Search (23 results, page 1 of 2)

0.03779368 = product of:
  0.11338104 = sum of:
    0.10491812 = weight(_text_:ranking in 444) [ClassicSimilarity], result of:
      0.10491812 = score(doc=444,freq=6.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.51755315 = fieldWeight in 444, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.0390625 = fieldNorm(doc=444)
    0.008462917 = product of:
      0.025388751 = sum of:
        0.025388751 = weight(_text_:22 in 444) [ClassicSimilarity], result of:
          0.025388751 = score(doc=444,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.19345059 = fieldWeight in 444, 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=444)
      0.33333334 = coord(1/3)
  0.33333334 = coord(2/6)

Abstract

This paper aims to review the fiercely discussed question of whether the ranking of Wikipedia articles in search engines is justified by the quality of the articles. After an overview of current research on information quality in Wikipedia, a summary of the extended discussion on the quality of encyclopedic entries in general is given. On this basis, a heuristic method for evaluating Wikipedia entries is developed and applied to Wikipedia articles that scored highly in a search engine retrieval effectiveness test and compared with the relevance judgment of jurors. In all search engines tested, Wikipedia results are unanimously judged better by the jurors than other results on the corresponding results position. Relevance judgments often roughly correspond with the results from the heuristic evaluation. Cases in which high relevance judgments are not in accordance with the comparatively low score from the heuristic evaluation are interpreted as an indicator of a high degree of trust in Wikipedia. One of the systemic shortcomings of Wikipedia lies in its necessarily incoherent user model. A further tuning of the suggested criteria catalog, for instance, the different weighing of the supplied criteria, could serve as a starting point for a user model differentiated evaluation of Wikipedia articles. Approved methods of quality evaluation of reference works are applied to Wikipedia articles and integrated with the question of search engine evaluation.

Date

30. 9.2012 19:27:22

0.031401675 = product of:
  0.09420502 = sum of:
    0.085665286 = weight(_text_:ranking in 3593) [ClassicSimilarity], result of:
      0.085665286 = score(doc=3593,freq=4.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.42258036 = fieldWeight in 3593, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3593)
    0.008539738 = product of:
      0.025619213 = sum of:
        0.025619213 = weight(_text_:29 in 3593) [ClassicSimilarity], result of:
          0.025619213 = score(doc=3593,freq=2.0), product of:
            0.13183585 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03747799 = queryNorm
            0.19432661 = fieldWeight in 3593, 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=3593)
      0.33333334 = coord(1/3)
  0.33333334 = coord(2/6)

Abstract

We present the first systematic study of the influence of time on user judgements for rankings and relevance grades of web search engine results. The goal of this study is to evaluate the change in user assessment of search results and explore how users' judgements change. To this end, we conducted a large-scale user study with 86 participants who evaluated 2 different queries and 4 diverse result sets twice with an interval of 2 months. To analyze the results we investigate whether 2 types of patterns of user behavior from the theory of categorical thinking hold for the case of evaluation of search results: (a) coarseness and (b) locality. To quantify these patterns we devised 2 new measures of change in user judgements and distinguish between local (when users swap between close ranks and relevance values) and nonlocal changes. Two types of judgements were considered in this study: (a) relevance on a 4-point scale, and (b) ranking on a 10-point scale without ties. We found that users tend to change their judgements of the results over time in about 50% of cases for relevance and in 85% of cases for ranking. However, the majority of these changes were local.

Date

16.11.2017 13:33:29

0.021963246 = product of:
  0.06588974 = sum of:
    0.0599657 = weight(_text_:ranking in 2752) [ClassicSimilarity], result of:
      0.0599657 = score(doc=2752,freq=4.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.29580626 = fieldWeight in 2752, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2752)
    0.005924042 = product of:
      0.017772125 = sum of:
        0.017772125 = weight(_text_:22 in 2752) [ClassicSimilarity], result of:
          0.017772125 = score(doc=2752,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.1354154 = fieldWeight in 2752, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2752)
      0.33333334 = coord(1/3)
  0.33333334 = coord(2/6)

Content

Inhalt: Acknowledgments; Abstract; Zusammenfassung; Contents; List of Figures; List of Tables; List of Acronyms; Chapter 1 Introduction ; 1.1 Research Questions; 1.2 Thesis Outline; Part I Fundamentals ; Chapter 2 Information Retrieval for Young Users ; 2.1 Basics of Information Retrieval; 2.1.1 Architecture of an IR System; 2.1.2 Relevance Ranking; 2.1.3 Search User Interfaces; 2.1.4 Targeted Search Engines; 2.2 Aspects of Child Development Relevant for Information Retrieval Tasks; 2.2.1 Human Cognitive Development; 2.2.2 Information Processing Theory; 2.2.3 Psychosocial Development 2.3 User Studies and Evaluation2.3.1 Methods in User Studies; 2.3.2 Types of Evaluation; 2.3.3 Evaluation with Children; 2.4 Discussion; Chapter 3 State of the Art ; 3.1 Children's Information-Seeking Behaviour; 3.1.1 Querying Behaviour; 3.1.2 Search Strategy; 3.1.3 Navigation Style; 3.1.4 User Interface; 3.1.5 Relevance Judgement; 3.2 Existing Algorithms and User Interface Concepts for Children; 3.2.1 Query; 3.2.2 Content; 3.2.3 Ranking; 3.2.4 Search Result Visualisation; 3.3 Existing Information Retrieval Systems for Children; 3.3.1 Digital Book Libraries; 3.3.2 Web Search Engines 3.4 Summary and DiscussionPart II Studying Open Issues ; Chapter 4 Usability of Existing Search Engines for Young Users ; 4.1 Assessment Criteria; 4.1.1 Criteria for Matching the Motor Skills; 4.1.2 Criteria for Matching the Cognitive Skills; 4.2 Results; 4.2.1 Conformance with Motor Skills; 4.2.2 Conformance with the Cognitive Skills; 4.2.3 Presentation of Search Results; 4.2.4 Browsing versus Searching; 4.2.5 Navigational Style; 4.3 Summary and Discussion; Chapter 5 Large-scale Analysis of Children's Queries and Search Interactions; 5.1 Dataset; 5.2 Results; 5.3 Summary and Discussion Chapter 6 Differences in Usability and Perception of Targeted Web Search Engines between Children and Adults 6.1 Related Work; 6.2 User Study; 6.3 Study Results; 6.4 Summary and Discussion; Part III Tackling the Challenges ; Chapter 7 Search User Interface Design for Children ; 7.1 Conceptual Challenges and Possible Solutions; 7.2 Knowledge Journey Design; 7.3 Evaluation; 7.3.1 Study Design; 7.3.2 Study Results; 7.4 Voice-Controlled Search: Initial Study; 7.4.1 User Study; 7.5 Summary and Discussion; Chapter 8 Addressing User Diversity ; 8.1 Evolving Search User Interface 8.1.1 Mapping Function8.1.2 Evolving Skills; 8.1.3 Detection of User Abilities; 8.1.4 Design Concepts; 8.2 Adaptation of a Search User Interface towards User Needs; 8.2.1 Design & Implementation; 8.2.2 Search Input; 8.2.3 Result Output; 8.2.4 General Properties; 8.2.5 Configuration and Further Details; 8.3 Evaluation; 8.3.1 Study Design; 8.3.2 Study Results; 8.3.3 Preferred UI Settings; 8.3.4 User satisfaction; 8.4 Knowledge Journey Exhibit; 8.4.1 Hardware; 8.4.2 Frontend; 8.4.3 Backend; 8.5 Summary and Discussion; Chapter 9 Supporting Visual Searchers in Processing Search Results 9.1 Related Work

Date

1. 2.2016 18:25:22

0.020983625 = product of:
  0.12590174 = sum of:
    0.12590174 = weight(_text_:ranking in 2799) [ClassicSimilarity], result of:
      0.12590174 = score(doc=2799,freq=6.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.62106377 = fieldWeight in 2799, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.046875 = fieldNorm(doc=2799)
  0.16666667 = coord(1/6)

Abstract

With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.

0.020191502 = product of:
  0.121149 = sum of:
    0.121149 = weight(_text_:ranking in 2696) [ClassicSimilarity], result of:
      0.121149 = score(doc=2696,freq=8.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.5976189 = fieldWeight in 2696, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2696)
  0.16666667 = coord(1/6)

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.

0.018721774 = product of:
  0.11233064 = sum of:
    0.11233064 = weight(_text_:suchmaschine in 2605) [ClassicSimilarity], result of:
      0.11233064 = score(doc=2605,freq=4.0), product of:
        0.21191008 = queryWeight, product of:
          5.6542544 = idf(docFreq=420, maxDocs=44218)
          0.03747799 = queryNorm
        0.53008634 = fieldWeight in 2605, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          5.6542544 = idf(docFreq=420, maxDocs=44218)
          0.046875 = fieldNorm(doc=2605)
  0.16666667 = coord(1/6)

RSWK

Suchmaschine / Information Retrieval

Subject

Suchmaschine / Information Retrieval

0.018721774 = product of:
  0.11233064 = sum of:
    0.11233064 = weight(_text_:suchmaschine in 478) [ClassicSimilarity], result of:
      0.11233064 = score(doc=478,freq=4.0), product of:
        0.21191008 = queryWeight, product of:
          5.6542544 = idf(docFreq=420, maxDocs=44218)
          0.03747799 = queryNorm
        0.53008634 = fieldWeight in 478, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          5.6542544 = idf(docFreq=420, maxDocs=44218)
          0.046875 = fieldNorm(doc=478)
  0.16666667 = coord(1/6)

RSWK

Internet / Suchmaschine / Forschung / Aufsatzsammlung

Subject

Internet / Suchmaschine / Forschung / Aufsatzsammlung

0.017486354 = product of:
  0.10491812 = sum of:
    0.10491812 = weight(_text_:ranking in 3752) [ClassicSimilarity], result of:
      0.10491812 = score(doc=3752,freq=6.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.51755315 = fieldWeight in 3752, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3752)
  0.16666667 = coord(1/6)

Abstract

Web search engines act as gatekeepers when people search for information online. Research has shown that search engine users seem to trust the search engines' ranking uncritically and mostly select top-ranked results. This study further examines search engine users' selection behavior. Drawing from the credibility and information research literature, we test whether the presence or absence of certain credibility cues influences the selection probability of search engine results. In an observational study, participants (N?=?247) completed two information research tasks on preset search engine results pages, on which three credibility cues (source reputation, message neutrality, and social recommendations) as well as the search result ranking were systematically varied. The results of our study confirm the significance of the ranking. Of the three credibility cues, only reputation had an additional effect on selection probabilities. Personal characteristics (prior knowledge about the researched issues, search engine usage patterns, etc.) did not influence the preference for search results linked with certain credibility cues. These findings are discussed in light of situational and contextual characteristics (e.g., involvement, low-cost scenarios).

0.016153201 = product of:
  0.0969192 = sum of:
    0.0969192 = weight(_text_:ranking in 2563) [ClassicSimilarity], result of:
      0.0969192 = score(doc=2563,freq=8.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.47809508 = fieldWeight in 2563, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03125 = fieldNorm(doc=2563)
  0.16666667 = coord(1/6)

Abstract

To what extent can changes in PageRank's damping factor affect node ranking? We prove that, at least on some graphs, the top k nodes assume all possible k! orderings as the damping factor varies, even if it varies within an arbitrarily small interval (e.g. [0.84999,0.85001][0.84999,0.85001]). Thus, the rank of a node for a given (finite set of discrete) damping factor(s) provides very little information about the rank of that node as the damping factor varies over a continuous interval. We bypass this problem introducing lineage analysis and proving that there is a simple condition, with a "natural" interpretation independent of PageRank, that allows one to verify "in one shot" if a node outperforms another simultaneously for all damping factors and all damping variables (informally, time variant damping factors). The novel notions of strong rank and weak rank of a node provide a measure of the fuzziness of the rank of that node, of the objective orderability of a graph's nodes, and of the quality of results returned by different ranking algorithms based on the random surfer model. We deploy our analytical tools on a 41M node snapshot of the .it Web domain and on a 0.7M node snapshot of the CiteSeer citation graph. Among other findings, we show that rank is indeed relatively stable in both graphs; that "classic" PageRank (d=0.85) marginally outperforms Weighted In-degree (d->0), mainly due to its ability to ferret out "niche" items; and that, for both the Web and CiteSeer, the ideal damping factor appears to be 0.8-0.9 to obtain those items of high importance to at least one (model of randomly surfing) user, but only 0.5-0.6 to obtain those items important to every (model of randomly surfing) user.

Content

This paper addresses the fundamental question of how the ranking induced by PageRank can be affected by variations of the damping factor. This introduction briefly reviews the PageRank algorithm (Section 1.1) and the crucial difference between score and rank (Section 1.2) before presenting an overview of our results and the organization of the rest of the paper (Section 1.3). Vgl. auch: doi:10.1016/j.jda.2009.11.001. http://www.sciencedirect.com/science/article/pii/S1570866709000926.

0.013989083 = product of:
  0.08393449 = sum of:
    0.08393449 = weight(_text_:ranking in 393) [ClassicSimilarity], result of:
      0.08393449 = score(doc=393,freq=6.0), product of:
        0.20271951 = queryWeight, product of:
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03747799 = queryNorm
        0.4140425 = fieldWeight in 393, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          5.4090285 = idf(docFreq=537, maxDocs=44218)
          0.03125 = fieldNorm(doc=393)
  0.16666667 = coord(1/6)

Abstract

This study employed benchmarking and intellectual relevance judgment in evaluating Google, Yahoo!, Bing, Yahoo! Kids, and Ask Kids on 30 queries that children formulated to find information for specific tasks. Retrieved hits on given queries were benchmarked to Google's and Yahoo! Kids' top-five ranked hits retrieved. Relevancy of hits was judged on a graded scale; precision was calculated using the precision-at-ten metric (P@10). Yahoo! and Bing produced a similar percentage in hit overlap with Google (nearly 30%), but differed in the ranking of hits. Ask Kids retrieved 11% in hit overlap with Google versus 3% by Yahoo! Kids. The engines retrieved 26 hits across query clusters that overlapped with Yahoo! Kids' top-five ranked hits. Precision (P) that the engines produced across the queries was P = 0.48 for relevant hits, and P = 0.28 for partially relevant hits. Precision by Ask Kids was P = 0.44 for relevant hits versus P = 0.21 by Yahoo! Kids. Bing produced the highest total precision (TP) of relevant hits (TP = 0.86) across the queries, and Yahoo! Kids yielded the lowest (TP = 0.47). Average precision (AP) of relevant hits was AP = 0.56 by leading engines versus AP = 0.29 by small engines. In contrast, average precision of partially relevant hits was AP = 0.83 by small engines versus AP = 0.33 by leading engines. Average precision of relevant hits across the engines was highest on two-word queries and lowest on one-word queries. Google performed best on natural language queries; Bing did the same (P = 0.69) on two-word queries. The findings have implications for search engine ranking algorithms, relevance theory, search engine design, research design, and information literacy.

0.0022567778 = product of:
  0.013540667 = sum of:
    0.013540667 = product of:
      0.040622 = sum of:
        0.040622 = weight(_text_:22 in 1149) [ClassicSimilarity], result of:
          0.040622 = score(doc=1149,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.30952093 = fieldWeight in 1149, 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=1149)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

17.12.2013 11:02:22

0.0017079476 = product of:
  0.010247685 = sum of:
    0.010247685 = product of:
      0.030743055 = sum of:
        0.030743055 = weight(_text_:29 in 94) [ClassicSimilarity], result of:
          0.030743055 = score(doc=94,freq=2.0), product of:
            0.13183585 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03747799 = queryNorm
            0.23319192 = fieldWeight in 94, 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=94)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Pages

S.29-46

0.0016925833 = product of:
  0.0101555 = sum of:
    0.0101555 = product of:
      0.030466499 = sum of:
        0.030466499 = weight(_text_:22 in 93) [ClassicSimilarity], result of:
          0.030466499 = score(doc=93,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.23214069 = fieldWeight in 93, 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=93)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

17. 4.2012 14:25:22

0.0016925833 = product of:
  0.0101555 = sum of:
    0.0101555 = product of:
      0.030466499 = sum of:
        0.030466499 = weight(_text_:22 in 105) [ClassicSimilarity], result of:
          0.030466499 = score(doc=105,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.23214069 = fieldWeight in 105, 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=105)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

17. 4.2012 15:22:11

0.0016925833 = product of:
  0.0101555 = sum of:
    0.0101555 = product of:
      0.030466499 = sum of:
        0.030466499 = weight(_text_:22 in 108) [ClassicSimilarity], result of:
          0.030466499 = score(doc=108,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.23214069 = fieldWeight in 108, 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=108)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

20. 4.2012 13:19:22

0.0016925833 = product of:
  0.0101555 = sum of:
    0.0101555 = product of:
      0.030466499 = sum of:
        0.030466499 = weight(_text_:22 in 3246) [ClassicSimilarity], result of:
          0.030466499 = score(doc=3246,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.23214069 = fieldWeight in 3246, 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=3246)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

20. 1.2015 18:30:22

0.0014232898 = product of:
  0.008539738 = sum of:
    0.008539738 = product of:
      0.025619213 = sum of:
        0.025619213 = weight(_text_:29 in 3961) [ClassicSimilarity], result of:
          0.025619213 = score(doc=3961,freq=2.0), product of:
            0.13183585 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.03747799 = queryNorm
            0.19432661 = fieldWeight in 3961, 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=3961)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

29. 8.2010 13:11:47

0.0014104862 = product of:
  0.008462917 = sum of:
    0.008462917 = product of:
      0.025388751 = sum of:
        0.025388751 = weight(_text_:22 in 109) [ClassicSimilarity], result of:
          0.025388751 = score(doc=109,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.19345059 = fieldWeight in 109, 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=109)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

20. 4.2012 13:22:37

0.0014104862 = product of:
  0.008462917 = sum of:
    0.008462917 = product of:
      0.025388751 = sum of:
        0.025388751 = weight(_text_:22 in 1177) [ClassicSimilarity], result of:
          0.025388751 = score(doc=1177,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.19345059 = fieldWeight in 1177, 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=1177)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

26. 1.2014 18:48:22

0.0014104862 = product of:
  0.008462917 = sum of:
    0.008462917 = product of:
      0.025388751 = sum of:
        0.025388751 = weight(_text_:22 in 1605) [ClassicSimilarity], result of:
          0.025388751 = score(doc=1605,freq=2.0), product of:
            0.13124153 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03747799 = queryNorm
            0.19345059 = fieldWeight in 1605, 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=1605)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Source

Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22