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  • × author_ss:"Mostafa, J."
  1. Mukhopadhyay, S.; Peng, S.; Raje, R.; Palakal, M.; Mostafa, J.: Multi-agent information classification using dynamic acquaintance lists (2003) 0.03 
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    Abstract
    There has been considerable interest in recent years in providing automated information services, such as information classification, by means of a society of collaborative agents. These agents augment each other's knowledge structures (e.g., the vocabularies) and assist each other in providing efficient information services to a human user. However, when the number of agents present in the society increases, exhaustive communication and collaboration among agents result in a [arge communication overhead and increased delays in response time. This paper introduces a method to achieve selective interaction with a relatively small number of potentially useful agents, based an simple agent modeling and acquaintance lists. The key idea presented here is that the acquaintance list of an agent, representing a small number of other agents to be collaborated with, is dynamically adjusted. The best acquaintances are automatically discovered using a learning algorithm, based an the past history of collaboration. Experimental results are presented to demonstrate that such dynamically learned acquaintance lists can lead to high quality of classification, while significantly reducing the delay in response time.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.10, S.966-975
  2. Sugimoto, C.R.; Mostafa, J.: ¬A note of concern and context : on careful use of terminologies (2018) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.3, S.347-348
  3. Zhang, Y.; Wu, D.; Hagen, L.; Song, I.-Y.; Mostafa, J.; Oh, S.; Anderson, T.; Shah, C.; Bishop, B.W.; Hopfgartner, F.; Eckert, K.; Federer, L.; Saltz, J.S.: Data science curriculum in the iField (2023) 0.01 
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    Abstract
    Many disciplines, including the broad Field of Information (iField), offer Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.
    Footnote
    Beitrag in einem Special issue on "Data Science in the iField".
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.6, S.641-662
  4. Mostafa, J.; Hall, D.M.: ¬A proposed quantitative methodology to characterize the corporate library universe : the role of personal research interests (2018) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.5, S.760
  5. Mongin, L.; Fu, Y.Y.; Mostafa, J.: Open Archives data Service prototype and automated subject indexing using D-Lib archive content as a testbed (2003) 0.01 
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    Abstract
    The Indiana University School of Library and Information Science opened a new research laboratory in January 2003; The Indiana University School of Library and Information Science Information Processing Laboratory [IU IP Lab]. The purpose of the new laboratory is to facilitate collaboration between scientists in the department in the areas of information retrieval (IR) and information visualization (IV) research. The lab has several areas of focus. These include grid and cluster computing, and a standard Java-based software platform to support plug and play research datasets, a selection of standard IR modules and standard IV algorithms. Future development includes software to enable researchers to contribute datasets, IR algorithms, and visualization algorithms into the standard environment. We decided early on to use OAI-PMH as a resource discovery tool because it is consistent with our mission.
  6. Heffron, J.K.; Dillon, A.; Mostafa, J.: Landmarks in the World Wide Web : a preliminary study (1996) 0.01 
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    Source
    Global complexity: information, chaos and control. Proceedings of the 59th Annual Meeting of the American Society for Information Science, ASIS'96, Baltimore, Maryland, 21-24 Oct 1996. Ed.: S. Hardin
  7. Mostafa, J.: Digital image representation and access (1994) 0.01 
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    Source
    Annual review of information science and technology. 29(1994), S.91-135
  8. Lam, W.; Mostafa, J.: Modeling user interest shift using a Baysian approach (2001) 0.01 
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    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.5, S.416-429
  9. Mostafa, J.; Dillon, A.: Design and evaluation of a user interface supporting multiple image query models (1996) 0.01 
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    Source
    Global complexity: information, chaos and control. Proceedings of the 59th Annual Meeting of the American Society for Information Science, ASIS'96, Baltimore, Maryland, 21-24 Oct 1996. Ed.: S. Hardin
  10. Mostafa, J.; Quiroga, L.M.; Palakal, M.: Filtering medical documents using automated and human classification methods (1998) 0.01 
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    Source
    Journal of the American Society for Information Science. 49(1998) no.14, S.1304-1318
  11. Mostafa, J.: Document search interface design : background and introduction to special topic section (2004) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 55(2004) no.10, S.869-872
  12. Mukhopadhyay, S.; Peng, S.; Raje, R.; Mostafa, J.; Palakal, M.: Distributed multi-agent information filtering : a comparative study (2005) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.8, S.834-842
  13. Mostafa, J.: Bessere Suchmaschinen für das Web (2006) 0.00 
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    Date
    22. 1.2006 18:34:49

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