Search (3 results, page 1 of 1)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × theme_ss:"Semantische Interoperabilität"
  1. Shah, C.: Collaborative information seeking : the art and science of making the whole greater than the sum of all (2012) 0.00
    0.0033653039 = product of:
      0.013461215 = sum of:
        0.013461215 = weight(_text_:information in 360) [ClassicSimilarity], result of:
          0.013461215 = score(doc=360,freq=16.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.21943474 = fieldWeight in 360, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=360)
      0.25 = coord(1/4)
    
    Abstract
    Today's complex, information-intensive problems often require people to work together. Mostly these tasks go far beyond simply searching together; they include information lookup, sharing, synthesis, and decision-making. In addition, they all have an end-goal that is mutually beneficial to all parties involved. Such "collaborative information seeking" (CIS) projects typically last several sessions and the participants all share an intention to contribute and benefit. Not surprisingly, these processes are highly interactive. Shah focuses on two individually well-understood notions: collaboration and information seeking, with the goal of bringing them together to show how it is a natural tendency for humans to work together on complex tasks. The first part of his book introduces the general notions of collaboration and information seeking, as well as related concepts, terminology, and frameworks; and thus provides the reader with a comprehensive treatment of the concepts underlying CIS. The second part of the book details CIS as a standalone domain. A series of frameworks, theories, and models are introduced to provide a conceptual basis for CIS. The final part describes several systems and applications of CIS, along with their broader implications on other fields such as computer-supported cooperative work (CSCW) and human-computer interaction (HCI). With this first comprehensive overview of an exciting new research field, Shah delivers to graduate students and researchers in academia and industry an encompassing description of the technologies involved, state-of-the-art results, and open challenges as well as research opportunities.
    Content
    Inhalt: Part I Introduction.- Introduction.- Collaboration.- Collaborative Information Seeking (CIS) in Context.- Part II Conceptual Understanding of CIS.- Frameworks for CIS Research and Development.- Toward a Model for CIS.- Part III CIS Systems, Applications, and Implications.- Systems and Tools for CIS.- Evaluation.- Conclusion.- Ten Stories of Five Cs.- Brief Overview of Computer-Supported Cooperative Work (CSCW).- Brief Overview of Computer-Supported Collaborative Learning (CSCL).- Brief Overview of Computer-Mediated Communication (CMC).
    Series
    The Information Retrieval Series ; 34
  2. Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011) 0.00
    0.0017847219 = product of:
      0.0071388874 = sum of:
        0.0071388874 = weight(_text_:information in 649) [ClassicSimilarity], result of:
          0.0071388874 = score(doc=649,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.116372846 = fieldWeight in 649, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=649)
      0.25 = coord(1/4)
    
    Abstract
    This paper is about a better understanding of the structure and dynamics of science and the usage of these insights for compensating the typical problems that arises in metadata-driven Digital Libraries. Three science model driven retrieval services are presented: co-word analysis based query expansion, re-ranking via Bradfordizing and author centrality. The services are evaluated with relevance assessments from which two important implications emerge: (1) precision values of the retrieval services are the same or better than the tf-idf retrieval baseline and (2) each service retrieved a disjoint set of documents. The different services each favor quite other - but still relevant - documents than pure term-frequency based rankings. The proposed models and derived retrieval services therefore open up new viewpoints on the scientific knowledge space and provide an alternative framework to structure scholarly information systems.
  3. Semantic search over the Web (2012) 0.00
    0.0011898145 = product of:
      0.004759258 = sum of:
        0.004759258 = weight(_text_:information in 411) [ClassicSimilarity], result of:
          0.004759258 = score(doc=411,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.0775819 = fieldWeight in 411, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=411)
      0.25 = coord(1/4)
    
    Abstract
    The Web has become the world's largest database, with search being the main tool that allows organizations and individuals to exploit its huge amount of information. Search on the Web has been traditionally based on textual and structural similarities, ignoring to a large degree the semantic dimension, i.e., understanding the meaning of the query and of the document content. Combining search and semantics gives birth to the idea of semantic search. Traditional search engines have already advertised some semantic dimensions. Some of them, for instance, can enhance their generated result sets with documents that are semantically related to the query terms even though they may not include these terms. Nevertheless, the exploitation of the semantic search has not yet reached its full potential. In this book, Roberto De Virgilio, Francesco Guerra and Yannis Velegrakis present an extensive overview of the work done in Semantic Search and other related areas. They explore different technologies and solutions in depth, making their collection a valuable and stimulating reading for both academic and industrial researchers. The book is divided into three parts. The first introduces the readers to the basic notions of the Web of Data. It describes the different kinds of data that exist, their topology, and their storing and indexing techniques. The second part is dedicated to Web Search. It presents different types of search, like the exploratory or the path-oriented, alongside methods for their efficient and effective implementation. Other related topics included in this part are the use of uncertainty in query answering, the exploitation of ontologies, and the use of semantics in mashup design and operation. The focus of the third part is on linked data, and more specifically, on applying ideas originating in recommender systems on linked data management, and on techniques for the efficiently querying answering on linked data.

Types