Search (19 results, page 1 of 1)

0.035786286 = product of:
  0.10735885 = sum of:
    0.10735885 = weight(_text_:search in 2567) [ClassicSimilarity], result of:
      0.10735885 = score(doc=2567,freq=32.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.6144187 = fieldWeight in 2567, product of:
          5.656854 = tf(freq=32.0), with freq of:
            32.0 = termFreq=32.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.03125 = fieldNorm(doc=2567)
  0.33333334 = coord(1/3)

Abstract

As the Web continues to grow and encompass broader and more diverse sources of information, providing effective search facilities to users becomes an increasingly challenging problem. To help users deal with the deluge of Web-accessible information, we propose a search system which makes use of context to improve search results in a scalable way. By context, we mean any sources of information, in addition to any search query, that provide clues about the user's true information need. For instance, a user's bookmarks and search history can be considered a part of the search context. We consider two types of context-based search. The first type of functionality we consider is "similarity search." In this case, as the user is browsing Web pages, URLs for pages similar to the current page are retrieved and displayed in a side panel. No query is explicitly issued; context alone (i.e., the page currently being viewed) is used to provide the user with useful related information. The second type of functionality involves taking search context into account when ranking results to standard search queries. Web search differs from traditional information retrieval tasks in several major ways, making effective context-sensitive Web search challenging. First, scalability is of critical importance. With billions of publicly accessible documents, the Web is much larger than traditional datasets. Similarly, with millions of search queries issued each day, the query load is much higher than for traditional information retrieval systems. Second, there are no guarantees on the quality ofWeb pages, with Web-authors taking an adversarial, rather than cooperative, approach in attempts to inflate the rankings of their pages. Third, there is a significant amount of metadata embodied in the link structure corresponding to the hyperlinks between Web pages that can be exploitedduring the retrieval process. In this thesis, we design a search system, using the Stanford WebBase platform, that exploits the link structure of the Web to provide scalable, context-sensitive search.

0.028291544 = product of:
  0.08487463 = sum of:
    0.08487463 = weight(_text_:search in 4569) [ClassicSimilarity], result of:
      0.08487463 = score(doc=4569,freq=20.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.48574063 = fieldWeight in 4569, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.03125 = fieldNorm(doc=4569)
  0.33333334 = coord(1/3)

Abstract

The results of this thesis are intended to support the information architect in designing a solution for improved search in a corporate environment. Specifically we have examined the type of search problems that require a domain model to enhance the search process. There are several approaches to modeling a domain. We have considered 3 different types of domain modeling schemes; taxonomy, thesaurus and ontology. The intention is to support the information architect in making an informed choice between one or more of these schemes. In our opinion the main criteria for this choice are the modeling characteristics of a scheme and the suitability for application in the search process. The second chapter is a discussion of modeling characteristics of each scheme, followed by a comparison between them. This should give an information architect an idea of which aspects of a domain can be modeled with each scheme. What is missing here is an indication of the effort required to model a domain with each scheme. There are too many factors that influence the amount of required effort, ranging from measurable factors like domain size and resource characteristics to cultural matters such as the willingness to share knowledge and the existence of a project champion in the team to keep the project running. The third chapter shows what role domain models can play in each part of the search process. This gives an idea of the problems that domain models can solve. We have split the search process into individual parts to show that domain models can be applied very differently in the process. The fourth chapter makes recommendations about the suitability of each individualdomain modeling scheme for improving search. Each scheme has particular characteristics that make it especially suitable for a domain or a search problem. In the appendix each case study is described in detail. These descriptions are intended to serve as a benchmark. The current problem of the enterprise can be compared to those described to see which case study is most similar, which solution was chosen, which problems arose and how they were dealt with. An important issue that we have not touched upon in this thesis is that of maintenance. The real problems of a domain model are revealed when it is applied in a search system and its deficits and wrong assumptions become clear. Adaptation and maintenance are always required. Unfortunately we have not been able to glean sufficient information about maintenance issues from our case studies to draw any meaningful conclusions.

0.017743714 = product of:
  0.053231142 = sum of:
    0.053231142 = product of:
      0.15969342 = sum of:
        0.15969342 = weight(_text_:3a in 701) [ClassicSimilarity], result of:
          0.15969342 = score(doc=701,freq=2.0), product of:
            0.4262143 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.05027291 = queryNorm
            0.3746787 = fieldWeight in 701, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.03125 = fieldNorm(doc=701)
      0.33333334 = coord(1/3)
  0.33333334 = coord(1/3)

Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

0.015893001 = product of:
  0.047679 = sum of:
    0.047679 = product of:
      0.095358 = sum of:
        0.095358 = weight(_text_:22 in 4635) [ClassicSimilarity], result of:
          0.095358 = score(doc=4635,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.5416616 = fieldWeight in 4635, 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=4635)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

26.11.2005 18:39:22

0.015815454 = product of:
  0.04744636 = sum of:
    0.04744636 = weight(_text_:search in 3222) [ClassicSimilarity], result of:
      0.04744636 = score(doc=3222,freq=4.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.27153727 = fieldWeight in 3222, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3222)
  0.33333334 = coord(1/3)

Abstract

The use of thesaurus-based indexing is a common approach for increasing the performance of information retrieval. In this thesis, we examine the suitability of a thesaurus for a given set of information and evaluate improvements of existing thesauri to get better search results. On this area, we focus on two aspects: 1. We demonstrate an analysis of the indexing results achieved by an automatic document indexer and the involved thesaurus. 2. We propose a method for thesaurus evaluation which is based on a combination of statistical measures and appropriate visualization techniques that support the detection of potential problems in a thesaurus. In this chapter, we give an overview of the context of our work. Next, we briefly outline the basics of thesaurus-based information retrieval and describe the Collexis Engine that was used for our experiments. In Chapter 3, we describe two experiments in automatically indexing documents in the areas of medicine and economics with corresponding thesauri and compare the results to available manual annotations. Chapter 4 describes methods for assessing thesauri and visualizing the result in terms of a treemap. We depict examples of interesting observations supported by the method and show that we actually find critical problems. We conclude with a discussion of open questions and future research in Chapter 5.

0.013622571 = product of:
  0.040867712 = sum of:
    0.040867712 = product of:
      0.081735425 = sum of:
        0.081735425 = weight(_text_:22 in 4865) [ClassicSimilarity], result of:
          0.081735425 = score(doc=4865,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.46428138 = fieldWeight in 4865, 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=4865)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 6.2002 19:41:59

0.013558928 = product of:
  0.040676784 = sum of:
    0.040676784 = weight(_text_:search in 127) [ClassicSimilarity], result of:
      0.040676784 = score(doc=127,freq=6.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.23279473 = fieldWeight in 127, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.02734375 = fieldNorm(doc=127)
  0.33333334 = coord(1/3)

Abstract

This thesis is organised as follows: Chapter 2 gives a general introduction to the field of information retrieval, covering its most important aspects. Further, the tasks of distributed and peer-to-peer information retrieval (P2PIR) are introduced, motivating their application and characterising the special challenges that they involve, including a review of existing architectures and search protocols in P2PIR. Finally, chapter 2 presents approaches to evaluating the e ectiveness of both traditional and peer-to-peer IR systems. Chapter 3 contains a detailed account of state-of-the-art information retrieval models and algorithms. This encompasses models for matching queries against document representations, term weighting algorithms, approaches to feedback and associative retrieval as well as distributed retrieval. It thus defines important terminology for the following chapters. The notion of "multi-level association graphs" (MLAGs) is introduced in chapter 4. An MLAG is a simple, graph-based framework that allows to model most of the theoretical and practical approaches to IR presented in chapter 3. Moreover, it provides an easy-to-grasp way of defining and including new entities into IR modeling, such as paragraphs or peers, dividing them conceptually while at the same time connecting them to each other in a meaningful way. This allows for a unified view on many IR tasks, including that of distributed and peer-to-peer search. Starting from related work and a formal defiition of the framework, the possibilities of modeling that it provides are discussed in detail, followed by an experimental section that shows how new insights gained from modeling inside the framework can lead to novel combinations of principles and eventually to improved retrieval effectiveness.
Chapter 5 empirically tackles the first of the two research questions formulated above, namely the question of global collection statistics. More precisely, it studies possibilities of radically simplified results merging. The simplification comes from the attempt - without having knowledge of the complete collection - to equip all peers with the same global statistics, making document scores comparable across peers. Chapter 5 empirically tackles the first of the two research questions formulated above, namely the question of global collection statistics. More precisely, it studies possibilities of radically simplified results merging. The simplification comes from the attempt - without having knowledge of the complete collection - to equip all peers with the same global statistics, making document scores comparable across peers. What is examined, is the question of how we can obtain such global statistics and to what extent their use will lead to a drop in retrieval effectiveness. In chapter 6, the second research question is tackled, namely that of making forwarding decisions for queries, based on profiles of other peers. After a review of related work in that area, the chapter first defines the approaches that will be compared against each other. Then, a novel evaluation framework is introduced, including a new measure for comparing results of a distributed search engine against those of a centralised one. Finally, the actual evaluation is performed using the new framework.

0.012652363 = product of:
  0.037957087 = sum of:
    0.037957087 = weight(_text_:search in 866) [ClassicSimilarity], result of:
      0.037957087 = score(doc=866,freq=4.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.21722981 = fieldWeight in 866, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.03125 = fieldNorm(doc=866)
  0.33333334 = coord(1/3)

Abstract

Mit der Entstehung des World Wide Web im Jahre 1989 und dem darauf folgenden rasanten Anstieg der Zahl an Webseiten, kam es sehr schnell zu der Notwendigkeit, eine gewisse Ordnung in die Vielzahl von Inhalten zu bringen. So wurde schon im Jahre 1991 ein erster Vorläufer der heutigen Websuchmaschinen namens Gopher entwickelt. Die Struktur von Gopher, bei der zunächst alle Webseiten katalogisiert wurden, um anschließend komplett durchsucht werden zu können, war damals richtungweisend und wird auch heute noch in den meisten anderen Websuchmaschinen verwendet. Von damals bis heute hat sich sehr viel am Markt der Suchmaschinen verändert. Seit dem Jahre 2004 gibt es nur mehr drei große Websuchmaschinen, bezogen auf die Anzahl erfasster Dokumente. Neben Yahoo! Search und Microsofts MSN Search ist Google die bisher erfolgreichste Suchmaschine der Welt. Dargestellt werden die Suchergebnisse, indem sie der Relevanz nach sortiert werden. Jede Suchmaschine hat ihre eigenen geheimen Kriterien, welche für die Bewertung der Relevanz herangezogen werden. Googles Suchergebnisse werden aus einer Kombination zweier Verfahren angeordnet. Neben der Hypertext-Matching-Analyse ist dies die PageRank-Technologie. Der so genannte PageRank-Algorithmus, benannt nach seinem Erfinder Lawrence Page, ist die wesentliche Komponente, die Google auf seinen Erfolgsweg gebracht hat. Über die genaue Funktionsweise dieses Algorithmus hat Google, insbesondere nach einigen Verbesserungen in den letzten Jahren, nicht alle Details preisgegeben. Fest steht jedoch, dass der PageRank-Algorithmus die Relevanz einer Webseite auf Basis der Hyperlinkstruktur des Webs berechnet, wobei die Relevanz einer Webseite danach gewichtet wird, wie viele Links auf sie zeigen und Verweise von ihrerseits stark verlinkten Seiten stärker ins Gewicht fallen.

0.011352143 = product of:
  0.03405643 = sum of:
    0.03405643 = product of:
      0.06811286 = sum of:
        0.06811286 = weight(_text_:22 in 3406) [ClassicSimilarity], result of:
          0.06811286 = score(doc=3406,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.38690117 = fieldWeight in 3406, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=3406)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

30. 5.2010 16:22:35

0.0096326135 = product of:
  0.028897839 = sum of:
    0.028897839 = product of:
      0.057795677 = sum of:
        0.057795677 = weight(_text_:22 in 4441) [ClassicSimilarity], result of:
          0.057795677 = score(doc=4441,freq=4.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.32829654 = fieldWeight in 4441, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=4441)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 2.2000 10:25:05

Series

Kölner Arbeitspapiere zur Bibliotheks- und Informationswissenschaft; Bd.22

0.009081715 = product of:
  0.027245143 = sum of:
    0.027245143 = product of:
      0.054490287 = sum of:
        0.054490287 = weight(_text_:22 in 1409) [ClassicSimilarity], result of:
          0.054490287 = score(doc=1409,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.30952093 = fieldWeight in 1409, 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=1409)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Nach der Veröffentlichung einer deutschen Übersetzung der Dewey Decimal Classification 22 im Oktober 2005 und ihrer Nutzung zur Inhaltserschließung in der Deutschen Nationalbibliographie seit Januar 2006 stellt sich aus Sicht der deutschen kunsthistorischen Spezialbibliotheken die Frage nach einer möglichen Verwendung der DDC und ihrer generellen Eignung zur Inhalterschließung kunsthistorischer Publikationen. Diese Frage wird vor dem Hintergrund der bestehenden bibliothekarischen Strukturen für die Kunstgeschichte sowie mit Blick auf die inhaltlichen Besonderheiten, die Forschungsmethodik und die publizistischen Traditionen dieses Faches erörtert.

0.0089465715 = product of:
  0.026839713 = sum of:
    0.026839713 = weight(_text_:search in 1742) [ClassicSimilarity], result of:
      0.026839713 = score(doc=1742,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.15360467 = fieldWeight in 1742, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.03125 = fieldNorm(doc=1742)
  0.33333334 = coord(1/3)

Abstract

While being theoretically so widely available, information can be restricted from a more general use by linguistic barriers. The linguistic aspects of the information languages and particularly the chances of an enhanced access to information by means of multilingual access facilities will make the substance of this thesis. The main problem of this research is thus to demonstrate that information retrieval can be improved by using multilingual thesaurus terms based on an intermediate or switching language to search with. Universal classification systems in general can play the role of switching languages for reasons dealt with in the forthcoming pages. The Universal Decimal Classification (UDC) in particular is the classification system used as example of a switching language for our objectives. The question may arise: why a universal classification system and not another thesaurus? Because the UDC like most of the classification systems uses symbols. Therefore, it is language independent and the problems of compatibility between such a thesaurus and different other thesauri in different languages are avoided. Another question may still arise? Why not then, assign running numbers to the descriptors in a thesaurus and make a switching language out of the resulting enumerative system? Because of some other characteristics of the UDC: hierarchical structure and terminological richness, consistency and control. One big problem to find an answer to is: can a thesaurus be made having as a basis a classification system in any and all its parts? To what extent this question can be given an affirmative answer? This depends much on the attributes of the universal classification system which can be favourably used to this purpose. Examples of different situations will be given and discussed upon beginning with those classes of UDC which are best fitted for building a thesaurus structure out of them (classes which are both hierarchical and faceted)...

0.0068112854 = product of:
  0.020433856 = sum of:
    0.020433856 = product of:
      0.040867712 = sum of:
        0.040867712 = weight(_text_:22 in 1746) [ClassicSimilarity], result of:
          0.040867712 = score(doc=1746,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.23214069 = fieldWeight in 1746, 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=1746)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 3.2015 9:17:30

0.0056760716 = product of:
  0.017028214 = sum of:
    0.017028214 = product of:
      0.03405643 = sum of:
        0.03405643 = weight(_text_:22 in 1482) [ClassicSimilarity], result of:
          0.03405643 = score(doc=1482,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.19345059 = fieldWeight in 1482, 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=1482)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 5.2005 18:25:26

0.0056760716 = product of:
  0.017028214 = sum of:
    0.017028214 = product of:
      0.03405643 = sum of:
        0.03405643 = weight(_text_:22 in 2460) [ClassicSimilarity], result of:
          0.03405643 = score(doc=2460,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.19345059 = fieldWeight in 2460, 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=2460)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Die ständig steigende Zahl an publizierter Information in immer neuen Formen verlangt besonders von Informations- und Dokumentationseinrichtungen immer präzisere Lösungen zur Erschließung dieser Informationen und ihrer benutzerfreundlichen Aufbereitung. Besonders im derzeitigen Zeitalter der Datenbanken und Online-Kataloge ist die Kombination von verbaler und klassifikatorischer Sacherschließung gefordert, ohne dabei die Verbindung zu den älteren, vielerorts noch (zumindest zusätzlich) in Verwendung befindlichen, Zettelkatalogen zu verlieren. Weltweit ist eine Vielzahl an verschiedenen Klassifikationen im Einsatz. Die Wahl der für eine Einrichtung passenden Klassifikation ist abhängig von ihrer thematischen und informationellen Ausrichtung, der Größe und Art der Bestände und nicht zuletzt von technischen und personellen Voraussetzungen. Auf Seiten der zu wählenden Klassifikation sind die Einfachheit der Handhabung für den Bibliothekar, die Verständlichkeit für den Benutzer, die Erweiterungsfähigkeit der Klassifikation durch das Aufkommen neuer Wissensgebiete und die Einbindung in informationelle Netze mit anderen Einrichtungen von entscheidender Bedeutung. In dieser Arbeit soll die Dewey Dezimalklassifikation (DDC) hinsichtlich dieser Punkte näher beleuchtet werden. Sie ist die weltweit am häufigsten benutzte Klassifikation. Etwa 200.000 Bibliotheken in 135 Ländern erschließen ihre Bestände mit diesem System. Sie liegt derzeit bereits in der 22. ungekürzten Auflage vor und wurde bisher in 30 Sprachen übersetzt. Eine deutsche Komplettübersetzung wird im Jahre 2005 erscheinen. Trotz teils heftig geführter Standardisierungsdebatten und Plänen für die Übernahme von amerikanischen Formalerschließungsregeln herrscht in Bezug auf die Sacherschließung unter deutschen Bibliotheken wenig Einigkeit. Die DDC ist in Deutschland und anderen europäischen Ländern kaum verbreitet, sieht von Großbritannien und von der Verwendung in Bibliografien ab. Diese Arbeit geht demzufolge auf die historischen Gründe dieser Entwicklung ein und wagt einen kurzen Ausblick in die Zukunft der Dezimalklassifikation.

0.0056760716 = product of:
  0.017028214 = sum of:
    0.017028214 = product of:
      0.03405643 = sum of:
        0.03405643 = weight(_text_:22 in 4333) [ClassicSimilarity], result of:
          0.03405643 = score(doc=4333,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.19345059 = fieldWeight in 4333, 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=4333)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Pages

22 S

0.0056760716 = product of:
  0.017028214 = sum of:
    0.017028214 = product of:
      0.03405643 = sum of:
        0.03405643 = weight(_text_:22 in 867) [ClassicSimilarity], result of:
          0.03405643 = score(doc=867,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.19345059 = fieldWeight in 867, 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=867)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Pages

22 S

0.0056760716 = product of:
  0.017028214 = sum of:
    0.017028214 = product of:
      0.03405643 = sum of:
        0.03405643 = weight(_text_:22 in 1670) [ClassicSimilarity], result of:
          0.03405643 = score(doc=1670,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.19345059 = fieldWeight in 1670, 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=1670)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

26. 9.2006 21:00:22

0.0056760716 = product of:
  0.017028214 = sum of:
    0.017028214 = product of:
      0.03405643 = sum of:
        0.03405643 = weight(_text_:22 in 642) [ClassicSimilarity], result of:
          0.03405643 = score(doc=642,freq=2.0), product of:
            0.17604718 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05027291 = queryNorm
            0.19345059 = fieldWeight in 642, 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=642)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 7.2022 12:16:58