Search (5 results, page 1 of 1)

0.03583357 = product of:
  0.07166714 = sum of:
    0.07166714 = product of:
      0.14333428 = sum of:
        0.14333428 = weight(_text_:22 in 1339) [ClassicSimilarity], result of:
          0.14333428 = score(doc=1339,freq=6.0), product of:
            0.17824122 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050899457 = queryNorm
            0.804159 = fieldWeight in 1339, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.09375 = fieldNorm(doc=1339)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

22. 2.2003 17:25:39
22. 2.2003 18:16:22

0.034352217 = product of:
  0.068704434 = sum of:
    0.068704434 = product of:
      0.13740887 = sum of:
        0.13740887 = weight(_text_:intelligence in 902) [ClassicSimilarity], result of:
          0.13740887 = score(doc=902,freq=6.0), product of:
            0.2703623 = queryWeight, product of:
              5.3116927 = idf(docFreq=592, maxDocs=44218)
              0.050899457 = queryNorm
            0.50823975 = fieldWeight in 902, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.3116927 = idf(docFreq=592, maxDocs=44218)
              0.0390625 = fieldNorm(doc=902)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

An enhanced understanding of the innovative use of artificial intelligence (AI) is essential for organizations to improve work design and daily business operations. This study's purpose is to offer insights into how AI can transform organizations' work practices through diving deeply into its innovative use in the context of a primary AI tool, a chatbot, and examining the antecedents of innovative use by conceptualizing employee trust as a multidimensional construct and exploring employees' perceived benefits. In particular, we have conceptualized employee trust in chatbots as a second-order construct, including three first-order variables: trust in functionality, trust in reliability, and trust in data protection. We collected data from 202 employees. The results supported our conceptualization of trust in chatbots and showed that three dimensions of first-order trust beliefs have relatively the same level of importance. Further, both knowledge support and work-life balance enhance trust in chatbots, which in turn leads to innovative use of chatbots. Our study contributes to the existing literature by introducing the new conceptualization of trust in chatbots and examining its antecedents and outcomes. The results can provide important practical insights regarding how to support innovative use of chatbots as the new way we organize work.

Series

Special issue: artificial intelligence and work

0.012068303 = product of:
  0.024136607 = sum of:
    0.024136607 = product of:
      0.048273213 = sum of:
        0.048273213 = weight(_text_:22 in 2635) [ClassicSimilarity], result of:
          0.048273213 = score(doc=2635,freq=2.0), product of:
            0.17824122 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050899457 = queryNorm
            0.2708308 = fieldWeight in 2635, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2635)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

0.01034426 = product of:
  0.02068852 = sum of:
    0.02068852 = product of:
      0.04137704 = sum of:
        0.04137704 = weight(_text_:22 in 1421) [ClassicSimilarity], result of:
          0.04137704 = score(doc=1421,freq=2.0), product of:
            0.17824122 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050899457 = queryNorm
            0.23214069 = fieldWeight in 1421, 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=1421)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

0.009752663 = product of:
  0.019505326 = sum of:
    0.019505326 = product of:
      0.03901065 = sum of:
        0.03901065 = weight(_text_:22 in 2654) [ClassicSimilarity], result of:
          0.03901065 = score(doc=2654,freq=4.0), product of:
            0.17824122 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050899457 = queryNorm
            0.21886435 = fieldWeight in 2654, 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=2654)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In order to transfer the Chinese Classified Thesaurus (CCT) into a machine-processable format and provide CCT-based Web services, a pilot study has been conducted in which a variety of selected CCT classes and mapped thesaurus entries are encoded with SKOS. OWL and RDFS are also used to encode the same contents for the purposes of feasibility and cost-benefit comparison. CCT is a collected effort led by the National Library of China. It is an integration of the national standards Chinese Library Classification (CLC) 4th edition and Chinese Thesaurus (CT). As a manually created mapping product, CCT provides for each of the classes the corresponding thesaurus terms, and vice versa. The coverage of CCT includes four major clusters: philosophy, social sciences and humanities, natural sciences and technologies, and general works. There are 22 main-classes, 52,992 sub-classes and divisions, 110,837 preferred thesaurus terms, 35,690 entry terms (non-preferred terms), and 59,738 pre-coordinated headings (Chinese Classified Thesaurus, 2005) Major challenges of encoding this large vocabulary comes from its integrated structure. CCT is a result of the combination of two structures (illustrated in Figure 1): a thesaurus that uses ISO-2788 standardized structure and a classification scheme that is basically enumerative, but provides some flexibility for several kinds of synthetic mechanisms Other challenges include the complex relationships caused by differences of granularities of two original schemes and their presentation with various levels of SKOS elements; as well as the diverse coordination of entries due to the use of auxiliary tables and pre-coordinated headings derived from combining classes, subdivisions, and thesaurus terms, which do not correspond to existing unique identifiers. The poster reports the progress, shares the sample SKOS entries, and summarizes problems identified during the SKOS encoding process. Although OWL Lite and OWL Full provide richer expressiveness, the cost-benefit issues and the final purposes of encoding CCT raise questions of using such approaches.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas