Search (12 results, page 1 of 1)

  • × author_ss:"Zhang, Y."
  • × year_i:[2000 TO 2010}
  1. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.00
    0.0019651123 = product of:
      0.029476684 = sum of:
        0.029476684 = sum of:
          0.005919926 = weight(_text_:information in 2742) [ClassicSimilarity], result of:
            0.005919926 = score(doc=2742,freq=2.0), product of:
              0.050870337 = queryWeight, product of:
                1.7554779 = idf(docFreq=20772, maxDocs=44218)
                0.028978055 = queryNorm
              0.116372846 = fieldWeight in 2742, 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=2742)
          0.023556758 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
            0.023556758 = score(doc=2742,freq=2.0), product of:
              0.101476215 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.028978055 = queryNorm
              0.23214069 = fieldWeight in 2742, 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=2742)
      0.06666667 = coord(1/15)
    
    Date
    22. 3.2009 17:49:11
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
  2. Zhang, Y.: Complex adaptive filtering user profile using graphical models (2008) 0.00
    4.8335994E-4 = product of:
      0.007250399 = sum of:
        0.007250399 = product of:
          0.014500798 = sum of:
            0.014500798 = weight(_text_:information in 2445) [ClassicSimilarity], result of:
              0.014500798 = score(doc=2445,freq=12.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.2850541 = fieldWeight in 2445, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2445)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    This article explores how to develop complex data driven user models that go beyond the bag of words model and topical relevance. We propose to learn from rich user specific information and to satisfy complex user criteria under the graphical modelling framework. We carried out a user study with a web based personal news filtering system, and collected extensive user information, including explicit user feedback, implicit user feedback and some contextual information. Experimental results on the data set collected demonstrate that the graphical modelling approach helps us to better understand the complex domain. The results also show that the complex data driven user modelling approach can improve the adaptive information filtering performance. We also discuss some practical issues while learning complex user models, including how to handle data noise and the missing data problem.
    Footnote
    Beitrag in einem Themenheft "Adaptive information retrieval"
    Source
    Information processing and management. 44(2008) no.6, S.1886-1900
  3. Zhang, Y.: Undergraduate students' mental models of the Web as an information retrieval system (2008) 0.00
    4.3507366E-4 = product of:
      0.0065261046 = sum of:
        0.0065261046 = product of:
          0.013052209 = sum of:
            0.013052209 = weight(_text_:information in 2385) [ClassicSimilarity], result of:
              0.013052209 = score(doc=2385,freq=14.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.256578 = fieldWeight in 2385, 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=2385)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    This study explored undergraduate students' mental models of the Web as an information retrieval system. Mental models play an important role in people's interaction with information systems. Better understanding of people's mental models could inspire better interface design and user instruction. Multiple data-collection methods, including questionnaire, semistructured interview, drawing, and participant observation, were used to elicit students' mental models of the Web from different perspectives, though only data from interviews and drawing descriptions are reported in this article. Content analysis of the transcripts showed that students had utilitarian rather than structural mental models of the Web. The majority of participants saw the Web as a huge information resource where everything can be found rather than an infrastructure consisting of hardware and computer applications. Students had different mental models of how information is organized on the Web, and the models varied in correctness and complexity. Students' mental models of search on the Web were illustrated from three points of view: avenues of getting information, understanding of search engines' working mechanisms, and search tactics. The research results suggest that there are mainly three sources contributing to the construction of mental models: personal observation, communication with others, and class instruction. In addition to structural and functional aspects, mental models have an emotional dimension.
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2087-2098
  4. Tenopir, C.; Wang, P.; Zhang, Y.; Simmons, B.; Pollard, R.: Academic users' interactions with ScienceDirect in search tasks : affective and cognitive behaviors (2008) 0.00
    3.2888478E-4 = product of:
      0.0049332716 = sum of:
        0.0049332716 = product of:
          0.009866543 = sum of:
            0.009866543 = weight(_text_:information in 2027) [ClassicSimilarity], result of:
              0.009866543 = score(doc=2027,freq=8.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.19395474 = fieldWeight in 2027, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2027)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    This article presents part of phase 2 of a research project funded by the NSF-National Science Digital Library Project, which observed how academic users interact with the ScienceDirect information retrieval system for simulated class-related assignments. The ultimate goal of the project is twofold: (1) to find ways to improve science and engineering students' use of science e-journal systems; (2) to develop methods to measure user interaction behaviors. Process-tracing technique recorded participants' processes and interaction behaviors that are measurable; think-aloud protocol captured participants' affective and cognitive verbalizations; pre- and post-search questionnaires solicited demographic information, prior experience with the system, and comments. We explored possible relationships between affective feelings and cognitive behaviors. During search interactions both feelings and thoughts occurred frequently. Positive feelings were more common and were associated more often with thoughts about results. Negative feelings were associated more often with thoughts related to the system, search strategy, and task. Learning styles are also examined as a factor influencing behavior. Engineering graduate students with an assimilating learning style searched longer and paused less than those with a converging learning style. Further exploration of learning styles is suggested.
    Footnote
    Beitrag eines Themenbereichs: Evaluation of Interactive Information Retrieval Systems
    Source
    Information processing and management. 44(2008) no.1, S.105-121
  5. Chung, W.; Zhang, Y.; Huang, Z.; Wang, G.; Ong, T.-H.; Chen, H.: Internet searching and browsing in a multilingual world : an experiment an the Chinese Business Intelligence Portal (CBizPort) (2004) 0.00
    2.848226E-4 = product of:
      0.004272339 = sum of:
        0.004272339 = product of:
          0.008544678 = sum of:
            0.008544678 = weight(_text_:information in 2393) [ClassicSimilarity], result of:
              0.008544678 = score(doc=2393,freq=6.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.16796975 = fieldWeight in 2393, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2393)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    The rapid growth of the non-English-speaking Internet population has created a need for better searching and browsing capabilities in languages other than English. However, existing search engines may not serve the needs of many non-English-speaking Internet users. In this paper, we propose a generic and integrated approach to searching and browsing the Internet in a multilingual world. Based an this approach, we have developed the Chinese Business Intelligence Portal (CBizPort), a meta-search engine that searches for business information of mainland China, Taiwan, and Hong Kong. Additional functions provided by CBizPort include encoding conversion (between Simplified Chinese and Traditional Chinese), summarization, and categorization. Experimental results of our user evaluation study show that the searching and browsing performance of CBizPort was comparable to that of regional Chinese search engines, and CBizPort could significantly augment these search engines. Subjects' verbal comments indicate that CBizPort performed best in terms of analysis functions, cross-regional searching, and user-friendliness, whereas regional search engines were more efficient and more popular. Subjects especially liked CBizPort's summarizer and categorizer, which helped in understanding search results. These encouraging results suggest a promising future of our approach to Internet searching and browsing in a multilingual world.
    Footnote
    Teil eines Themenheftes zu: Information seeking research
    Source
    Journal of the American Society for Information Science and Technology. 55(2004) no.9, S.818-831
  6. Zhang, Y.; Xu, W.: Fast exact maximum likelihood estimation for mixture of language model (2008) 0.00
    2.79068E-4 = product of:
      0.0041860198 = sum of:
        0.0041860198 = product of:
          0.0083720395 = sum of:
            0.0083720395 = weight(_text_:information in 2082) [ClassicSimilarity], result of:
              0.0083720395 = score(doc=2082,freq=4.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.16457605 = fieldWeight in 2082, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2082)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language model of a given document (or document set), and then do retrieval or classification based on this model. A common language modeling approach assumes the data D is generated from a mixture of several language models. The core problem is to find the maximum likelihood estimation of one language model mixture, given the fixed mixture weights and the other language model mixture. The EM algorithm is usually used to find the solution. In this paper, we proof that an exact maximum likelihood estimation of the unknown mixture component exists and can be calculated using the new algorithm we proposed. We further improve the algorithm and provide an efficient algorithm of O(k) complexity to find the exact solution, where k is the number of words occurring at least once in data D. Furthermore, we proof the probabilities of many words are exactly zeros, and the MLE estimation is implemented as a feature selection technique explicitly.
    Source
    Information processing and management. 44(2008) no.3, S.1076-1085
  7. Zhang, Y.: Using the Internet for survey research : a case study (2000) 0.00
    2.6310782E-4 = product of:
      0.0039466172 = sum of:
        0.0039466172 = product of:
          0.0078932345 = sum of:
            0.0078932345 = weight(_text_:information in 4294) [ClassicSimilarity], result of:
              0.0078932345 = score(doc=4294,freq=2.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.1551638 = fieldWeight in 4294, 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=4294)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Source
    Journal of the American Society for Information Science. 51(2000) no.1, S.57-68
  8. Zhang, X.; Li, Y.; Liu, J.; Zhang, Y.: Effects of interaction design in digital libraries on user interactions (2008) 0.00
    2.3255666E-4 = product of:
      0.0034883497 = sum of:
        0.0034883497 = product of:
          0.0069766995 = sum of:
            0.0069766995 = weight(_text_:information in 1898) [ClassicSimilarity], result of:
              0.0069766995 = score(doc=1898,freq=4.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.13714671 = fieldWeight in 1898, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1898)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    Purpose - This study aims to investigate the effects of different search and browse features in digital libraries (DLs) on task interactions, and what features would lead to poor user experience. Design/methodology/approach - Three operational DLs: ACM, IEEE CS, and IEEE Xplore are used in this study. These three DLs present different features in their search and browsing designs. Two information-seeking tasks are constructed: one search task and one browsing task. An experiment was conducted in a usability laboratory. Data from 35 participants are collected on a set of measures for user interactions. Findings - The results demonstrate significant differences in many aspects of the user interactions between the three DLs. For both search and browse designs, the features that lead to poor user interactions are identified. Research limitations/implications - User interactions are affected by specific design features in DLs. Some of the design features may lead to poor user performance and should be improved. The study was limited mainly in the variety and the number of tasks used. Originality/value - The study provided empirical evidence to the effects of interaction design features in DLs on user interactions and performance. The results contribute to our knowledge about DL designs in general and about the three operational DLs in particular.
    Theme
    Information Gateway
  9. Dang, Y.; Zhang, Y.; Chen, H.; Hu, P.J.-H.; Brown, S.A.; Larson, C.: Arizona Literature Mapper : an integrated approach to monitor and analyze global bioterrorism research literature (2009) 0.00
    2.3255666E-4 = product of:
      0.0034883497 = sum of:
        0.0034883497 = product of:
          0.0069766995 = sum of:
            0.0069766995 = weight(_text_:information in 2943) [ClassicSimilarity], result of:
              0.0069766995 = score(doc=2943,freq=4.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.13714671 = fieldWeight in 2943, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2943)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Abstract
    Biomedical research is critical to biodefense, which is drawing increasing attention from governments globally as well as from various research communities. The U.S. government has been closely monitoring and regulating biomedical research activities, particularly those studying or involving bioterrorism agents or diseases. Effective surveillance requires comprehensive understanding of extant biomedical research and timely detection of new developments or emerging trends. The rapid knowledge expansion, technical breakthroughs, and spiraling collaboration networks demand greater support for literature search and sharing, which cannot be effectively supported by conventional literature search mechanisms or systems. In this study, we propose an integrated approach that integrates advanced techniques for content analysis, network analysis, and information visualization. We design and implement Arizona Literature Mapper, a Web-based portal that allows users to gain timely, comprehensive understanding of bioterrorism research, including leading scientists, research groups, institutions as well as insights about current mainstream interests or emerging trends. We conduct two user studies to evaluate Arizona Literature Mapper and include a well-known system for benchmarking purposes. According to our results, Arizona Literature Mapper is significantly more effective for supporting users' search of bioterrorism publications than PubMed. Users consider Arizona Literature Mapper more useful and easier to use than PubMed. Users are also more satisfied with Arizona Literature Mapper and show stronger intentions to use it in the future. Assessments of Arizona Literature Mapper's analysis functions are also positive, as our subjects consider them useful, easy to use, and satisfactory. Our results have important implications that are also discussed in the article.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.7, S.1466-1485
  10. Zhang, Y.: Scholarly use of Internet-based electronic resources (2001) 0.00
    1.9733087E-4 = product of:
      0.002959963 = sum of:
        0.002959963 = product of:
          0.005919926 = sum of:
            0.005919926 = weight(_text_:information in 5212) [ClassicSimilarity], result of:
              0.005919926 = score(doc=5212,freq=2.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.116372846 = fieldWeight in 5212, 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=5212)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.8, S.628-654
  11. Zhang, Y.: ¬The influence of mental models on undergraduate students' searching behavior on the Web (2008) 0.00
    1.9733087E-4 = product of:
      0.002959963 = sum of:
        0.002959963 = product of:
          0.005919926 = sum of:
            0.005919926 = weight(_text_:information in 2097) [ClassicSimilarity], result of:
              0.005919926 = score(doc=2097,freq=2.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.116372846 = fieldWeight in 2097, 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=2097)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Source
    Information processing and management. 44(2008) no.3, S.1330-1345
  12. Zhang, Y.; Li, Y.: ¬A user-centered functional metadata evaluation of moving image collections (2008) 0.00
    1.6444239E-4 = product of:
      0.0024666358 = sum of:
        0.0024666358 = product of:
          0.0049332716 = sum of:
            0.0049332716 = weight(_text_:information in 1884) [ClassicSimilarity], result of:
              0.0049332716 = score(doc=1884,freq=2.0), product of:
                0.050870337 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.028978055 = queryNorm
                0.09697737 = fieldWeight in 1884, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1884)
          0.5 = coord(1/2)
      0.06666667 = coord(1/15)
    
    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.8, S.1331-1346