Search (54 results, page 2 of 3)

0.015815454 = product of:
  0.04744636 = sum of:
    0.04744636 = weight(_text_:search in 2596) [ClassicSimilarity], result of:
      0.04744636 = score(doc=2596,freq=4.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.27153727 = fieldWeight in 2596, 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=2596)
  0.33333334 = coord(1/3)

Abstract

Purpose - To describe how information visualization can be used in the design of interface tools for large-scale repositories. Design/methodology/approach - One challenge for designers in the context of large-scale repositories is to create interface tools that help users find specific information of interest. In order to be most effective, these tools need to leverage the cognitive characteristics of the target users. At the Los Alamos National Laboratory, the authors' target users are scientists and engineers who can be characterized as higher-order, analytical thinkers. In this paper, the authors describe a visualization tool they have created for making the authors' large-scale digital object repositories more usable for them: SearchGraph, which facilitates data set analysis by displaying search results in the form of a two- or three-dimensional interactive scatter plot. Findings - Using SearchGraph, users can view a condensed, abstract visualization of search results. They can view the same dataset from multiple perspectives by manipulating several display, sort, and filter options. Doing so allows them to see different patterns in the dataset. For example, they can apply a logarithmic transformation in order to create more scatter in a dense cluster of data points or they can apply filters in order to focus on a specific subset of data points. Originality/value - SearchGraph is a creative solution to the problem of how to design interface tools for large-scale repositories. It is particularly appropriate for the authors' target users, who are scientists and engineers. It extends the work of the first two authors on ActiveGraph, a read-write digital library visualization tool.

0.015815454 = product of:
  0.04744636 = sum of:
    0.04744636 = weight(_text_:search in 3366) [ClassicSimilarity], result of:
      0.04744636 = score(doc=3366,freq=4.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.27153727 = fieldWeight in 3366, 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=3366)
  0.33333334 = coord(1/3)

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.

0.015656501 = product of:
  0.0469695 = sum of:
    0.0469695 = weight(_text_:search in 1528) [ClassicSimilarity], result of:
      0.0469695 = score(doc=1528,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.2688082 = fieldWeight in 1528, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1528)
  0.33333334 = coord(1/3)

0.015656501 = product of:
  0.0469695 = sum of:
    0.0469695 = weight(_text_:search in 5774) [ClassicSimilarity], result of:
      0.0469695 = score(doc=5774,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.2688082 = fieldWeight in 5774, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5774)
  0.33333334 = coord(1/3)

Abstract

The DeweyBrowser allows users to search and browse collections of library resources organized by the Dewey Decimal Classification (DDC) system. The visual interface provides access to several million records from the OCLC WorldCat database and to a collection of records derived from the abridged edition of DDC. The prototype was developed out of a desire to make the most of Dewey numbers assigned to library materials and to explore new ways of providing access to the DDC.

0.015656501 = product of:
  0.0469695 = sum of:
    0.0469695 = weight(_text_:search in 2385) [ClassicSimilarity], result of:
      0.0469695 = score(doc=2385,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.2688082 = fieldWeight in 2385, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2385)
  0.33333334 = coord(1/3)

Abstract

LyberWorld is a prototype IR user interface. It implements visualizations of an abstract information space: fulltext. The video demonstrates a visual user interface for the probabilistic fulltext retrieval system INQUERY. Visualizations are used to communicate information search and browsing activities in a natural way by applying metaphors of spatial navigation in abstract information spaces. Visualization tools for exploring information spaces and judging relevance of information items are introduced and an example session demonstrates the prototype. The presence of a spatial model in the user's mind is regarded as an essential contribution towards natural interaction and reduction of cognitive costs during retrieval dialogues.

0.014794002 = product of:
  0.044382006 = sum of:
    0.044382006 = weight(_text_:search in 1211) [ClassicSimilarity], result of:
      0.044382006 = score(doc=1211,freq=14.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.25399986 = fieldWeight in 1211, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1211)
  0.33333334 = coord(1/3)

Abstract

In this article we present a method for retrieving documents from a digital library through a visual interface based on automatically generated concepts. We used a vocabulary generation algorithm to generate a set of concepts for the digital library and a technique called the max-min distance technique to cluster them. Additionally, the concepts were visualized in a spring embedding graph layout to depict the semantic relationship among them. The resulting graph layout serves as an aid to users for retrieving documents. An online archive containing the contents of D-Lib Magazine from July 1995 to May 2002 was used to test the utility of an implemented retrieval and visualization system. We believe that the method developed and tested can be applied to many different domains to help users get a better understanding of online document collections and to minimize users' cognitive load during execution of search tasks. Over the past few years, the volume of information available through the World Wide Web has been expanding exponentially. Never has so much information been so readily available and shared among so many people. Unfortunately, the unstructured nature and huge volume of information accessible over networks have made it hard for users to sift through and find relevant information. To deal with this problem, information retrieval (IR) techniques have gained more intensive attention from both industrial and academic researchers. Numerous IR techniques have been developed to help deal with the information overload problem. These techniques concentrate on mathematical models and algorithms for retrieval. Popular IR models such as the Boolean model, the vector-space model, the probabilistic model and their variants are well established.
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.

Content

The JAVA applet is available at <http://ella.slis.indiana.edu/~junzhang/dlib/IV.html>. A prototype of this interface has been developed and is available at <http://ella.slis.indiana.edu/~junzhang/dlib/IV.html>. The D-Lib search interface is available at <http://www.dlib.org/Architext/AT-dlib2query.html>.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 2131) [ClassicSimilarity], result of:
      0.04025957 = score(doc=2131,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 2131, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=2131)
  0.33333334 = coord(1/3)

Abstract

This is a preprint to be published in the Extensions & Corrections to the UDC. The paper explains the basic functions of browsing and searching that need to be supported in relation to analytico-synthetic classifications such as Universal Decimal Classification (UDC), irrespective of any specific, real-life implementation. UDC is an example of a semi-faceted system that can be used, for instance, for both post-coordinate searching and hierarchical/facet browsing. The advantages of using a classification for IR, however, depend on the strength of the GUI, which should provide a user-friendly interface to classification browsing and searching. The power of this interface is in supporting visualisation that will 'convert' what is potentially a user-unfriendly indexing language based on symbols, to a subject presentation that is easy to understand, search and navigate. A summary of the basic functions of searching and browsing a classification that may be provided on a user-friendly interface is given and examples of classification browsing interfaces are provided.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 1202) [ClassicSimilarity], result of:
      0.04025957 = score(doc=1202,freq=8.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 1202, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0234375 = fieldNorm(doc=1202)
  0.33333334 = coord(1/3)

Abstract

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.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 1718) [ClassicSimilarity], result of:
      0.04025957 = score(doc=1718,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 1718, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=1718)
  0.33333334 = coord(1/3)

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.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 2503) [ClassicSimilarity], result of:
      0.04025957 = score(doc=2503,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 2503, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=2503)
  0.33333334 = coord(1/3)

Content

The aim of this study is to develop a software tool, VisuaLCSH, for effective searching, browsing, and maintenance of LCSH. This tool enables visualizing subject headings and hierarchical structures implied and embedded in LCSH. A conceptual framework for converting the hierarchical structure of headings in LCSH to an explicit tree structure is proposed, described, and implemented. The highlights of VisuaLCSH are summarized below: 1) revealing multiple aspects of a heading; 2) normalizing the hierarchical relationships in LCSH; 3) showing multi-level hierarchies in LCSH sub-trees; 4) improving the navigational function of LCSH in retrieval; and 5) enabling the implementation of generic search, i.e., the 'exploding' feature, in searching LCSH.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 3550) [ClassicSimilarity], result of:
      0.04025957 = score(doc=3550,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 3550, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=3550)
  0.33333334 = coord(1/3)

Abstract

Displaying aspects of "aboutness" by means of non-verbal representations, such as notations, symbols, or icons, or through rich visual displays, such as those of topic maps, can facilitate meaning-making, putting information in context, and situating it relative to other information. As the design of displays of web-enabled information has struggled to keep pace with a bourgeoning body of digital content, increasingly innovative approaches to organizing search results have warranted greater attention. Using Worldmapper as an example, this paper examines cartograms - a derivative of the data map which adds dimensionality to the geographic positioning of information - as one approach to representing and managing subject content, and to tracking the diffusion of knowledge across place and time.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 1847) [ClassicSimilarity], result of:
      0.04025957 = score(doc=1847,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 1847, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=1847)
  0.33333334 = coord(1/3)

Abstract

The present study reports on the information seeking processes in a visual context, referred to throughout as visual information seeking. This study synthesizes research throughout different, yet complementary, areas, each capable of contributing findings and understanding to visual information seeking. Methods previously applied for examining the visual information seeking process are reviewed, including interactive experiments, surveys, and various qualitative approaches. The methods and resulting findings are presented and structured according to generalized phases of existing information seeking models, which include the needs, actions, and assessments of users. A review of visual information needs focuses on need and thus query formulation; user actions, as reviewed, centers on search and browse behaviors and the observed trends, concluded by a survey of users' assessments of visual information as part of the interactive process. This separate examination, specific to a visual context, is significant; visual information can influence outcomes in an interactive process and presents variations in the types of needs, tasks, considerations, and decisions of users, as compared to information seeking in other contexts.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 2384) [ClassicSimilarity], result of:
      0.04025957 = score(doc=2384,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 2384, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=2384)
  0.33333334 = coord(1/3)

Abstract

LyberWorld is a prototype IR user interface. It implements visualizations of an abstract information space-fulltext. The paper derives a model for such visualizations and an exemplar user interface design is implemented for the probabilistic fulltext retrieval system INQUERY. Visualizations are used to communicate information search and browsing activities in a natural way by applying metaphors of spatial navigation in abstract information spaces. Visualization tools for exploring information spaces and judging relevance of information items are introduced and an example session demonstrates the prototype. The presence of a spatial model in the user's mind and interaction with a system's corresponding display methods is regarded as an essential contribution towards natural interaction and reduction of cognitive costs during e.g. query construction, orientation within the database content, relevance judgement and orientation within the retrieval context.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 3195) [ClassicSimilarity], result of:
      0.04025957 = score(doc=3195,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 3195, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=3195)
  0.33333334 = coord(1/3)

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.

0.013419857 = product of:
  0.04025957 = sum of:
    0.04025957 = weight(_text_:search in 5547) [ClassicSimilarity], result of:
      0.04025957 = score(doc=5547,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.230407 = fieldWeight in 5547, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.046875 = fieldNorm(doc=5547)
  0.33333334 = coord(1/3)

Abstract

Children seek information in order to complete school projects on a wide variety of topics, as well as to support their various leisure activities. Such information can be found in print documents, but increasingly young people are turning to the Web to meet their information needs. In order to exploit this resource, however, children must be able to search or browse digital information through the intermediation of an interface. In particular, they must use Web-based portals that in most cases have been designed for adult users. Guidelines for interface design are not hard to find, but typically they also postulate adult rather than juvenile users. The authors discuss their own research work that has focused upon what young people themselves have to say about the design of portal interfaces. They conclude that specific interface design guidelines are required for young users rather than simply relying upon general design guidelines, and that in order to formulate such guidelines it is necessary to actively include the young people themselves in this process.

0.012652363 = product of:
  0.037957087 = sum of:
    0.037957087 = weight(_text_:search in 3337) [ClassicSimilarity], result of:
      0.037957087 = score(doc=3337,freq=4.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.21722981 = fieldWeight in 3337, 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=3337)
  0.33333334 = coord(1/3)

Content

"Die Stadtbibliothek Reutlingen (www.stadtbibliothek-reutlingen.de) hat ihren gesamten Internetauftritt auf den Web-Opac Premium von BOND umgerüstet. Der WebOpac Premium ist weit mehr als ein gewöhnlicher Web-Opac. Vielmehr ist er ein Internet-Por-tal, in dessen Struktur alle Informationen und Angebote der Stadtbibliothek integriert sind. Mit dem Web-Opac Premium konnte die Bibliothek bei der Neugestaltung ihrer Internetseiten auf ein bestehendes und flexibel anpassbares Produkt zurückgreifen, um so Zeit und Arbeit zu sparen. Bestehende HTML-Seiten der alten Homepage wurden einfach in die neue Website übernommen. Zudem erhöhen viele Zusatzfunktionen des Web-Opac Premium die Attraktivität der Bibliothek. Neu ist auch die »Assoziative Suche« (Spider Search), mit der die Bibliotheksbenutzer bei der Mediensuche neue Sinnzusammenhänge erschließen und so ihre Suchergebnisse verbessern können. Für die übersichtliche Gliederung der Website sorgen die horizontale Navigationsleiste nach Abteilungen und Zweigstellen der Stadtbibliothek sowie ein blaues Navigationselement im linken Frame, das sich mit sprechenden Begriffen an alle Benutzer und bestimmte Zielgruppen der Bibliothek wendet. Unter dem Stichwort »Suche« können Leser sowohl nach Inhalten auf der Website als auch über drei Wege nach Medien suchen: über den Web-Opac der Stadtbibliothek, die Assoziative Mediensuche im Katalog der Bibliothek und in regionalen Katalogen, wie denen der Bibliothek der Fachhochschule Reutlingen, der UB oder der Stadtbücherei Tübingen. Der Bereich »Service« bietet viele Informationen zur Bibliothek und deren Benutzung. Unter »Meine Bibliothek« kann der Leser nach der Anmeldung sein Benutzerkonto einsehen, die Leihfrist der entliehenen Medien verlängern und sich sein persönliches Interessenprofil abspeichern. Das heißt der Leser legt gewünschte Stichwörter, Verfasser, Mediengruppen oder Interessenkreise fest und wird regelmäßig zu seinen Wunschthemen informiert. Der Bereich »Veranstaltungen« informiert über die aktuellen Veranstaltungen, untergliedert nach Kinderbibliothek, Hauptstelle und Zweigstellen. Das eingesetzte Veranstaltungsmodul des Web-Opacs Premium übernimmt die automatisierte Aktualisierung der angezeigten Veranstaltungen durch Angabe von Start- und Ablaufdatum."

Object

Spider Search

0.012652363 = product of:
  0.037957087 = sum of:
    0.037957087 = weight(_text_:search in 2547) [ClassicSimilarity], result of:
      0.037957087 = score(doc=2547,freq=4.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.21722981 = fieldWeight in 2547, 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=2547)
  0.33333334 = coord(1/3)

Abstract

The discovery service (a search engine and service called WILBERT) used at our library at the Technical University of Applied Sciences Wildau (TUAS Wildau) is comprised of more than 8 million items. If we were to record all licensed publications in this tool to a higher level of articles, including their bibliographic records and full texts, we would have a holding estimated at a hundred million documents. A lot of features, such as ranking, autocompletion, multi-faceted classification, refining opportunities reduce the number of hits. However, it is not enough to give intuitive support for a systematic overview of topics related to documents in the library. John Naisbitt once said: "We are drowning in information, but starving for knowledge." This quote is still very true today. Two years ago, we started to develop micro thesauri for MINT topics in order to develop an advanced indexing of the library stock. We use iQvoc as a vocabulary management system to create the thesaurus. It provides an easy-to-use browser interface that builds a SKOS thesaurus in the background. The purpose of this is to integrate the thesauri in WILBERT in order to offer a better subject-related search. This approach especially supports first-year students by giving them the possibility to browse through a hierarchical alignment of a subject, for instance, logistics or computer science, and thereby discover how the terms are related. It also supports the students with an insight into established abbreviations and alternative labels. Students at the TUAS Wildau were involved in the developmental process of the software regarding the interface and functionality of iQvoc. The first steps have been taken and involve the inclusion of 3000 terms in our discovery tool WILBERT.

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

0.011183213 = product of:
  0.03354964 = sum of:
    0.03354964 = weight(_text_:search in 1078) [ClassicSimilarity], result of:
      0.03354964 = score(doc=1078,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.19200584 = fieldWeight in 1078, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1078)
  0.33333334 = coord(1/3)

Abstract

In this article and two other articles which conceptualize a future stage of the research program (Leide, Cole, Large, & Beheshti, submitted for publication; Cole, Leide, Large, Beheshti, & Brooks, in preparation), we map-out a domain novice user's encounter with an IR system from beginning to end so that appropriate classification-based visualization schemes can be inserted into the encounter process. This article describes the visualization of a navigation classification scheme only. The navigation classification scheme uses the metaphor of a ship and ship's navigator traveling through charted (but unknown to the user) waters, guided by a series of lighthouses. The lighthouses contain mediation interfaces linking the user to the information store through agents created for each. The user's agent is the cognitive model the user has of the information space, which the system encourages to evolve via interaction with the system's agent. The system's agent is an evolving classification scheme created by professional indexers to represent the structure of the information store. We propose a more systematic, multidimensional approach to creating evolving classification/indexing schemes, based on where the user is and what she is trying to do at that moment during the search session.

0.011183213 = product of:
  0.03354964 = sum of:
    0.03354964 = weight(_text_:search in 10) [ClassicSimilarity], result of:
      0.03354964 = score(doc=10,freq=2.0), product of:
        0.1747324 = queryWeight, product of:
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.05027291 = queryNorm
        0.19200584 = fieldWeight in 10, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.475677 = idf(docFreq=3718, maxDocs=44218)
          0.0390625 = fieldNorm(doc=10)
  0.33333334 = coord(1/3)

Abstract

Recent efforts in biomedical visual question answering (VQA) research rely on combined information gathered from the image content and surrounding text supporting the figure. Biomedical journals are a rich source of information for such multimodal content indexing. For multipanel figures in these journals, it is critical to develop automatic figure panel splitting and label recognition algorithms to associate individual panels with text metadata in the figure caption and the body of the article. Challenges in this task include large variations in figure panel layout, label location, size, contrast to background, and so on. In this work, we propose a deep convolutional neural network, which splits the panels and recognizes the panel labels in a single step. Visual features are extracted from several layers at various depths of the backbone neural network and organized to form a feature pyramid. These features are fed into classification and regression networks to generate candidates of panels and their labels. These candidates are merged to create the final panel segmentation result through a beam search algorithm. We evaluated the proposed algorithm on the ImageCLEF data set and achieved better performance than the results reported in the literature. In order to thoroughly investigate the proposed algorithm, we also collected and annotated our own data set of 10,642 figures. The experiments, trained on 9,642 figures and evaluated on the remaining 1,000 figures, show that combining panel splitting and panel label recognition mutually benefit each other.