Search (7 results, page 1 of 1)

  • × author_ss:"Johnson, A."
  1. Johnson, A.: Information brokers (1991) 0.01
    0.0067306077 = product of:
      0.02692243 = sum of:
        0.02692243 = weight(_text_:information in 1294) [ClassicSimilarity], result of:
          0.02692243 = score(doc=1294,freq=4.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.43886948 = fieldWeight in 1294, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.125 = fieldNorm(doc=1294)
      0.25 = coord(1/4)
    
    Source
    Encyclopedia of library and information science. Vol.48, [=Suppl.11]
  2. Qin, H.; Wang, H.; Johnson, A.: Understanding the information needs and information-seeking behaviours of new-generation engineering designers for effective knowledge management (2020) 0.01
    0.0057061506 = product of:
      0.022824602 = sum of:
        0.022824602 = weight(_text_:information in 181) [ClassicSimilarity], result of:
          0.022824602 = score(doc=181,freq=46.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.37206972 = fieldWeight in 181, product of:
              6.78233 = tf(freq=46.0), with freq of:
                46.0 = termFreq=46.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=181)
      0.25 = coord(1/4)
    
    Abstract
    Purpose This paper aims to explore the information needs and information-seeking behaviours of the new generation of engineering designers. A survey study is used to approach what their information needs are, how these needs change during an engineering design project and how their information-seeking behaviours have been influenced by the newly developed information technologies (ITs). Through an in-depth analysis of the survey results, the key functions have been identified for the next-generation management systems. Design/methodology/approach The paper first proposed four hypotheses on the information needs and information-seeking behaviours of young engineers. Then, a survey study was undertaken to understand their information usage in terms of the information needs and information-seeking behaviours during a complete engineering design process. Through analysing the survey results, several findings were obtained and on this basis, further comparisons were made to discuss and evaluate the hypotheses. Findings The paper has revealed that the engineering designers' information needs will evolve throughout the engineering design project; thus, they should be assisted at several different levels. Although they intend to search information and knowledge on know-what and know-how, what they really require is the know-why knowledge in order to help them complete design tasks. Also, the paper has shown how the newly developed ITs and web-based applications have influenced the engineers' information-seeking practices. Research limitations/implications The research subjects chosen in this study are engineering students in universities who, although not as experienced as engineers in companies, do go through a complete design process with the tasks similar to industrial scenarios. In addition, the focus of this study is to understand the information-seeking behaviours of a new generation of design engineers, so that the development of next-generation information and knowledge management systems can be well informed. In this sense, the results obtained do reveal some new knowledge about the information-seeking behaviours during a general design process. Practical implications This paper first identifies the information needs and information-seeking behaviours of the new generation of engineering designers. On this basis, the varied ways to meet these needs and behaviours are discussed and elaborated. This intends to provide the key characteristics for the development of the next-generation knowledge management system for engineering design projects. Originality/value This paper proposes a novel means of exploring the future engineers' information needs and information-seeking behaviours in a collaborative working environment. It also characterises the key features and functions for the next generation of knowledge management systems for engineering design.
    Source
    Aslib journal of information management. 72(2020) no.6, S.853-868
  3. Johnson, A.; Fotouhi, F.: Adaptive clustering of hypermedia documents (1998) 0.00
    0.004164351 = product of:
      0.016657405 = sum of:
        0.016657405 = weight(_text_:information in 4679) [ClassicSimilarity], result of:
          0.016657405 = score(doc=4679,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.27153665 = fieldWeight in 4679, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.109375 = fieldNorm(doc=4679)
      0.25 = coord(1/4)
    
    Source
    Encyclopedia of library and information science. Vol.63, [=Suppl.26]
  4. Jagtap, S.; Johnson, A.: Requirements and use of in-service information in an engineering redesign task : case studies from the aerospace industry (2010) 0.00
    0.0039349417 = product of:
      0.015739767 = sum of:
        0.015739767 = weight(_text_:information in 4116) [ClassicSimilarity], result of:
          0.015739767 = score(doc=4116,freq=14.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.256578 = fieldWeight in 4116, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4116)
      0.25 = coord(1/4)
    
    Abstract
    This article describes the research stimulated by a fundamental shift that is occurring in the manufacture and marketing of aero engines for commercial and defense purposes, away from the selling of products to the provision of services. This research was undertaken in an aerospace company, which designs and manufactures aero engines and also offers contracts, under which it remains responsible for the maintenance of engines. These contracts allow the company to collect far more data about the in-service performance of their engines than was previously available. This article aims at identifying what parts of this in-service information are required when components or systems of existing engines need to be redesigned because they have not performed as expected in service. In addition, this article aims at understanding how designers use this in-service information in a redesign task. In an attempt to address these aims, we analyzed five case studies involving redesign of components or systems of an existing engine. The findings show that the in-service information accessed by the designers mainly contains the undesired physical actions (e.g., deterioration mechanisms, deterioration effects, etc.) and the causal chains of these undesired physical actions. We identified a pattern in the designers' actions regarding the use of these causal chains. The designers have generated several solutions that utilize these causal chains seen in the in-service information. The findings provide a sound basis for developing tools and methods to support designers in effectively satisfying their in-service information requirements in a redesign task.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2442-2460
  5. Johnson, A.; Fotouhi, F.: Adaptive clustering of hypermedia documents (1996) 0.00
    0.0033653039 = product of:
      0.013461215 = sum of:
        0.013461215 = weight(_text_:information in 7437) [ClassicSimilarity], result of:
          0.013461215 = score(doc=7437,freq=4.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.21943474 = fieldWeight in 7437, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0625 = fieldNorm(doc=7437)
      0.25 = coord(1/4)
    
    Abstract
    Compares the use of 2 adaptive algorithms (genetic algorithms, and neural networks) in clustering hypermedia documents. The clusters allow the user to index into the nodes and find information quickly. The clustering focuses on the user's paths through the hypermedia document and not on the content of the nodes or the structure of the links in the document, thus the clustering reflects the unique relationships each user sees among the nodes. The original hypermedia document remains untouched, and each user has a personalised index into this document
    Source
    Information systems. 21(1996) no.6, S.459-473
  6. Johnson, A.; Fotouhi, F.: Adaptive indexing in very large databases (1995) 0.00
    0.002379629 = product of:
      0.009518516 = sum of:
        0.009518516 = weight(_text_:information in 1940) [ClassicSimilarity], result of:
          0.009518516 = score(doc=1940,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.1551638 = fieldWeight in 1940, 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=1940)
      0.25 = coord(1/4)
    
    Abstract
    Compares the use of 2 adaptive algorithms (genetic algorithms, and neural networks) in clustering the tables of a very large database. These clusters allow the user to index into this overwhelming number of tables and find the needed information quickly. Clusters the tables based on the user's queries and not on the content of the tables, thus the clustering reflects the unique relationships each user sees among the tables. The original database remains untouched, however each user will now have a personalized index into this database
  7. Eschenfelder, K.R.; Johnson, A.: Managing the data commons : controlled sharing of scholarly data (2014) 0.00
    0.0017847219 = product of:
      0.0071388874 = sum of:
        0.0071388874 = weight(_text_:information in 1341) [ClassicSimilarity], result of:
          0.0071388874 = score(doc=1341,freq=2.0), product of:
            0.06134496 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.034944877 = queryNorm
            0.116372846 = fieldWeight in 1341, 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=1341)
      0.25 = coord(1/4)
    
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1757-1774