Search (6 results, page 1 of 1)

0.021121528 = product of:
  0.08448611 = sum of:
    0.08448611 = sum of:
      0.047486246 = weight(_text_:software in 1289) [ClassicSimilarity], result of:
        0.047486246 = score(doc=1289,freq=2.0), product of:
          0.18056466 = queryWeight, product of:
            3.9671519 = idf(docFreq=2274, maxDocs=44218)
            0.045514934 = queryNorm
          0.2629875 = fieldWeight in 1289, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.9671519 = idf(docFreq=2274, maxDocs=44218)
            0.046875 = fieldNorm(doc=1289)
      0.03699987 = weight(_text_:22 in 1289) [ClassicSimilarity], result of:
        0.03699987 = score(doc=1289,freq=2.0), product of:
          0.15938555 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.045514934 = queryNorm
          0.23214069 = fieldWeight in 1289, 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=1289)
  0.25 = coord(1/4)

Abstract

QVIZ will research and create a framework for visualizing and querying archival resources by a time-space interface based on maps and emergent knowledge structures. The framework will also integrate social software, such as wikis, in order to utilize knowledge in existing and new communities of practice. QVIZ will lead to improved information sharing and knowledge creation, easier access to information in a user-adapted context and innovative ways of exploring and visualizing materials over time, between countries and other administrative units. The common European framework for sharing and accessing archival information provided by the QVIZ project will open a considerably larger commercial market based on archival materials as well as a richer understanding of European history.

Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

0.0059357807 = product of:
  0.023743123 = sum of:
    0.023743123 = product of:
      0.047486246 = sum of:
        0.047486246 = weight(_text_:software in 3205) [ClassicSimilarity], result of:
          0.047486246 = score(doc=3205,freq=2.0), product of:
            0.18056466 = queryWeight, product of:
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.045514934 = queryNorm
            0.2629875 = fieldWeight in 3205, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.046875 = fieldNorm(doc=3205)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

The goal of Open Knowledge Maps is to create a visual interface to the world's scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps.

0.0039571873 = product of:
  0.01582875 = sum of:
    0.01582875 = product of:
      0.0316575 = sum of:
        0.0316575 = weight(_text_:software in 4746) [ClassicSimilarity], result of:
          0.0316575 = score(doc=4746,freq=2.0), product of:
            0.18056466 = queryWeight, product of:
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.045514934 = queryNorm
            0.17532499 = fieldWeight in 4746, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.03125 = fieldNorm(doc=4746)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Abstract

Many real-world domains can be represented as large node-link graphs: backbone Internet routers connect with 70,000 other hosts, mid-sized Web servers handle between 20,000 and 200,000 hyperlinked documents, and dictionaries contain millions of words defined in terms of each other. Computational manipulation of such large graphs is common, but previous tools for graph visualization have been limited to datasets of a few thousand nodes. Visual depictions of graphs and networks are external representations that exploit human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structure. We assert that the two key advantages of computer-based systems for information visualization over traditional paper-based visual exposition are interactivity and scalability. We also argue that designing visualization software by taking the characteristics of a target user's task domain into account leads to systems that are more effective and scale to larger datasets than previous work. This thesis contains a detailed analysis of three specialized systems for the interactive exploration of large graphs, relating the intended tasks to the spatial layout and visual encoding choices. We present two novel algorithms for specialized layout and drawing that use quite different visual metaphors. The H3 system for visualizing the hyperlink structures of web sites scales to datasets of over 100,000 nodes by using a carefully chosen spanning tree as the layout backbone, 3D hyperbolic geometry for a Focus+Context view, and provides a fluid interactive experience through guaranteed frame rate drawing. The Constellation system features a highly specialized 2D layout intended to spatially encode domain-specific information for computational linguists checking the plausibility of a large semantic network created from dictionaries. The Planet Multicast system for displaying the tunnel topology of the Internet's multicast backbone provides a literal 3D geographic layout of arcs on a globe to help MBone maintainers find misconfigured long-distance tunnels. Each of these three systems provides a very different view of the graph structure, and we evaluate their efficacy for the intended task. We generalize these findings in our analysis of the importance of interactivity and specialization for graph visualization systems that are effective and scalable.

0.0039571873 = product of:
  0.01582875 = sum of:
    0.01582875 = product of:
      0.0316575 = sum of:
        0.0316575 = weight(_text_:software in 1292) [ClassicSimilarity], result of:
          0.0316575 = score(doc=1292,freq=2.0), product of:
            0.18056466 = queryWeight, product of:
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.045514934 = queryNorm
            0.17532499 = fieldWeight in 1292, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.03125 = fieldNorm(doc=1292)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Content

Traditional print reference guides often have two methods of finding information: an order (alphabetical for dictionaries and encyclopedias, by subject hierarchy in the case of thesauri) and indices (ordered lists, with a more complete listing of words and concepts, which refers back to original content from the main body of the book). A user of such traditional print reference guides who is looking for information will either browse through the ordered information in the main body of the reference book, or scan through the indices to find what is necessary. The advent of the computer allows for much more rapid electronic searches of the same information, and for multiple layers of indices. Users can either search through information by entering a keyword, or users can browse through the information through an outline index, which represents the information contained in the main body of the data. There are two traditional user interfaces for such applications. First, the user may type text into a search field and in response, a list of results is returned to the user. The user then selects a returned entry and may page through the resulting information. Alternatively, the user may choose from a list of words from an index. For example, software thesaurus applications, in which a user attempts to find synonyms, antonyms, homonyms, etc. for a selected word, are usually implemented using the conventional search and presentation techniques discussed above. The presentation of results only allows for a one-dimensional order of data at any one time. In addition, only a limited number of results can be shown at once, and selecting a result inevitably leads to another page-if the result is not satisfactory, the users must search again. Finally, it is difficult to present information about the manner in which the search results are related, or to present quantitative information about the results without causing confusion. Therefore, there exists a need for a multidimensional graphical display of information, in particular with respect to information relating to the meaning of words and their relationships to other words. There further exists a need to present large amounts of information in a way that can be manipulated by the user, without the user losing his place. And there exists a need for more fluid, intuitive and powerful thesaurus functionality that invites the exploration of language.

0.0039571873 = product of:
  0.01582875 = sum of:
    0.01582875 = product of:
      0.0316575 = sum of:
        0.0316575 = weight(_text_:software in 2547) [ClassicSimilarity], result of:
          0.0316575 = score(doc=2547,freq=2.0), product of:
            0.18056466 = queryWeight, product of:
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.045514934 = queryNorm
            0.17532499 = fieldWeight in 2547, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.9671519 = idf(docFreq=2274, maxDocs=44218)
              0.03125 = fieldNorm(doc=2547)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

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.

0.0023124919 = product of:
  0.0092499675 = sum of:
    0.0092499675 = product of:
      0.018499935 = sum of:
        0.018499935 = weight(_text_:22 in 3035) [ClassicSimilarity], result of:
          0.018499935 = score(doc=3035,freq=2.0), product of:
            0.15938555 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045514934 = 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(1/4)

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.