Search (63 results, page 4 of 4)

0.0068065543 = product of:
  0.013613109 = sum of:
    0.013613109 = product of:
      0.027226217 = sum of:
        0.027226217 = weight(_text_:systems in 5732) [ClassicSimilarity], result of:
          0.027226217 = score(doc=5732,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.1697705 = fieldWeight in 5732, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5732)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Recent technological developments have increased the use of machine learning to solve many problems, including many in information retrieval. Multimedia information retrieval as a problem represents a significant challenge to machine learning as a technological solution, but some problems can still be addressed by using appropriate AI techniques. We review the technological developments and provide a perspective on the use of machine learning in conjunction with knowledge organization to address multimedia IR needs. The semantic gap in multimedia IR remains a significant problem in the field, and solutions to them are many years off. However, new technological developments allow the use of knowledge organization and machine learning in multimedia search systems and services. Specifically, we argue that, the improvement of detection of some classes of lowlevel features in images music and video can be used in conjunction with knowledge organization to tag or label multimedia content for better retrieval performance. We provide an overview of the use of knowledge organization schemes in machine learning and make recommendations to information professionals on the use of this technology with knowledge organization techniques to solve multimedia IR problems. We introduce a five-step process model that extracts features from multimedia objects (Step 1) from both knowledge organization (Step 1a) and machine learning (Step 1b), merging them together (Step 2) to create an index of those multimedia objects (Step 3). We also overview further steps in creating an application to utilize the multimedia objects (Step 4) and maintaining and updating the database of features on those objects (Step 5).

0.0054452433 = product of:
  0.010890487 = sum of:
    0.010890487 = product of:
      0.021780973 = sum of:
        0.021780973 = weight(_text_:systems in 738) [ClassicSimilarity], result of:
          0.021780973 = score(doc=738,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.1358164 = fieldWeight in 738, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.03125 = fieldNorm(doc=738)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Content

Enthält u.a. die Beiträge: CHIARAMELLA, Y.: Browsing and querying: two complementary approaches for multimedia information retrieval; ELZER, P. u. U. KROHN: Visualisierung zur Unterstützung der Suche in komplexen Datenbeständen; OROSCO, R.: AutoFocus: User assistance in information visualization; LALMAS, M. u. I. RUTHVEN: A model for structured document retrieval: empirical investigations; HERZNER, W., M. KUMMER u. M. THUSWALD: DVS: a system for recording, archiving and retrieval of digital video in security environments; LOPEZ, J. u.a.: A user interface for the design of human figures multimedia animations; BOLES, D. u. G. WÜTHERICH: Transformationelle Multimedia-Softwareentwicklung; HAMMWÖHNER, R.: Komplexe Hypertextmodelle im World Wide Web durch dynamische Dokumente; BAUMGARTEN, C.: Probabilistische Modellierung der effizienten Informationssuche in verteilten multimedialen Dokumentbeständen durch Einschränkung des Suchraums; GÖVERT, N.: Evaluierung eines entscheidungstheoretischen Modells zur Datenbankselektion; RÖLLEKE, T. u. M. BLÖMER: Probabilisitc logical information retrieval for content, hypertext, and database querying; VICHOT, F. u.a.: High precision hypertext navigation based on NLP automatic extractions; PETROU, C., D, MARTAKOS u. S. HADJIEFTHYMIADES: Adding semantics to hypermedia towards link's enhancement and dynamic linking; ASHMAN, H., A. GARRIDO u. H. Oinas-Kukkonen: Hand-made and computed links, precomputed and dynamic links; MOGHRABI, I.A.R. u. M.A. SAFAR: Study of algorithms for clustering records in document database; PFEIFER, U. u. S. PENNEKAMP:Incremental processing of vague queries in interactive retrieval systems; DRESLER, S., A.G. GROSSE u. A. RÖSNER: Realisierung und Optimierung der Informationsbeschaffung von Internet-Suchmaschinen am Beispiel vom www.crawler.de; WOLFF, C. u. C. WOMSER-HACKER: Graphisches Faktenretrieval mit vager Anfrageinterpretation; DALAMAGAS, T. u. M.D. DUNLOP: Automatic construction of news hypertext; KAHABKA, T., M.KORKEA-AHO u. G. SPECHT: GRAS: an adaptive personalization scheme for hypermedia databases; BENZ, H. u.a.: DIANE: hypermedia documents in a distributed annotation environment; BEKAVEC, B. u. M. RITTBERGER: Kontextsensitive Visualisierung von Suchergebnissen; RIEKERT, W.-F. u.a.: Fach-, raum- und zeitbezogene Katalogisierung und Recherche von Umweltinformationen auf dem Internet; DUPONT-CHRIST, S. u.a.: PRISMA: eine Basis für multimediale Informationssysteme im Internet

0.0054452433 = product of:
  0.010890487 = sum of:
    0.010890487 = product of:
      0.021780973 = sum of:
        0.021780973 = weight(_text_:systems in 6520) [ClassicSimilarity], result of:
          0.021780973 = score(doc=6520,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.1358164 = fieldWeight in 6520, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.03125 = fieldNorm(doc=6520)
      0.5 = coord(1/2)
  0.5 = coord(1/2)