Information die in einem bestimmten Kontext relevanteste zu selektieren. Empfehlungssysteme spielen hier eine besondere Rolle, da sie personalisiert - d. h. kontextspezifisch und benutzerindividuell - relevante Information herausfiltern können. Definition: Ein Empfehlungssystem empfiehlt einem Benutzer bzw. einer Benutzerin in einem definierten Kontext aus einer gegebenen Menge von Empfehlungsobjekten eine Teilmenge als relevant. Empfehlungssysteme machen Benutzer auf Objekte aufmerksam, die sie möglicherweise nie gefunden hätten, weil sie nicht danach gesucht hätten oder sie in der schieren Menge an insgesamt relevanter Information untergegangen wären.
    Type
    a
  8. Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998) 0.02 
    0.023909008 = product of:
  0.047818016 = sum of:
    0.014856329 = weight(_text_:h in 5704) [ClassicSimilarity], result of:
      0.014856329 = score(doc=5704,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.16469726 = fieldWeight in 5704, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.046875 = fieldNorm(doc=5704)
    0.025806347 = weight(_text_:u in 5704) [ClassicSimilarity], result of:
      0.025806347 = score(doc=5704,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.21706703 = fieldWeight in 5704, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.046875 = fieldNorm(doc=5704)
    0.007155341 = weight(_text_:a in 5704) [ClassicSimilarity], result of:
      0.007155341 = score(doc=5704,freq=10.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.1709182 = fieldWeight in 5704, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=5704)
  0.5 = coord(3/6)
    Abstract
    Presents a neural network approach to document semantic indexing. Reports results of a study to apply a Hopfield net algorithm to simulate human associative memory for concept exploration in the domain of computer science and engineering. The INSPEC database, consisting of 320.000 abstracts from leading periodical articles was used as the document test bed. Benchmark tests conformed that 3 parameters: maximum number of activated nodes; maximum allowable error; and maximum number of iterations; were useful in positively influencing network convergence behaviour without negatively impacting central processing unit performance. Another series of benchmark tests was performed to determine the effectiveness of various filtering techniques in reducing the negative impact of noisy input terms. Preliminary user tests conformed expectations that the Hopfield net is potentially useful as an associative memory technique to improve document recall and precision by solving discrepancies between indexer vocabularies and end user vocabularies
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  9. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.02 
    0.022100132 = product of:
  0.044200264 = sum of:
    0.025806347 = weight(_text_:u in 5696) [ClassicSimilarity], result of:
      0.025806347 = score(doc=5696,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.21706703 = fieldWeight in 5696, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.046875 = fieldNorm(doc=5696)
    0.008466314 = weight(_text_:a in 5696) [ClassicSimilarity], result of:
      0.008466314 = score(doc=5696,freq=14.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.20223314 = fieldWeight in 5696, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=5696)
    0.009927606 = product of:
      0.029782817 = sum of:
        0.029782817 = weight(_text_:29 in 5696) [ClassicSimilarity], result of:
          0.029782817 = score(doc=5696,freq=2.0), product of:
            0.12771805 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03630739 = queryNorm
            0.23319192 = fieldWeight in 5696, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.046875 = fieldNorm(doc=5696)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Abstract
    Shows how probabilistic information retrieval based on document components may be implemented as a feedforward (feedbackward) artificial neural network. The network supports adaptation of connection weights as well as the growing of new edges between queries and terms based on user relevance feedback data for training, and it reflects query modification and expansion in information retrieval. A learning rule is applied that can also be viewed as supporting sequential learning using a harmonic sequence learning rate. Experimental results with 4 standard small collections and a large Wall Street Journal collection show that small query expansion levels of about 30 terms can achieve most of the gains at the low-recall high-precision region, while larger expansion levels continue to provide gains at the high-recall low-precision region of a precision recall curve
    Date
    29. 1.1996 18:42:14
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  10. Chen, H.; Lally, A.M.; Zhu, B.; Chau, M.: HelpfulMed : Intelligent searching for medical information over the Internet (2003) 0.02 
    0.020208735 = product of:
  0.04041747 = sum of:
    0.012380276 = weight(_text_:h in 1615) [ClassicSimilarity], result of:
      0.012380276 = score(doc=1615,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.13724773 = fieldWeight in 1615, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1615)
    0.02150529 = weight(_text_:u in 1615) [ClassicSimilarity], result of:
      0.02150529 = score(doc=1615,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.1808892 = fieldWeight in 1615, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1615)
    0.0065319026 = weight(_text_:a in 1615) [ClassicSimilarity], result of:
      0.0065319026 = score(doc=1615,freq=12.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.15602624 = fieldWeight in 1615, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1615)
  0.5 = coord(3/6)
    Abstract
    The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.
    Footnote
    Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  11. Liu, X.; Zheng, W.; Fang, H.: ¬An exploration of ranking models and feedback method for related entity finding (2013) 0.02 
    0.020208735 = product of:
  0.04041747 = sum of:
    0.012380276 = weight(_text_:h in 2714) [ClassicSimilarity], result of:
      0.012380276 = score(doc=2714,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.13724773 = fieldWeight in 2714, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2714)
    0.02150529 = weight(_text_:u in 2714) [ClassicSimilarity], result of:
      0.02150529 = score(doc=2714,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.1808892 = fieldWeight in 2714, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2714)
    0.0065319026 = weight(_text_:a in 2714) [ClassicSimilarity], result of:
      0.0065319026 = score(doc=2714,freq=12.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.15602624 = fieldWeight in 2714, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2714)
  0.5 = coord(3/6)
    Abstract
    Most existing search engines focus on document retrieval. However, information needs are certainly not limited to finding relevant documents. Instead, a user may want to find relevant entities such as persons and organizations. In this paper, we study the problem of related entity finding. Our goal is to rank entities based on their relevance to a structured query, which specifies an input entity, the type of related entities and the relation between the input and related entities. We first discuss a general probabilistic framework, derive six possible retrieval models to rank the related entities, and then compare these models both analytically and empirically. To further improve performance, we study the problem of feedback in the context of related entity finding. Specifically, we propose a mixture model based feedback method that can utilize the pseudo feedback entities to estimate an enriched model for the relation between the input and related entities. Experimental results over two standard TREC collections show that the derived relation generation model combined with a relation feedback method performs better than other models.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  12. Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008) 0.02 
    0.01987797 = product of:
  0.03975594 = sum of:
    0.02150529 = weight(_text_:u in 2393) [ClassicSimilarity], result of:
      0.02150529 = score(doc=2393,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.1808892 = fieldWeight in 2393, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2393)
    0.009977645 = weight(_text_:a in 2393) [ClassicSimilarity], result of:
      0.009977645 = score(doc=2393,freq=28.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.23833402 = fieldWeight in 2393, product of:
          5.2915025 = tf(freq=28.0), with freq of:
            28.0 = termFreq=28.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2393)
    0.0082730055 = product of:
      0.024819015 = sum of:
        0.024819015 = weight(_text_:29 in 2393) [ClassicSimilarity], result of:
          0.024819015 = score(doc=2393,freq=2.0), product of:
            0.12771805 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03630739 = queryNorm
            0.19432661 = fieldWeight in 2393, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2393)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Abstract
    This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.
    Date
    9.11.2008 13:07:29
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  13. 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) 0.02 
    0.01953958 = product of:
  0.03907916 = sum of:
    0.01980844 = weight(_text_:h in 3) [ClassicSimilarity], result of:
      0.01980844 = score(doc=3,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.21959636 = fieldWeight in 3, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0625 = fieldNorm(doc=3)
    0.006033913 = weight(_text_:a in 3) [ClassicSimilarity], result of:
      0.006033913 = score(doc=3,freq=4.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.14413087 = fieldWeight in 3, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0625 = fieldNorm(doc=3)
    0.013236808 = product of:
      0.03971042 = sum of:
        0.03971042 = weight(_text_:29 in 3) [ClassicSimilarity], result of:
          0.03971042 = score(doc=3,freq=2.0), product of:
            0.12771805 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03630739 = queryNorm
            0.31092256 = fieldWeight in 3, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0625 = fieldNorm(doc=3)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Date
    31.12.1996 19:29:41
    Source
    Spektrum der Wissenschaft. 1999, H.8, S.44-49
    Type
    a
  14. Maylein, L.; Langenstein, A.: Neues vom Relevanz-Ranking im HEIDI-Katalog der Universitätsbibliothek Heidelberg : Perspektiven für bibliothekarische Dienstleistungen (2013) 0.02 
    0.01953958 = product of:
  0.03907916 = sum of:
    0.01980844 = weight(_text_:h in 775) [ClassicSimilarity], result of:
      0.01980844 = score(doc=775,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.21959636 = fieldWeight in 775, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0625 = fieldNorm(doc=775)
    0.006033913 = weight(_text_:a in 775) [ClassicSimilarity], result of:
      0.006033913 = score(doc=775,freq=4.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.14413087 = fieldWeight in 775, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0625 = fieldNorm(doc=775)
    0.013236808 = product of:
      0.03971042 = sum of:
        0.03971042 = weight(_text_:29 in 775) [ClassicSimilarity], result of:
          0.03971042 = score(doc=775,freq=2.0), product of:
            0.12771805 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03630739 = queryNorm
            0.31092256 = fieldWeight in 775, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.0625 = fieldNorm(doc=775)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Date
    29. 6.2013 18:06:23
    Source
    B.I.T.online. 16(2013) H.3, S.190-200
    Type
    a
  15. Robertson, S.E.: ¬The probability ranking principle in IR (1977) 0.02 
    0.019337542 = product of:
  0.058012627 = sum of:
    0.051612694 = weight(_text_:u in 1935) [ClassicSimilarity], result of:
      0.051612694 = score(doc=1935,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.43413407 = fieldWeight in 1935, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.09375 = fieldNorm(doc=1935)
    0.0063999314 = weight(_text_:a in 1935) [ClassicSimilarity], result of:
      0.0063999314 = score(doc=1935,freq=2.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.15287387 = fieldWeight in 1935, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.09375 = fieldNorm(doc=1935)
  0.33333334 = coord(2/6)
    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willet. San Francisco: Morgan Kaufmann 1997. S.281-286.
    Type
    a
  16. Salton, G.; Buckley, C.: Term-weighting approaches in automatic text retrieval (1988) 0.02 
    0.019337542 = product of:
  0.058012627 = sum of:
    0.051612694 = weight(_text_:u in 1938) [ClassicSimilarity], result of:
      0.051612694 = score(doc=1938,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.43413407 = fieldWeight in 1938, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.09375 = fieldNorm(doc=1938)
    0.0063999314 = weight(_text_:a in 1938) [ClassicSimilarity], result of:
      0.0063999314 = score(doc=1938,freq=2.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.15287387 = fieldWeight in 1938, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.09375 = fieldNorm(doc=1938)
  0.33333334 = coord(2/6)
    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.323-328.
    Type
    a
  17. Sparck Jones, K.: Search term relevance weighting given little relevance information (1979) 0.02 
    0.019337542 = product of:
  0.058012627 = sum of:
    0.051612694 = weight(_text_:u in 1939) [ClassicSimilarity], result of:
      0.051612694 = score(doc=1939,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.43413407 = fieldWeight in 1939, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.09375 = fieldNorm(doc=1939)
    0.0063999314 = weight(_text_:a in 1939) [ClassicSimilarity], result of:
      0.0063999314 = score(doc=1939,freq=2.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.15287387 = fieldWeight in 1939, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.09375 = fieldNorm(doc=1939)
  0.33333334 = coord(2/6)
    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.329-338.
    Type
    a
  18. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.02 
    0.019274056 = product of:
  0.038548112 = sum of:
    0.02150529 = weight(_text_:u in 1428) [ClassicSimilarity], result of:
      0.02150529 = score(doc=1428,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.1808892 = fieldWeight in 1428, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1428)
    0.008844238 = weight(_text_:a in 1428) [ClassicSimilarity], result of:
      0.008844238 = score(doc=1428,freq=22.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.21126054 = fieldWeight in 1428, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1428)
    0.0081985835 = product of:
      0.02459575 = sum of:
        0.02459575 = weight(_text_:22 in 1428) [ClassicSimilarity], result of:
          0.02459575 = score(doc=1428,freq=2.0), product of:
            0.1271423 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03630739 = queryNorm
            0.19345059 = fieldWeight in 1428, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1428)
      0.33333334 = coord(1/3)
  0.5 = coord(3/6)
    Abstract
    Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing an theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept an the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based an semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.
    Date
    22. 3.2003 19:35:46
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  19. Bhansali, D.; Desai, H.; Deulkar, K.: ¬A study of different ranking approaches for semantic search (2015) 0.02 
    0.01925216 = product of:
  0.03850432 = sum of:
    0.012380276 = weight(_text_:h in 2696) [ClassicSimilarity], result of:
      0.012380276 = score(doc=2696,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.13724773 = fieldWeight in 2696, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2696)
    0.02150529 = weight(_text_:u in 2696) [ClassicSimilarity], result of:
      0.02150529 = score(doc=2696,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.1808892 = fieldWeight in 2696, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2696)
    0.0046187527 = weight(_text_:a in 2696) [ClassicSimilarity], result of:
      0.0046187527 = score(doc=2696,freq=6.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.11032722 = fieldWeight in 2696, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2696)
  0.5 = coord(3/6)
    Abstract
    Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  20. Xu, B.; Lin, H.; Lin, Y.: Assessment of learning to rank methods for query expansion (2016) 0.02 
    0.018828383 = product of:
  0.037656765 = sum of:
    0.012380276 = weight(_text_:h in 2929) [ClassicSimilarity], result of:
      0.012380276 = score(doc=2929,freq=2.0), product of:
        0.09020387 = queryWeight, product of:
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.03630739 = queryNorm
        0.13724773 = fieldWeight in 2929, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.4844491 = idf(docFreq=10020, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2929)
    0.02150529 = weight(_text_:u in 2929) [ClassicSimilarity], result of:
      0.02150529 = score(doc=2929,freq=2.0), product of:
        0.11888653 = queryWeight, product of:
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.03630739 = queryNorm
        0.1808892 = fieldWeight in 2929, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2744443 = idf(docFreq=4547, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2929)
    0.0037711957 = weight(_text_:a in 2929) [ClassicSimilarity], result of:
      0.0037711957 = score(doc=2929,freq=4.0), product of:
        0.041864127 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03630739 = queryNorm
        0.090081796 = fieldWeight in 2929, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2929)
  0.5 = coord(3/6)
    Abstract
    Pseudo relevance feedback, as an effective query expansion method, can significantly improve information retrieval performance. However, the method may negatively impact the retrieval performance when some irrelevant terms are used in the expanded query. Therefore, it is necessary to refine the expansion terms. Learning to rank methods have proven effective in information retrieval to solve ranking problems by ranking the most relevant documents at the top of the returned list, but few attempts have been made to employ learning to rank methods for term refinement in pseudo relevance feedback. This article proposes a novel framework to explore the feasibility of using learning to rank to optimize pseudo relevance feedback by means of reranking the candidate expansion terms. We investigate some learning approaches to choose the candidate terms and introduce some state-of-the-art learning to rank methods to refine the expansion terms. In addition, we propose two term labeling strategies and examine the usefulness of various term features to optimize the framework. Experimental results with three TREC collections show that our framework can effectively improve retrieval performance.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a

Authors

Years

Languages

Types

  • a 337
  • m 9
  • el 8
  • s 4
  • p 2
  • r 2
  • x 2
  • More… Less…

Themes

Subjects

Classifications