Search (18 results, page 1 of 1)

  • × author_ss:"Liu, Y."
  1. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.04 
    0.042316247 = product of:
  0.08463249 = sum of:
    0.023104034 = weight(_text_:technology in 5492) [ClassicSimilarity], result of:
      0.023104034 = score(doc=5492,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 5492, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5492)
    0.06152846 = sum of:
      0.029589878 = weight(_text_:management in 5492) [ClassicSimilarity], result of:
        0.029589878 = score(doc=5492,freq=2.0), product of:
          0.15891297 = queryWeight, product of:
            3.3706124 = idf(docFreq=4130, maxDocs=44218)
            0.04714662 = queryNorm
          0.18620178 = fieldWeight in 5492, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.3706124 = idf(docFreq=4130, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5492)
      0.03193858 = weight(_text_:22 in 5492) [ClassicSimilarity], result of:
        0.03193858 = score(doc=5492,freq=2.0), product of:
          0.16509943 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.04714662 = queryNorm
          0.19345059 = fieldWeight in 5492, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=5492)
  0.5 = coord(2/4)
    Abstract
    Purpose Online knowledge communities make great contributions to global knowledge sharing and innovation. Resource tagging approaches have been widely adopted in such communities to describe, annotate and organize knowledge resources mainly through users' participation. However, it is unclear what causes the adoption of a particular resource tagging approach. The purpose of this paper is to identify factors that drive users to use a hybrid social tagging approach. Design/methodology/approach Technology acceptance model and social cognitive theory are adopted to support an integrated model proposed in this paper. Zhihu, one of the most popular online knowledge communities in China, is taken as the survey context. A survey was conducted with a questionnaire and collected data were analyzed through structural equation model. Findings A new hybrid social resource tagging approach was refined and described. The empirical results revealed that self-efficacy, perceived usefulness (PU) and perceived ease of use exert positive effect on users' attitude. Moreover, social influence, PU and attitude impact significantly on users' intention to use a hybrid social resource tagging approach. Originality/value Theoretically, this study enriches the type of resource tagging approaches and recognizes factors influencing user adoption to use it. Regarding the practical parts, the results provide online information system providers and designers with referential strategies to improve the performance of the current tagging approaches and promote them.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.2, S.155-175
  2. Liu, Y.; Huang, X.; An, A.: Personalized recommendation with adaptive mixture of markov models (2007) 0.02 
    0.018949486 = product of:
  0.037898973 = sum of:
    0.023104034 = weight(_text_:technology in 606) [ClassicSimilarity], result of:
      0.023104034 = score(doc=606,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 606, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=606)
    0.014794939 = product of:
      0.029589878 = sum of:
        0.029589878 = weight(_text_:management in 606) [ClassicSimilarity], result of:
          0.029589878 = score(doc=606,freq=2.0), product of:
            0.15891297 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.04714662 = queryNorm
            0.18620178 = fieldWeight in 606, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.0390625 = fieldNorm(doc=606)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    With more and more information available on the Internet, the task of making personalized recommendations to assist the user's navigation has become increasingly important. Considering there might be millions of users with different backgrounds accessing a Web site everyday, it is infeasible to build a separate recommendation system for each user. To address this problem, clustering techniques can first be employed to discover user groups. Then, user navigation patterns for each group can be discovered, to allow the adaptation of a Web site to the interest of each individual group. In this paper, we propose to model user access sequences as stochastic processes, and a mixture of Markov models based approach is taken to cluster users and to capture the sequential relationships inherent in user access histories. Several important issues that arise in constructing the Markov models are also addressed. The first issue lies in the complexity of the mixture of Markov models. To improve the efficiency of building/maintaining the mixture of Markov models, we develop a lightweight adapt-ive algorithm to update the model parameters without recomputing model parameters from scratch. The second issue concerns the proper selection of training data for building the mixture of Markov models. We investigate two different training data selection strategies and perform extensive experiments to compare their effectiveness on a real dataset that is generated by a Web-based knowledge management system, Livelink.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.12, S.1851-1870
  3. Fang, Z.; Liu, Y.; Jiang, F.; Dong, W.: How does family support influence digital immigrants' extended use of smartphones? : an empirical study based on IT identity theory (2023) 0.01 
    0.0100043425 = product of:
  0.04001737 = sum of:
    0.04001737 = weight(_text_:technology in 1091) [ClassicSimilarity], result of:
      0.04001737 = score(doc=1091,freq=6.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.2849816 = fieldWeight in 1091, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1091)
  0.25 = coord(1/4)
    Abstract
    The number of digital immigrants using new technologies such as smartphones is rapidly increasing. However, digital immigrants still struggle to actually use and benefit from digital technology. This article examines the role of family support in digital immigrants' use of more smartphone functions based on information technology (IT) identity theory. We surveyed 241 digital immigrants who owned smartphones and used structural equation modeling (PLS-SEM) for analysis. We examined the contributing roles of family support for digital immigrants' IT identity and extended use behavior. Family cognitive and emotional support can shape IT identity by improving the smartphone-related experience. Family support has a positive impact on digital immigrants' self-efficacy, embeddedness, perceived usefulness, and perceived enjoyment of using a smartphone. Positive usage experience can also facilitate the establishment of IT identity, which is a key predictor of smartphone use behavior. A strong IT identity also promotes extended use behavior. We discuss the contributions and implications of our findings.
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.12, S.1463-1481
  4. Liu, Y.; Rousseau, R.: Citation analysis and the development of science : a case study using articles by some Nobel prize winners (2014) 0.01 
    0.0092416145 = product of:
  0.036966458 = sum of:
    0.036966458 = weight(_text_:technology in 1197) [ClassicSimilarity], result of:
      0.036966458 = score(doc=1197,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.2632547 = fieldWeight in 1197, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0625 = fieldNorm(doc=1197)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.2, S.281-289
  5. Liu, Y.; Shi, J.; Chen, Y.: Patient-centered and experience-aware mining for effective adverse drug reaction discovery in online health forums (2018) 0.01 
    0.006931211 = product of:
  0.027724843 = sum of:
    0.027724843 = weight(_text_:technology in 4114) [ClassicSimilarity], result of:
      0.027724843 = score(doc=4114,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.19744103 = fieldWeight in 4114, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.046875 = fieldNorm(doc=4114)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.2, S.215-228
  6. Liu, Y.; Du, F.; Sun, J.; Silva, T.; Jiang, Y.; Zhu, T.: Identifying social roles using heterogeneous features in online social networks (2019) 0.01 
    0.006931211 = product of:
  0.027724843 = sum of:
    0.027724843 = weight(_text_:technology in 5293) [ClassicSimilarity], result of:
      0.027724843 = score(doc=5293,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.19744103 = fieldWeight in 5293, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.046875 = fieldNorm(doc=5293)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.7, S.660-674
  7. Liu, Y.: Precision One MediaSource : film/video locator on CD-ROM (1995) 0.01 
    0.006387716 = product of:
  0.025550865 = sum of:
    0.025550865 = product of:
      0.05110173 = sum of:
        0.05110173 = weight(_text_:22 in 7744) [ClassicSimilarity], result of:
          0.05110173 = score(doc=7744,freq=2.0), product of:
            0.16509943 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04714662 = queryNorm
            0.30952093 = fieldWeight in 7744, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=7744)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Date
    22. 6.1997 16:34:51
  8. Liu, Y.; Zhang, M.; Cen, R.; Ru, L.; Ma, S.: Data cleansing for Web information retrieval using query independent features (2007) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 607) [ClassicSimilarity], result of:
      0.023104034 = score(doc=607,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 607, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=607)
  0.25 = coord(1/4)
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.12, S.1884-1898
  9. Liu, Y.; Rousseau, R.: Knowledge diffusion through publications and citations : a case study using ESI-fields as unit of diffusion (2010) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 3334) [ClassicSimilarity], result of:
      0.023104034 = score(doc=3334,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 3334, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3334)
  0.25 = coord(1/4)
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.2, S.340-351
  10. Liu, Y.; Li, W.; Huang, Z.; Fang, Q.: ¬A fast method based on multiple clustering for name disambiguation in bibliographic citations (2015) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 1672) [ClassicSimilarity], result of:
      0.023104034 = score(doc=1672,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 1672, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1672)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.3, S.634-644
  11. Liu, Y.; Xu, S.; Blanchard, E.: ¬A local context-aware LDA model for topic modeling in a document network (2017) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 3642) [ClassicSimilarity], result of:
      0.023104034 = score(doc=3642,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 3642, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3642)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.6, S.1429-1448
  12. Zhou, H.; Xiao, L.; Liu, Y.; Chen, X.: ¬The effect of prediscussion note-taking in hidden profile tasks (2018) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 4184) [ClassicSimilarity], result of:
      0.023104034 = score(doc=4184,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 4184, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4184)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.4, S.566-577
  13. Wu, Y.; Liu, Y.; Tsai, Y.-H.R.; Yau, S.-T.: Investigating the role of eye movements and physiological signals in search satisfaction prediction using geometric analysis (2019) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 5382) [ClassicSimilarity], result of:
      0.023104034 = score(doc=5382,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 5382, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5382)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.9, S.981-999
  14. Sun, J.; Zhu, M.; Jiang, Y.; Liu, Y.; Wu, L.L.: Hierarchical attention model for personalized tag recommendation : peer effects on information value perception (2021) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 98) [ClassicSimilarity], result of:
      0.023104034 = score(doc=98,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 98, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=98)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.2, S.173-189
  15. Qin, C.; Liu, Y.; Ma, X.; Chen, J.; Liang, H.: Designing for serendipity in online knowledge communities : an investigation of tag presentation formats and openness to experience (2022) 0.01 
    0.0057760086 = product of:
  0.023104034 = sum of:
    0.023104034 = weight(_text_:technology in 664) [ClassicSimilarity], result of:
      0.023104034 = score(doc=664,freq=2.0), product of:
        0.14042088 = queryWeight, product of:
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.04714662 = queryNorm
        0.16453418 = fieldWeight in 664, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.978387 = idf(docFreq=6114, maxDocs=44218)
          0.0390625 = fieldNorm(doc=664)
  0.25 = coord(1/4)
    Source
    Journal of the Association for Information Science and Technology. 73(2022) no.10, S.1401-1417
  16. Liu, Y.; Rousseau, R.: Towards a representation of diffusion and interaction of scientific ideas : the case of fiber optics communication (2012) 0.01 
    0.0051782285 = product of:
  0.020712914 = sum of:
    0.020712914 = product of:
      0.041425828 = sum of:
        0.041425828 = weight(_text_:management in 2723) [ClassicSimilarity], result of:
          0.041425828 = score(doc=2723,freq=2.0), product of:
            0.15891297 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.04714662 = queryNorm
            0.2606825 = fieldWeight in 2723, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2723)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Source
    Information processing and management. 48(2012) no.4, S.791-801
  17. Lim, S.C.J.; Liu, Y.; Lee, W.B.: Multi-facet product information search and retrieval using semantically annotated product family ontology (2010) 0.00 
    0.004184641 = product of:
  0.016738564 = sum of:
    0.016738564 = product of:
      0.033477128 = sum of:
        0.033477128 = weight(_text_:management in 4239) [ClassicSimilarity], result of:
          0.033477128 = score(doc=4239,freq=4.0), product of:
            0.15891297 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.04714662 = queryNorm
            0.21066327 = fieldWeight in 4239, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.03125 = fieldNorm(doc=4239)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Abstract
    With the advent of various services and applications of Semantic Web, semantic annotation has emerged as an important research topic. The application of semantically annotated ontology had been evident in numerous information processing and retrieval tasks. One of such tasks is utilizing the semantically annotated ontology in product design which is able to suggest many important applications that are critical to aid various design related tasks. However, ontology development in design engineering remains a time consuming and tedious task that demands considerable human efforts. In the context of product family design, management of different product information that features efficient indexing, update, navigation, search and retrieval across product families is both desirable and challenging. For instance, an efficient way of retrieving timely information on product family can be useful for tasks such as product family redesign and new product variant derivation when requirements change. However, the current research and application of information search and navigation in product family is mostly limited to its structural aspect which is insufficient to handle advanced information search especially when the query targets at multiple aspects of a product. This paper attempts to address this problem by proposing an information search and retrieval framework based on the semantically annotated multi-facet product family ontology. Particularly, we propose a document profile (DP) model to suggest semantic tags for annotation purpose. Using a case study of digital camera families, we illustrate how the faceted search and retrieval of product information can be accomplished. We also exemplify how we can derive new product variants based on the designer's query of requirements via the faceted search and retrieval of product family information. Lastly, in order to highlight the value of our current work, we briefly discuss some further research and applications in design decision support, e.g. commonality analysis and variety comparison, based on the semantically annotated multi-facet product family ontology.
    Source
    Information processing and management. 46(2010) no.4, S.479-493
  18. Lim, S.C.J.; Liu, Y.; Lee, W.B.: ¬A methodology for building a semantically annotated multi-faceted ontology for product family modelling (2011) 0.00 
    0.0029589878 = product of:
  0.011835951 = sum of:
    0.011835951 = product of:
      0.023671903 = sum of:
        0.023671903 = weight(_text_:management in 1485) [ClassicSimilarity], result of:
          0.023671903 = score(doc=1485,freq=2.0), product of:
            0.15891297 = queryWeight, product of:
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.04714662 = queryNorm
            0.14896142 = fieldWeight in 1485, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.3706124 = idf(docFreq=4130, maxDocs=44218)
              0.03125 = fieldNorm(doc=1485)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Abstract
    Product family design is one of the prevailing approaches in realizing mass customization. With the increasing number of product offerings targeted at different market segments, the issue of information management in product family design, that is related to an efficient and effective storage, sharing and timely retrieval of design information, has become more complicated and challenging. Product family modelling schema reported in the literature generally stress the component aspects of a product family and its analysis, with a limited capability to model complex inter-relations between physical components and other required information in different semantic orientations, such as manufacturing, material and marketing wise. To tackle this problem, ontology-based representation has been identified as a promising solution to redesign product platforms especially in a semantically rich environment. However, ontology development in design engineering demands a great deal of time commitment and human effort to process complex information. When a large variety of products are available, particularly in the consumer market, a more efficient method for building a product family ontology with the incorporation of multi-faceted semantic information is therefore highly desirable. In this study, we propose a methodology for building a semantically annotated multi-faceted ontology for product family modelling that is able to automatically suggest semantically-related annotations based on the design and manufacturing repository. The six steps of building such ontology: formation of product family taxonomy; extraction of entities; faceted unit generation and concept identification; facet modelling and semantic annotation; formation of a semantically annotated multi-faceted product family ontology (MFPFO); and ontology validation and evaluation are discussed in detail. Using a family of laptop computers as an illustrative example, we demonstrate how our methodology can be deployed step by step to create a semantically annotated MFPFO. Finally, we briefly discuss future research issues as well as interesting applications that can be further pursued based on the MFPFO developed.

Authors

Years

Themes