Search (52 results, page 1 of 3)

0.025926981 = product of:
  0.06913862 = sum of:
    0.014174575 = weight(_text_:libraries in 1202) [ClassicSimilarity], result of:
      0.014174575 = score(doc=1202,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.1088852 = fieldWeight in 1202, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1202)
    0.02538763 = weight(_text_:case in 1202) [ClassicSimilarity], result of:
      0.02538763 = score(doc=1202,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.14572193 = fieldWeight in 1202, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1202)
    0.02957641 = weight(_text_:studies in 1202) [ClassicSimilarity], result of:
      0.02957641 = score(doc=1202,freq=4.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.18704411 = fieldWeight in 1202, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1202)
  0.375 = coord(3/8)

Abstract

The concept of c-space is proposed as a visualization schema relating containers of content to cataloging surrogates and classification structures. Possible applications of keyword vector clusters within c-space could include improved retrieval rates through the use of captioning within visual hierarchies, tracings of semantic bleeding among subclasses, and access to buried knowledge within subject-neutral publication containers. The Scholastica Project is described as one example, following a tradition of research dating back to the 1980's. Preliminary focus group assessment indicates that this type of classification rendering may offer digital library searchers enriched entry strategies and an expanded range of re-entry vocabularies. Those of us who work in traditional libraries typically assume that our systems of classification: Library of Congress Classification (LCC) and Dewey Decimal Classification (DDC), are descriptive rather than prescriptive. In other words, LCC classes and subclasses approximate natural groupings of texts that reflect an underlying order of knowledge, rather than arbitrary categories prescribed by librarians to facilitate efficient shelving. Philosophical support for this assumption has traditionally been found in a number of places, from the archetypal tree of knowledge, to Aristotelian categories, to the concept of discursive formations proposed by Michel Foucault. Gary P. Radford has elegantly described an encounter with Foucault's discursive formations in the traditional library setting: "Just by looking at the titles on the spines, you can see how the books cluster together...You can identify those books that seem to form the heart of the discursive formation and those books that reside on the margins. Moving along the shelves, you see those books that tend to bleed over into other classifications and that straddle multiple discursive formations. You can physically and sensually experience...those points that feel like state borders or national boundaries, those points where one subject ends and another begins, or those magical places where one subject has morphed into another..."
But what happens to this awareness in a digital library? Can discursive formations be represented in cyberspace, perhaps through diagrams in a visualization interface? And would such a schema be helpful to a digital library user? To approach this question, it is worth taking a moment to reconsider what Radford is looking at. First, he looks at titles to see how the books cluster. To illustrate, I scanned one hundred books on the shelves of a college library under subclass HT 101-395, defined by the LCC subclass caption as Urban groups. The City. Urban sociology. Of the first 100 titles in this sequence, fifty included the word "urban" or variants (e.g. "urbanization"). Another thirty-five used the word "city" or variants. These keywords appear to mark their titles as the heart of this discursive formation. The scattering of titles not using "urban" or "city" used related terms such as "town," "community," or in one case "skyscrapers." So we immediately see some empirical correlation between keywords and classification. But we also see a problem with the commonly used search technique of title-keyword. A student interested in urban studies will want to know about this entire subclass, and may wish to browse every title available therein. A title-keyword search on "urban" will retrieve only half of the titles, while a search on "city" will retrieve just over a third. There will be no overlap, since no titles in this sample contain both words. The only place where both words appear in a common string is in the LCC subclass caption, but captions are not typically indexed in library Online Public Access Catalogs (OPACs). In a traditional library, this problem is mitigated when the student goes to the shelf looking for any one of the books and suddenly discovers a much wider selection than the keyword search had led him to expect. But in a digital library, the issue of non-retrieval can be more problematic, as studies have indicated. Micco and Popp reported that, in a study funded partly by the U.S. Department of Education, 65 of 73 unskilled users searching for material on U.S./Soviet foreign relations found some material but never realized they had missed a large percentage of what was in the database.

0.019292213 = product of:
  0.07716885 = sum of:
    0.042312715 = weight(_text_:case in 3869) [ClassicSimilarity], result of:
      0.042312715 = score(doc=3869,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.24286987 = fieldWeight in 3869, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3869)
    0.034856133 = weight(_text_:studies in 3869) [ClassicSimilarity], result of:
      0.034856133 = score(doc=3869,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.22043361 = fieldWeight in 3869, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3869)
  0.25 = coord(2/8)

Abstract

The changes in KO systems induced by sociocultural influences may include those in both classificatory principles and cultural features. The proposed study will examine the Korean Decimal Classification (KDC)'s adaptation of the Dewey Decimal Classification (DDC) by comparing the two systems. This case manifests the sociocultural influences on KOSs in a cross-cultural context. Therefore, the study aims at an in-depth investigation of sociocultural influences by situating a KOS in a cross-cultural environment and examining the dynamics between two classification systems designed to organize information resources in two distinct sociocultural contexts. As a preceding stage of the comparison, the analysis was conducted on the changes that result from the meeting of different sociocultural feature in a descriptive method. The analysis aims to identify variations between the two schemes in comparison of the knowledge structures of the two classifications, in terms of the quantity of class numbers that represent concepts and their relationships in each of the individual main classes. The most effective analytic strategy to show the patterns of the comparison was visualizations of similarities and differences between the two systems. Increasing or decreasing tendencies in the class through various editions were analyzed. Comparing the compositions of the main classes and distributions of concepts in the KDC and DDC discloses the differences in their knowledge structures empirically. This phase of quantitative analysis and visualizing techniques generates empirical evidence leading to interpretation.

0.017544128 = product of:
  0.07017651 = sum of:
    0.02834915 = weight(_text_:libraries in 3195) [ClassicSimilarity], result of:
      0.02834915 = score(doc=3195,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.2177704 = fieldWeight in 3195, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.046875 = fieldNorm(doc=3195)
    0.04182736 = weight(_text_:studies in 3195) [ClassicSimilarity], result of:
      0.04182736 = score(doc=3195,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.26452032 = fieldWeight in 3195, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.046875 = fieldNorm(doc=3195)
  0.25 = coord(2/8)

Abstract

The scientific community's growing eagerness to make research data available to the public provides libraries - with our expertise in metadata and discovery - an interesting new opportunity. This paper details the in-house creation of a "data catalog" which describes datasets ranging from population-level studies like the US Census to small, specialized datasets created by researchers at our own institution. Based on Symfony2 and Solr, the data catalog provides a powerful search interface to help researchers locate the data that can help them, and an administrative interface so librarians can add, edit, and manage metadata elements at will. This paper will outline the successes, failures, and total redos that culminated in the current manifestation of our data catalog.

0.016720567 = product of:
  0.06688227 = sum of:
    0.05077526 = weight(_text_:case in 3693) [ClassicSimilarity], result of:
      0.05077526 = score(doc=3693,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.29144385 = fieldWeight in 3693, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.046875 = fieldNorm(doc=3693)
    0.01610701 = product of:
      0.03221402 = sum of:
        0.03221402 = weight(_text_:22 in 3693) [ClassicSimilarity], result of:
          0.03221402 = score(doc=3693,freq=2.0), product of:
            0.13876937 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03962768 = queryNorm
            0.23214069 = fieldWeight in 3693, 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=3693)
      0.5 = coord(1/2)
  0.25 = coord(2/8)

Date

22. 7.2010 19:36:46

0.01567913 = product of:
  0.06271652 = sum of:
    0.049294014 = weight(_text_:studies in 4641) [ClassicSimilarity], result of:
      0.049294014 = score(doc=4641,freq=4.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.3117402 = fieldWeight in 4641, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4641)
    0.013422508 = product of:
      0.026845016 = sum of:
        0.026845016 = weight(_text_:22 in 4641) [ClassicSimilarity], result of:
          0.026845016 = score(doc=4641,freq=2.0), product of:
            0.13876937 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03962768 = queryNorm
            0.19345059 = fieldWeight in 4641, 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=4641)
      0.5 = coord(1/2)
  0.25 = coord(2/8)

Abstract

Studies on the state and structure of digital knowledge concerning science generally relate to macro and meso scales. Supported by visualizations, these studies can deliver knowledge about emerging scientific fields or collaboration between countries, scientific centers, or groups of researchers. Analyses of individual activities or single scientific career paths are rarely presented and discussed. The authors decided to fill this gap and developed a web application for visualizing the scientific output of particular researchers. This free software based on bibliographic data from local databases, provides six layouts for analysis. Researchers can see the dynamic characteristics of their own writing activity, the time and place of publication, and the thematic scope of research problems. They can also identify cooperation networks, and consequently, study the dependencies and regularities in their own scientific activity. The current article presents the results of a study of the application's usability and functionality as well as attempts to define different user groups. A survey about the interface was sent to select researchers employed at Nicolaus Copernicus University. The results were used to answer the question as to whether such a specialized visualization tool can significantly augment the individual information space of the contemporary researcher.

Date

21.12.2018 17:22:13

0.012549498 = product of:
  0.050197992 = sum of:
    0.023624292 = weight(_text_:libraries in 2559) [ClassicSimilarity], result of:
      0.023624292 = score(doc=2559,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.18147534 = fieldWeight in 2559, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2559)
    0.0265737 = product of:
      0.0531474 = sum of:
        0.0531474 = weight(_text_:area in 2559) [ClassicSimilarity], result of:
          0.0531474 = score(doc=2559,freq=2.0), product of:
            0.1952553 = queryWeight, product of:
              4.927245 = idf(docFreq=870, maxDocs=44218)
              0.03962768 = queryNorm
            0.27219442 = fieldWeight in 2559, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.927245 = idf(docFreq=870, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2559)
      0.5 = coord(1/2)
  0.25 = coord(2/8)

Abstract

Purpose - The purpose of this paper is to report an investigation into the ways in which Canadian digital library collections have incorporated knowledge organization systems into their search interfaces. Design/methodology/approach - A combination of data-gathering techniques was used. These were as follows: a review of the literature related to the application of knowledge organization systems, deep scanning of Canadian governmental and academic institutions web sites on the web, identify and contact researchers in the area of knowledge organization, and identify and contact people in the governmental organizations who are involved in knowledge organization and information management. Findings - A total of 33 digital collections were identified that have made use of some type of knowledge organization system. Thesauri, subject heading lists and classification schemes were the widely used knowledge organization systems in the surveyed Canadian digital library collections. Research limitations/implications - The target population for this research was limited to governmental and academic digital library collections. Practical implications - An evaluation of the knowledge organization systems interfaces showed that searching, browsing and navigation facilities as well as bilingual features call for improvements. Originality/value - This research contributes to the following areas: digital libraries, knowledge organization systems and services and search interface design.

0.01206966 = product of:
  0.04827864 = sum of:
    0.034856133 = weight(_text_:studies in 5272) [ClassicSimilarity], result of:
      0.034856133 = score(doc=5272,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.22043361 = fieldWeight in 5272, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5272)
    0.013422508 = product of:
      0.026845016 = sum of:
        0.026845016 = weight(_text_:22 in 5272) [ClassicSimilarity], result of:
          0.026845016 = score(doc=5272,freq=2.0), product of:
            0.13876937 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03962768 = queryNorm
            0.19345059 = fieldWeight in 5272, 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=5272)
      0.5 = coord(1/2)
  0.25 = coord(2/8)

Abstract

This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.

Date

22. 7.2006 16:11:05

0.010989259 = product of:
  0.043957036 = sum of:
    0.035903532 = weight(_text_:case in 3035) [ClassicSimilarity], result of:
      0.035903532 = score(doc=3035,freq=4.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.20608193 = fieldWeight in 3035, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0234375 = fieldNorm(doc=3035)
    0.008053505 = product of:
      0.01610701 = sum of:
        0.01610701 = weight(_text_:22 in 3035) [ClassicSimilarity], result of:
          0.01610701 = score(doc=3035,freq=2.0), product of:
            0.13876937 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03962768 = queryNorm
            0.116070345 = fieldWeight in 3035, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0234375 = fieldNorm(doc=3035)
      0.5 = coord(1/2)
  0.25 = coord(2/8)

Abstract

A PICTURE is said to be worth a thousand words. That metaphor might be expected to pertain a fortiori in the case of scientific papers, where a figure can brilliantly illuminate an idea that might otherwise be baffling. Papers with figures in them should thus be easier to grasp than those without. They should therefore reach larger audiences and, in turn, be more influential simply by virtue of being more widely read. But are they?

Content

As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.

0.008706411 = product of:
  0.034825645 = sum of:
    0.011812146 = weight(_text_:libraries in 1211) [ClassicSimilarity], result of:
      0.011812146 = score(doc=1211,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.09073767 = fieldWeight in 1211, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1211)
    0.0230135 = product of:
      0.046027 = sum of:
        0.046027 = weight(_text_:area in 1211) [ClassicSimilarity], result of:
          0.046027 = score(doc=1211,freq=6.0), product of:
            0.1952553 = queryWeight, product of:
              4.927245 = idf(docFreq=870, maxDocs=44218)
              0.03962768 = queryNorm
            0.23572728 = fieldWeight in 1211, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              4.927245 = idf(docFreq=870, maxDocs=44218)
              0.01953125 = fieldNorm(doc=1211)
      0.5 = coord(1/2)
  0.25 = coord(2/8)

Abstract

From the user's perspective, however, it is still difficult to use current information retrieval systems. Users frequently have problems expressing their information needs and translating those needs into queries. This is partly due to the fact that information needs cannot be expressed appropriately in systems terms. It is not unusual for users to input search terms that are different from the index terms information systems use. Various methods have been proposed to help users choose search terms and articulate queries. One widely used approach is to incorporate into the information system a thesaurus-like component that represents both the important concepts in a particular subject area and the semantic relationships among those concepts. Unfortunately, the development and use of thesauri is not without its own problems. The thesaurus employed in a specific information system has often been developed for a general subject area and needs significant enhancement to be tailored to the information system where it is to be used. This thesaurus development process, if done manually, is both time consuming and labor intensive. Usage of a thesaurus in searching is complex and may raise barriers for the user. For illustration purposes, let us consider two scenarios of thesaurus usage. In the first scenario the user inputs a search term and the thesaurus then displays a matching set of related terms. Without an overview of the thesaurus - and without the ability to see the matching terms in the context of other terms - it may be difficult to assess the quality of the related terms in order to select the correct term. In the second scenario the user browses the whole thesaurus, which is organized as in an alphabetically ordered list. The problem with this approach is that the list may be long, and neither does it show users the global semantic relationship among all the listed terms.
Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.

0.0074047255 = product of:
  0.059237804 = sum of:
    0.059237804 = weight(_text_:case in 4646) [ClassicSimilarity], result of:
      0.059237804 = score(doc=4646,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.34001783 = fieldWeight in 4646, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4646)
  0.125 = coord(1/8)

0.0073941024 = product of:
  0.05915282 = sum of:
    0.05915282 = weight(_text_:studies in 1718) [ClassicSimilarity], result of:
      0.05915282 = score(doc=1718,freq=4.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.37408823 = fieldWeight in 1718, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.046875 = fieldNorm(doc=1718)
  0.125 = coord(1/8)

Abstract

This review describes experimental designs (users, search tasks, measures, etc.) used by 31 controlled user studies of information visualization (IV) tools for textual information retrieval (IR) and a meta-analysis of the reported statistical effects. Comparable experimental designs allow research designers to compare their results with other reports, and support the development of experimentally verified design guidelines concerning which IV techniques are better suited to which types of IR tasks. The studies generally use a within-subject design with 15 or more undergraduate students performing browsing to known-item tasks on sets of at least 1,000 full-text articles or Web pages on topics of general interest/news. Results of the meta-analysis (N = 8) showed no significant effects of the IV tool as compared with a text-only equivalent, but the set shows great variability suggesting an inadequate basis of comparison. Experimental design recommendations are provided which would support comparison of existing IV tools for IR usability testing.

0.0070872875 = product of:
  0.0566983 = sum of:
    0.0566983 = weight(_text_:libraries in 3088) [ClassicSimilarity], result of:
      0.0566983 = score(doc=3088,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.4355408 = fieldWeight in 3088, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.09375 = fieldNorm(doc=3088)
  0.125 = coord(1/8)

0.0070872875 = product of:
  0.0566983 = sum of:
    0.0566983 = weight(_text_:libraries in 2553) [ClassicSimilarity], result of:
      0.0566983 = score(doc=2553,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.4355408 = fieldWeight in 2553, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.09375 = fieldNorm(doc=2553)
  0.125 = coord(1/8)

0.0063469075 = product of:
  0.05077526 = sum of:
    0.05077526 = weight(_text_:case in 3156) [ClassicSimilarity], result of:
      0.05077526 = score(doc=3156,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.29144385 = fieldWeight in 3156, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.046875 = fieldNorm(doc=3156)
  0.125 = coord(1/8)

Abstract

Gaining a rapid overview of an emerging scientific topic, sometimes called research fronts, is an increasingly common task due to the growing amount of interdisciplinary collaboration. Visual overviews that show temporal patterns of paper publication and citation links among papers can help researchers and analysts to see the rate of growth of topics, identify key papers, and understand influences across subdisciplines. This article applies a novel network-visualization tool based on meaningful layouts of nodes to present research fronts and show citation links that indicate influences across research fronts. To demonstrate the value of two-dimensional layouts with multiple regions and user control of link visibility, we conducted a design-oriented, preliminary case study with 6 domain experts over a 4-month period. The main benefits were being able (a) to easily identify key papers and see the increasing number of papers within a research front, and (b) to quickly see the strength and direction of influence across related research fronts.

0.0052890894 = product of:
  0.042312715 = sum of:
    0.042312715 = weight(_text_:case in 82) [ClassicSimilarity], result of:
      0.042312715 = score(doc=82,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.24286987 = fieldWeight in 82, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0390625 = fieldNorm(doc=82)
  0.125 = coord(1/8)

Abstract

Aggregated journal-journal citation networks based on the Journal Citation Reports 2004 of the Science Citation Index (5,968 journals) and the Social Science Citation Index (1,712 journals) are made accessible from the perspective of any of these journals. A vector-space model Is used for normalization, and the results are brought online at http://www.leydesdorff.net/jcr04 as input files for the visualization program Pajek. The user is thus able to analyze the citation environment in terms of links and graphs. Furthermore, the local impact of a journal is defined as its share of the total citations in the specific journal's citation environments; the vertical size of the nodes is varied proportionally to this citation impact. The horizontal size of each node can be used to provide the same information after correction for within-journal (self-)citations. In the "citing" environment, the equivalents of this measure can be considered as a citation activity index which maps how the relevant journal environment is perceived by the collective of authors of a given journal. As a policy application, the mechanism of Interdisciplinary developments among the sciences is elaborated for the case of nanotechnology journals.

0.0052890894 = product of:
  0.042312715 = sum of:
    0.042312715 = weight(_text_:case in 3366) [ClassicSimilarity], result of:
      0.042312715 = score(doc=3366,freq=2.0), product of:
        0.1742197 = queryWeight, product of:
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.03962768 = queryNorm
        0.24286987 = fieldWeight in 3366, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.3964143 = idf(docFreq=1480, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3366)
  0.125 = coord(1/8)

Abstract

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.

0.0047248583 = product of:
  0.037798867 = sum of:
    0.037798867 = weight(_text_:libraries in 317) [ClassicSimilarity], result of:
      0.037798867 = score(doc=317,freq=2.0), product of:
        0.13017908 = queryWeight, product of:
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.03962768 = queryNorm
        0.29036054 = fieldWeight in 317, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2850544 = idf(docFreq=4499, maxDocs=44218)
          0.0625 = fieldNorm(doc=317)
  0.125 = coord(1/8)

Source

Research and advanced technology for digital libraries : proceedings of the 12th European conference, ECDL '08, Aarhus, Denmark

0.0043570166 = product of:
  0.034856133 = sum of:
    0.034856133 = weight(_text_:studies in 2700) [ClassicSimilarity], result of:
      0.034856133 = score(doc=2700,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.22043361 = fieldWeight in 2700, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2700)
  0.125 = coord(1/8)

Abstract

Although information retrieval techniques used by Web search engines have improved substantially over the years, the results of Web searches have continued to be represented in simple list-based formats. Although the list-based representation makes it easy to evaluate a single document for relevance, it does not support the users in the broader tasks of manipulating or exploring the search results as they attempt to find a collection of relevant documents. HotMap is a meta-search system that provides a compact visual representation of Web search results at two levels of detail, and it supports interactive exploration via nested sorting of Web search results based on query term frequencies. An evaluation of the search results for a set of vague queries has shown that the re-sorted search results can provide a higher portion of relevant documents among the top search results. User studies show an increase in speed and effectiveness and a reduction in missed documents when comparing HotMap to the list-based representation used by Google. Subjective measures were positive, and users showed a preference for the HotMap interface. These results provide evidence for the utility of next-generation Web search results interfaces that promote interactive search results exploration.

0.0043570166 = product of:
  0.034856133 = sum of:
    0.034856133 = weight(_text_:studies in 4831) [ClassicSimilarity], result of:
      0.034856133 = score(doc=4831,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.22043361 = fieldWeight in 4831, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4831)
  0.125 = coord(1/8)

Abstract

In the 1950s, the "universe of knowledge" metaphor returned in discussions around the "first theory of faceted classification'; the Colon Classification (CC) of S.R. Ranganathan, to stress the differences within an "universe of concepts" system. Here we claim that the Universal Decimal Classification (UDC) has been either ignored or incorrectly represented in studies that focused on the pivotal role of Ranganathan in a transition from "top-down universe of concepts systems" to "bottom-up universe of concepts systems." Early 20th century designs from Paul Otlet reveal a two directional interaction between "elements" and "ensembles"that can be compared to the relations between the universe of knowledge and universe of concepts systems. Moreover, an unpublished manuscript with the title "Theorie schematique de la Classification" of 1908 includes sketches that demonstrate an exploration by Paul Otlet of the multidimensional characteristics of the UDC. The interactions between these one- and multidimensional representations of the UDC support Donker Duyvis' critical comments to Ranganathan who had dismissed it as a rigid hierarchical system in comparison to his own Colon Classification. A visualization of the experiments of the Knowledge Space Lab in which main categories of Wikipedia were mapped on the UDC provides empirical evidence of its faceted structure's flexibility.

0.0043570166 = product of:
  0.034856133 = sum of:
    0.034856133 = weight(_text_:studies in 1725) [ClassicSimilarity], result of:
      0.034856133 = score(doc=1725,freq=2.0), product of:
        0.15812531 = queryWeight, product of:
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.03962768 = queryNorm
        0.22043361 = fieldWeight in 1725, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.9902744 = idf(docFreq=2222, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1725)
  0.125 = coord(1/8)

Abstract

We sought to understand how users interpret meanings of symbols commonly used in information systems, especially how icons are processed by the brain. We investigated Chinese and English speakers' processing of 4 types of visual stimuli: icons, pictures, Chinese characters, and English words. The goal was to examine, via functional magnetic resonance imaging (fMRI) data, the hypothesis that people cognitively process icons as logographic words and to provide neurological evidence related to human-computer interaction (HCI), which has been rare in traditional information system studies. According to the neuroimaging data of 19 participants, we conclude that icons are not cognitively processed as logographical words like Chinese characters, although they both stimulate the semantic system in the brain that is needed for language processing. Instead, more similar to images and pictures, icons are not as efficient as words in conveying meanings, and brains (people) make more effort to process icons than words. We use this study to demonstrate that it is practicable to test information system constructs such as elements of graphical user interfaces (GUIs) with neuroscience data and that, with such data, we can better understand individual or group differences related to system usage and user-computer interactions.