Search (5 results, page 1 of 1)

0.036502596 = product of:
  0.07300519 = sum of:
    0.07300519 = sum of:
      0.033047944 = weight(_text_:classification in 2753) [ClassicSimilarity], result of:
        0.033047944 = score(doc=2753,freq=4.0), product of:
          0.16603322 = queryWeight, product of:
            3.1847067 = idf(docFreq=4974, maxDocs=44218)
            0.05213454 = queryNorm
          0.19904417 = fieldWeight in 2753, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            3.1847067 = idf(docFreq=4974, maxDocs=44218)
            0.03125 = fieldNorm(doc=2753)
      0.039957248 = weight(_text_:22 in 2753) [ClassicSimilarity], result of:
        0.039957248 = score(doc=2753,freq=4.0), product of:
          0.18256627 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05213454 = queryNorm
          0.21886435 = fieldWeight in 2753, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.03125 = fieldNorm(doc=2753)
  0.5 = coord(1/2)

Abstract

This book constitutes the thoroughly refereed post-conference proceedings of the First COST Action IC1302 International KEYSTONE Conference on semantic Keyword-based Search on Structured Data Sources, IKC 2015, held in Coimbra, Portugal, in September 2015. The 13 revised full papers, 3 revised short papers, and 2 invited papers were carefully reviewed and selected from 22 initial submissions. The paper topics cover techniques for keyword search, semantic data management, social Web and social media, information retrieval, benchmarking for search on big data.

Content

Inhalt: Professional Collaborative Information Seeking: On Traceability and Creative Sensemaking / Nürnberger, Andreas (et al.) - Recommending Web Pages Using Item-Based Collaborative Filtering Approaches / Cadegnani, Sara (et al.) - Processing Keyword Queries Under Access Limitations / Calì, Andrea (et al.) - Balanced Large Scale Knowledge Matching Using LSH Forest / Cochez, Michael (et al.) - Improving css-KNN Classification Performance by Shifts in Training Data / Draszawka, Karol (et al.) - Classification Using Various Machine Learning Methods and Combinations of Key-Phrases and Visual Features / HaCohen-Kerner, Yaakov (et al.) - Mining Workflow Repositories for Improving Fragments Reuse / Harmassi, Mariem (et al.) - AgileDBLP: A Search-Based Mobile Application for Structured Digital Libraries / Ifrim, Claudia (et al.) - Support of Part-Whole Relations in Query Answering / Kozikowski, Piotr (et al.) - Key-Phrases as Means to Estimate Birth and Death Years of Jewish Text Authors / Mughaz, Dror (et al.) - Visualization of Uncertainty in Tag Clouds / Platis, Nikos (et al.) - Multimodal Image Retrieval Based on Keywords and Low-Level Image Features / Pobar, Miran (et al.) - Toward Optimized Multimodal Concept Indexing / Rekabsaz, Navid (et al.) - Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives / Souza, Tarcisio (et al.) - Indexing of Textual Databases Based on Lexical Resources: A Case Study for Serbian / Stankovic, Ranka (et al.) - Domain-Specific Modeling: Towards a Food and Drink Gazetteer / Tagarev, Andrey (et al.) - Analysing Entity Context in Multilingual Wikipedia to Support Entity-Centric Retrieval Applications / Zhou, Yiwei (et al.)

Date

1. 2.2016 18:25:22

0.022626381 = product of:
  0.045252763 = sum of:
    0.045252763 = product of:
      0.090505525 = sum of:
        0.090505525 = weight(_text_:classification in 3804) [ClassicSimilarity], result of:
          0.090505525 = score(doc=3804,freq=30.0), product of:
            0.16603322 = queryWeight, product of:
              3.1847067 = idf(docFreq=4974, maxDocs=44218)
              0.05213454 = queryNorm
            0.5451049 = fieldWeight in 3804, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              3.1847067 = idf(docFreq=4974, maxDocs=44218)
              0.03125 = fieldNorm(doc=3804)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This book proposes a novel approach to classification, discusses its myriad advantages, and outlines how such an approach to classification can best be pursued. It encourages a collaborative effort toward the detailed development of such a classification. This book is motivated by the increased importance of interdisciplinary scholarship in the academy, and the widely perceived shortcomings of existing knowledge organization schemes in serving interdisciplinary scholarship. It is designed for scholars of classification research, knowledge organization, the digital environment, and interdisciplinarity itself. The approach recommended blends a general classification with domain-specific classification practices. The book reaches a set of very strong conclusions:
-Existing classification systems serve interdisciplinary research and teaching poorly. -A novel approach to classification, grounded in the phenomena studied rather than disciplines, would serve interdisciplinary scholarship much better. It would also have advantages for disciplinary scholarship. The productivity of scholarship would thus be increased. -This novel approach is entirely feasible. Various concerns that might be raised can each be addressed. The broad outlines of what a new classification would look like are developed. -This new approach might serve as a complement to or a substitute for existing classification systems. -Domain analysis can and should be employed in the pursuit of a general classification. This will be particularly important with respect to interdisciplinary domains. -Though the impetus for this novel approach comes from interdisciplinarity, it is also better suited to the needs of the Semantic Web, and a digital environment more generally. Though the primary focus of the book is on classification systems, most chapters also address how the analysis could be extended to thesauri and ontologies. The possibility of a universal thesaurus is explored. The classification proposed has many of the advantages sought in ontologies for the Semantic Web. The book is therefore of interest to scholars working in these areas as well.

LCSH

Classification / Research

Subject

Classification / Research

0.012486639 = product of:
  0.024973279 = sum of:
    0.024973279 = product of:
      0.049946558 = sum of:
        0.049946558 = weight(_text_:22 in 1949) [ClassicSimilarity], result of:
          0.049946558 = score(doc=1949,freq=4.0), product of:
            0.18256627 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05213454 = queryNorm
            0.27358043 = fieldWeight in 1949, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1949)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Classification

004.67/8 22

DDC

004.67/8 22

0.0058421064 = product of:
  0.011684213 = sum of:
    0.011684213 = product of:
      0.023368426 = sum of:
        0.023368426 = weight(_text_:classification in 362) [ClassicSimilarity], result of:
          0.023368426 = score(doc=362,freq=2.0), product of:
            0.16603322 = queryWeight, product of:
              3.1847067 = idf(docFreq=4974, maxDocs=44218)
              0.05213454 = queryNorm
            0.14074548 = fieldWeight in 362, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1847067 = idf(docFreq=4974, maxDocs=44218)
              0.03125 = fieldNorm(doc=362)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Content

Inhalt: An Introduction to Text Mining.- Information Extraction from Text.- A Survey of Text Summarization Techniques.- A Survey of Text Clustering Algorithms.- Dimensionality Reduction and Topic Modeling.- A Survey of Text Classification Algorithms.- Transfer Learning for Text Mining.- Probabilistic Models for Text Mining.- Mining Text Streams.- Translingual Mining from Text Data.- Text Mining in Multimedia.- Text Analytics in Social Media.- A Survey of Opinion Mining and Sentiment Analysis.- Biomedical Text Mining: A Survey of Recent Progress.- Index.

0.0058421064 = product of:
  0.011684213 = sum of:
    0.011684213 = product of:
      0.023368426 = sum of:
        0.023368426 = weight(_text_:classification in 5134) [ClassicSimilarity], result of:
          0.023368426 = score(doc=5134,freq=2.0), product of:
            0.16603322 = queryWeight, product of:
              3.1847067 = idf(docFreq=4974, maxDocs=44218)
              0.05213454 = queryNorm
            0.14074548 = fieldWeight in 5134, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1847067 = idf(docFreq=4974, maxDocs=44218)
              0.03125 = fieldNorm(doc=5134)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Footnote

Rez. in: Cataloging and classification quarterly 54(2016) no.7, S.504-505 (Claudia Horning).