Search (31 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Suchmaschinen"
  • × type_ss:"el"
  1. Smith, A.G.: Search features of digital libraries (2000) 0.01 
    0.011581604 = product of:
  0.02895401 = sum of:
    0.0136117125 = weight(_text_:information in 940) [ClassicSimilarity], result of:
      0.0136117125 = score(doc=940,freq=4.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.16457605 = fieldWeight in 940, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=940)
    0.015342298 = weight(_text_:und in 940) [ClassicSimilarity], result of:
      0.015342298 = score(doc=940,freq=2.0), product of:
        0.10442211 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.047114085 = queryNorm
        0.14692576 = fieldWeight in 940, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.046875 = fieldNorm(doc=940)
  0.4 = coord(2/5)
    Content
    Enthält eine Zusammenstellung der Werkzeuge und Hilfsmittel des Information Retrieval
    Source
    Information Research. 5(2000) no.3, April 2000
  2. Baeza-Yates, R.; Boldi, P.; Castillo, C.: Generalizing PageRank : damping functions for linkbased ranking algorithms (2006) 0.01 
    0.0095916195 = product of:
  0.02397905 = sum of:
    0.008020778 = weight(_text_:information in 2565) [ClassicSimilarity], result of:
      0.008020778 = score(doc=2565,freq=2.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.09697737 = fieldWeight in 2565, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2565)
    0.01595827 = product of:
      0.03191654 = sum of:
        0.03191654 = weight(_text_:22 in 2565) [ClassicSimilarity], result of:
          0.03191654 = score(doc=2565,freq=2.0), product of:
            0.1649855 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047114085 = queryNorm
            0.19345059 = fieldWeight in 2565, 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=2565)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Date
    16. 1.2016 10:22:28
    Source
    http://chato.cl/papers/baeza06_general_pagerank_damping_functions_link_ranking.pdf [Proceedings of the ACM Special Interest Group on Information Retrieval (SIGIR) Conference, SIGIR'06, August 6-10, 2006, Seattle, Washington, USA]
  3. Dunning, A.: Do we still need search engines? (1999) 0.01 
    0.0089366315 = product of:
  0.044683155 = sum of:
    0.044683155 = product of:
      0.08936631 = sum of:
        0.08936631 = weight(_text_:22 in 6021) [ClassicSimilarity], result of:
          0.08936631 = score(doc=6021,freq=2.0), product of:
            0.1649855 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047114085 = queryNorm
            0.5416616 = fieldWeight in 6021, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.109375 = fieldNorm(doc=6021)
      0.5 = coord(1/2)
  0.2 = coord(1/5)
    Source
    Ariadne. 1999, no.22
  4. Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011) 0.01 
    0.00832241 = product of:
  0.020806026 = sum of:
    0.008020778 = weight(_text_:information in 438) [ClassicSimilarity], result of:
      0.008020778 = score(doc=438,freq=2.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.09697737 = fieldWeight in 438, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=438)
    0.012785248 = weight(_text_:und in 438) [ClassicSimilarity], result of:
      0.012785248 = score(doc=438,freq=2.0), product of:
        0.10442211 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.047114085 = queryNorm
        0.12243814 = fieldWeight in 438, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0390625 = fieldNorm(doc=438)
  0.4 = coord(2/5)
    Abstract
    In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.
    Content
    Vgl.: http://swse.deri.org/ und http://swse.org/.
  5. Birmingham, J.: Internet search engines (1996) 0.01 
    0.0076599694 = product of:
  0.038299847 = sum of:
    0.038299847 = product of:
      0.076599695 = sum of:
        0.076599695 = weight(_text_:22 in 5664) [ClassicSimilarity], result of:
          0.076599695 = score(doc=5664,freq=2.0), product of:
            0.1649855 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047114085 = queryNorm
            0.46428138 = fieldWeight in 5664, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=5664)
      0.5 = coord(1/2)
  0.2 = coord(1/5)
    Date
    10.11.1996 16:36:22
  6. Kopp, O.: Google Hummingbird-Algorithmus-Update : Infos & Hintergründe (2013) 0.01 
    0.006200516 = product of:
  0.03100258 = sum of:
    0.03100258 = weight(_text_:und in 2522) [ClassicSimilarity], result of:
      0.03100258 = score(doc=2522,freq=6.0), product of:
        0.10442211 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.047114085 = queryNorm
        0.2968967 = fieldWeight in 2522, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2522)
  0.2 = coord(1/5)
    Abstract
    Pünktlich zum 15. Geburtstag der Google Suche verkündete Google gestern auf einer Pressekonferenz in der "Gründungs-Garage", dass das bedeutendste Google Update seit dem Caffeine Update im Jahr 2010 und größte Algorithmus-Update seit 2001 schon seit ca. einem Monat aktiv ist. Das aktuelle Update heißt Hummingbird zu deutsch Kollibri. Es soll ca. 90% aller Suchanfragen betreffen und soll im Vergleich zu Caffeine ein echtes Algorithmus-Update sein. Es soll dabei helfen komplexere Suchanfragen besser zu deuten und noch besser die eigentliche Suchintention bzw. Fragestellung hinter einer Suchanfrage zu erkennen sowie passende Dokumente dazu anzubieten. Auch auf Dokumentenebene soll die eigentliche Intention hinter dem Content besser mit der Suchanfrage gematcht werden.
  7. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01 
    0.005106646 = product of:
  0.025533231 = sum of:
    0.025533231 = product of:
      0.051066462 = sum of:
        0.051066462 = weight(_text_:22 in 1149) [ClassicSimilarity], result of:
          0.051066462 = score(doc=1149,freq=2.0), product of:
            0.1649855 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047114085 = queryNorm
            0.30952093 = fieldWeight in 1149, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=1149)
      0.5 = coord(1/2)
  0.2 = coord(1/5)
    Date
    17.12.2013 11:02:22
  8. Lossau, N.: Search engine technology and digital libraries : libraries need to discover the academic internet (2004) 0.00 
    0.004491636 = product of:
  0.02245818 = sum of:
    0.02245818 = weight(_text_:information in 1161) [ClassicSimilarity], result of:
      0.02245818 = score(doc=1161,freq=8.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.27153665 = fieldWeight in 1161, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1161)
  0.2 = coord(1/5)
    Abstract
    With the development of the World Wide Web, the "information search" has grown to be a significant business sector of a global, competitive and commercial market. Powerful players have entered this market, such as commercial internet search engines, information portals, multinational publishers and online content integrators. Will Google, Yahoo or Microsoft be the only portals to global knowledge in 2010? If libraries do not want to become marginalized in a key area of their traditional services, they need to acknowledge the challenges that come with the globalisation of scholarly information, the existence and further growth of the academic internet
    Theme
    Information Gateway
  9. ¬Der Google Hummingbird Algorithmus : semantisch-holistische Suche (2013) 0.00 
    0.0040912796 = product of:
  0.020456398 = sum of:
    0.020456398 = weight(_text_:und in 2521) [ClassicSimilarity], result of:
      0.020456398 = score(doc=2521,freq=2.0), product of:
        0.10442211 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.047114085 = queryNorm
        0.19590102 = fieldWeight in 2521, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0625 = fieldNorm(doc=2521)
  0.2 = coord(1/5)
    Abstract
    Im September 2013 verkündete Google den schon einen Monat vorher ausgerollten völlig neuen Algorithmus mit dem Namen "Hummingbird". Der Name wurde bewusst gewählt. Schließlich zeichnet den "Kolibri" seine äußerst schnelle und dabei doch präzise Methodik aus. Searchmetrics hat analysiert, wie sich der neue Algorithmus auf die SERPs auswirkt. Ergebnis: Die Diversität der Suchergebnisse hat abgenommen. Google zeigt zunehmend "gleichere" Resultate für semantisch äquivalente Queries an.
  10. Advanced online media use (2023) 0.00 
    0.0040912796 = product of:
  0.020456398 = sum of:
    0.020456398 = weight(_text_:und in 954) [ClassicSimilarity], result of:
      0.020456398 = score(doc=954,freq=2.0), product of:
        0.10442211 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.047114085 = queryNorm
        0.19590102 = fieldWeight in 954, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.0625 = fieldNorm(doc=954)
  0.2 = coord(1/5)
    Abstract
    Ten recommendations for the advanced use of online media. Mit Links auf historische und weiterführende Beiträge.
  11. Kriewel, S.; Klas, C.P.; Schaefer, A.; Fuhr, N.: DAFFODIL : strategic support for user-oriented access to heterogeneous digital libraries (2004) 0.00 
    0.003889871 = product of:
  0.019449355 = sum of:
    0.019449355 = weight(_text_:information in 4838) [ClassicSimilarity], result of:
      0.019449355 = score(doc=4838,freq=6.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.23515764 = fieldWeight in 4838, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4838)
  0.2 = coord(1/5)
    Abstract
    DAFFODIL is a search system for digital libraries aiming at strategic support during the information search process. From a user point of view this strategic support is mainly implemented by high-level search functions, so-called stratagems, which provide functionality beyond today's digital libraries. Through the tight integration of stratagems and with the federation of heterogeneous digital libraries, DAFFODIL reaches high effects of synergy for information and services. These effects provide high-quality metadata for the searcher through an intuitively controllable user interface. The implementation of stratagems follows a tool-based model.
    Theme
    Information Gateway
  12. Warnick, W.L.; Leberman, A.; Scott, R.L.; Spence, K.J.; Johnsom, L.A.; Allen, V.S.: Searching the deep Web : directed query engine applications at the Department of Energy (2001) 0.00 
    0.0038499737 = product of:
  0.019249868 = sum of:
    0.019249868 = weight(_text_:information in 1215) [ClassicSimilarity], result of:
      0.019249868 = score(doc=1215,freq=8.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.23274569 = fieldWeight in 1215, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=1215)
  0.2 = coord(1/5)
    Abstract
    Directed Query Engines, an emerging class of search engine specifically designed to access distributed resources on the deep web, offer the opportunity to create inexpensive digital libraries. Already, one such engine, Distributed Explorer, has been used to select and assemble high quality information resources and incorporate them into publicly available systems for the physical sciences. By nesting Directed Query Engines so that one query launches several other engines in a cascading fashion, enormous virtual collections may soon be assembled to form a comprehensive information infrastructure for the physical sciences. Once a Directed Query Engine has been configured for a set of information resources, distributed alerts tools can provide patrons with personalized, profile-based notices of recent additions to any of the selected resources. Due to the potentially enormous size and scope of Directed Query Engine applications, consideration must be given to issues surrounding the representation of large quantities of information from multiple, heterogeneous sources.
  13. Matrix of WWW indices : a comparison of Internet indexing tools (1995) 0.00 
    0.0032083113 = product of:
  0.016041556 = sum of:
    0.016041556 = weight(_text_:information in 3165) [ClassicSimilarity], result of:
      0.016041556 = score(doc=3165,freq=2.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.19395474 = fieldWeight in 3165, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.078125 = fieldNorm(doc=3165)
  0.2 = coord(1/5)
    Imprint
    Ann Arbor : University of Michigan School of Information and Library Studies
  14. Internet search tool details (1996) 0.00 
    0.0032083113 = product of:
  0.016041556 = sum of:
    0.016041556 = weight(_text_:information in 5677) [ClassicSimilarity], result of:
      0.016041556 = score(doc=5677,freq=2.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.19395474 = fieldWeight in 5677, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.078125 = fieldNorm(doc=5677)
  0.2 = coord(1/5)
    Abstract
    Summaries of the popular engines extrated from the search sites. Summaries are from: AltaVista, Excite, HotBot, InfoSeek, Ultra, Lycos, OpenText Web Index, and Yahoo. Information covered includes Contents, Searching tips, Results, and Update frequency
  15. Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005) 0.00 
    0.003191654 = product of:
  0.01595827 = sum of:
    0.01595827 = product of:
      0.03191654 = sum of:
        0.03191654 = weight(_text_:22 in 2564) [ClassicSimilarity], result of:
          0.03191654 = score(doc=2564,freq=2.0), product of:
            0.1649855 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047114085 = queryNorm
            0.19345059 = fieldWeight in 2564, 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=2564)
      0.5 = coord(1/2)
  0.2 = coord(1/5)
    Date
    16. 1.2016 10:22:28
  16. What is Schema.org? (2011) 0.00 
    0.0027223425 = product of:
  0.0136117125 = sum of:
    0.0136117125 = weight(_text_:information in 4437) [ClassicSimilarity], result of:
      0.0136117125 = score(doc=4437,freq=4.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.16457605 = fieldWeight in 4437, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=4437)
  0.2 = coord(1/5)
    Abstract
    This site provides a collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google and Yahoo! rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Many sites are generated from structured data, which is often stored in databases. When this data is formatted into HTML, it becomes very difficult to recover the original structured data. Many applications, especially search engines, can benefit greatly from direct access to this structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results in order to make it easier for users to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure. A shared markup vocabulary makes easier for webmasters to decide on a markup schema and get the maximum benefit for their efforts. So, in the spirit of sitemaps.org, Bing, Google and Yahoo! have come together to provide a shared collection of schemas that webmasters can use.
  17. Ding, L.; Finin, T.; Joshi, A.; Peng, Y.; Cost, R.S.; Sachs, J.; Pan, R.; Reddivari, P.; Doshi, V.: Swoogle : a Semantic Web search and metadata engine (2004) 0.00 
    0.0027223425 = product of:
  0.0136117125 = sum of:
    0.0136117125 = weight(_text_:information in 4704) [ClassicSimilarity], result of:
      0.0136117125 = score(doc=4704,freq=4.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.16457605 = fieldWeight in 4704, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=4704)
  0.2 = coord(1/5)
    Abstract
    Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.
    Source
    CIKM '04 Proceedings of the thirteenth ACM international conference on Information and knowledge management
  18. Dodge, M.: ¬A map of Yahoo! (2000) 0.00 
    0.0026456413 = product of:
  0.013228206 = sum of:
    0.013228206 = weight(_text_:information in 1555) [ClassicSimilarity], result of:
      0.013228206 = score(doc=1555,freq=34.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.15993917 = fieldWeight in 1555, product of:
          5.8309517 = tf(freq=34.0), with freq of:
            34.0 = termFreq=34.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.015625 = fieldNorm(doc=1555)
  0.2 = coord(1/5)
    Content
    "Introduction Yahoo! is the undisputed king of the Web directories, providing one of the key information navigation tools on the Internet. It has maintained its popularity over many Internet-years as the most visited Web site, against intense competition. This is because it does a good job of shifting, cataloguing and organising the Web [1] . But what would a map of Yahoo!'s hierarchical classification of the Web look like? Would an interactive map of Yahoo!, rather than the conventional listing of sites, be more useful as navigational tool? We can get some idea what a map of Yahoo! might be like by taking a look at ET-Map, a prototype developed by Hsinchun Chen and colleagues in the Artificial Intelligence Lab [2] at the University of Arizona. ET-Map was developed in 1995 as part of innovative research in automatic Internet homepage categorization and it charts a large chunk of Yahoo!, from the entertainment section representing some 110,000 different Web links. The map is a two-dimensional, multi-layered category map; its aim is to provide an intuitive visual information browsing tool. ET-Map can be browsed interactively, explored and queried, using the familiar point-and-click navigation style of the Web to find information of interest.
    The View From Above Browsing for a particular piece on information on the Web can often feel like being stuck in an unfamiliar part of town walking around at street level looking for a particular store. You know the store is around there somewhere, but your viewpoint at ground level is constrained. What you really want is to get above the streets, hovering half a mile or so up in the air, to see the whole neighbourhood. This kind of birds-eye view function has been memorably described by David D. Clark, Senior Research Scientist at MIT's Laboratory for Computer Science and the Chairman of the Invisible Worlds Protocol Advisory Board, as the missing "up button" on the browser [3] . ET-Map is a nice example of a prototype for Clark's "up-button" view of an information space. The goal of information maps, like ET-Map, is to provide the browser with a sense of the lie of the information landscape, what is where, the location of clusters and hotspots, what is related to what. Ideally, this 'big-picture' all-in-one visual summary needs to fit on a single standard computer screen. ET-Map is one of my favourite examples, but there are many other interesting information maps being developed by other researchers and companies (see inset at the bottom of this page). How does ET-Map work? Here is a sequence of screenshots of a typical browsing session with ET-Map, which ends with access to Web pages on jazz musician Miles Davis. You can also tryout ET-Map for yourself, using a fully working demo on the AI Lab's website [4] . We begin with the top-level map showing forty odd broad entertainment 'subject regions' represented by regularly shaped tiles. Each tile is a visual summary of a group of Web pages with similar content. These tiles are shaded different colours to differentiate them, while labels identify the subject of the tile and the number in brackets telling you how many individual Web page links it contains. ET-Map uses two important, but common-sense, spatial concepts in its organisation and representation of the Web. Firstly, the 'subject regions' size is directly related to the number of Web pages in that category. For example, the 'MUSIC' subject area contains over 11,000 pages and so has a much larger area than the neighbouring area of 'LIVE' which only has 4,300 odd pages. This is intuitively meaningful, as the largest tiles are visually more prominent on the map and are likely to be more significant as they contain the most links. In addition, a second spatial concept, that of neighbourhood proximity, is applied so 'subject regions' closely related in term of content are plotted close to each other on the map. For example, 'FILM' and 'YEAR'S OSCARS', at the bottom left, are neighbours in both semantic and spatial space. This make senses as many things in the real-world are ordered in this way, with things that are alike being spatially close together (e.g. layout of goods in a store, or books in a library). Importantly, ET-Map is also a multi-layer map, with sub-maps showing greater informational resolution through a finer degree of categorization. So for any subject region that contains more than two hundred Web pages, a second-level map, with more detailed categories is generated. This subdivision of information space is repeated down the hierarchy as far as necessary. In the example, the user selected the 'MUSIC' subject region which, not surprisingly, contained many thousands of pages. A second-level map with numerous different music categories is then presented to the user. Delving deeper, the user wants to learn more about jazz music, so clicking on the 'JAZZ' tile leads to a third-level map, a fine-grained map of jazz related Web pages. Finally, selecting the 'MILES DAVIS' subject region leads to more a conventional looking ranking of pages from which the user selects one to download.
    ET-Map was created using a sophisticated AI technique called Kohonen self-organizing map, a neural network approach that has been used for automatic analysis and classification of semantic content of text documents like Web pages. I do not pretend to fully understand how this technique works; I tend to think of it as a clever 'black-box' that group together things that are alike [5] . It is a real challenge to automatically classify pages from a very heterogeneous information collection like the Web into categories that will match the conceptions of a typical user. Directories like Yahoo! tend to rely on the skill of human editors to achieve this. ET-Map is an interesting prototype that I think highlights well the potential for a map-based approach to Web browsing. I am surprised none of the major search engines or directories have introduced the option of mapping results. Although, I am sure many are working on ideas. People certainly need all the help they get, as Web growth shows no sign of slowing. Just last month it was reported that the Web had surpassed one billion indexable pages [6].
    Information Maps There are many other fascinating examples that employ two dimensional interactive maps to provide a 'birds-eye' view of information. They use various underlying techniques of textual analysis and clustering to turn the mass of information into a useful summary map (see "Mining in Textual Mountains" in Mappa.Mundi Magazine). In terms of visual representations they can be divided into two groups, those that generate smooth surfaces and those that produce regular, tiled maps. Unfortunately, we don't have space to examine them in detail, but they are well worth spending some time exploring. I will be covering some of them in future columns.
    Research Prototypes Visual SiteMap Developed by Xia Lin, based at the College of Library and Information Science, Drexel University. CVG Cyberspace geography visualization, developed by Luc Girardin, at The Graduate Institute of International Studies, Switzerland. WEBSOM Maps the thousands of articles posted on Usenet newsgroups. It is being developed by researchers at the Neural Networks Research Centre, Helsinki University of Technology in Finland. TreeMaps Developed by Brian Johnson, Ben Shneiderman and colleagues in the Human-Computer Interaction Lab at the University of Maryland. Commercial Information Maps: NewsMaps Provides interactive information landscapes summarizing daily news stories, developed Cartia, Inc. Web Squirrel Creates maps known as information farms. It is developed by Eastgate Systems, Inc. Umap Produces interactive maps of Web searches. Map of the Market An interactive map of the market performance of the stocks of major US corporations developed by SmartMoney.com."
  19. Hodson, H.: Google's fact-checking bots build vast knowledge bank (2014) 0.00 
    0.0025666493 = product of:
  0.012833246 = sum of:
    0.012833246 = weight(_text_:information in 1700) [ClassicSimilarity], result of:
      0.012833246 = score(doc=1700,freq=2.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.1551638 = fieldWeight in 1700, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0625 = fieldNorm(doc=1700)
  0.2 = coord(1/5)
    Abstract
    The search giant is automatically building Knowledge Vault, a massive database that could give us unprecedented access to the world's facts GOOGLE is building the largest store of knowledge in human history - and it's doing so without any human help. Instead, Knowledge Vault autonomously gathers and merges information from across the web into a single base of facts about the world, and the people and objects in it.
  20. Brin, S.; Page, L.: ¬The anatomy of a large-scale hypertextual Web search engine (1998) 0.00 
    0.0022686187 = product of:
  0.011343094 = sum of:
    0.011343094 = weight(_text_:information in 947) [ClassicSimilarity], result of:
      0.011343094 = score(doc=947,freq=4.0), product of:
        0.08270773 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.047114085 = queryNorm
        0.13714671 = fieldWeight in 947, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=947)
  0.2 = coord(1/5)
    Abstract
    In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/. To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want

Authors

Years

Themes