دانشگاه علامه طباطبایی

  اخبار و اعلانات

 آمار

تعداد نشریات60
تعداد شماره‌ها2,022
تعداد مقالات16,253
تعداد مشاهده مقاله42,491,285
تعداد دریافت فایل اصل مقاله24,319,739
Mohammadesmaeil, Sedigheh. (1399). Clustering of the Iranian Asthma and allergy specialists'''' clinical information-seeking behavior by Neural network analysis. سامانه مدیریت نشریات علمی, 2(3), 99-114. doi: 10.22054/dcm.2020.56672.1011
Sedigheh Mohammadesmaeil. "Clustering of the Iranian Asthma and allergy specialists'''' clinical information-seeking behavior by Neural network analysis". سامانه مدیریت نشریات علمی, 2, 3, 1399, 99-114. doi: 10.22054/dcm.2020.56672.1011
Mohammadesmaeil, Sedigheh. (1399). 'Clustering of the Iranian Asthma and allergy specialists'''' clinical information-seeking behavior by Neural network analysis', سامانه مدیریت نشریات علمی, 2(3), pp. 99-114. doi: 10.22054/dcm.2020.56672.1011
Mohammadesmaeil, Sedigheh. Clustering of the Iranian Asthma and allergy specialists'''' clinical information-seeking behavior by Neural network analysis. سامانه مدیریت نشریات علمی, 1399; 2(3): 99-114. doi: 10.22054/dcm.2020.56672.1011

Clustering of the Iranian Asthma and allergy specialists'''' clinical information-seeking behavior by Neural network analysis

International Journal of Digital Content Management
مقاله 5، دوره 2، شماره 3، خرداد 2021، صفحه 99-114    اصل مقاله (969.51 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22054/dcm.2020.56672.1011
نویسنده
Sedigheh Mohammadesmaeil*
Department of Knowledge and Information Science, Islamic Azad University, Research and Science Branch, Tehran
چکیده
Introduction: The aim of this study was to determine the information retrieval and information therapy behavior of Asthma and allergy specialists in the country, based on cohonen self-organized neural network model.
Methods: The methodology of the present study, which is an applied study in terms of purpose, has been done by descriptive-survey method using neural network technique. The tool of this research is a researcher-made questionnaire that was distributed among a sample of people in the community (149 people). After collecting the data, the neural network was selected for data clustering and using MATLAB software, Asthma and allergy specialists were clustered based on the main components of the research. Then, by removing each of the main sub-components of the research, the most effective and least effective option in their information-seeking behavior in working with information resources in this specialized field was determined.
Results: The most effective component in clustering information barriers, was "lack of time due to workload" and the least was "distance of libraries and information centers". About information retrieval skills, the most effective component is " knowing what keywords to use when searching the Internet, and to be familiar with synonyms and terms related to the information I need."
Conclusion: By studying the clustering of information behaviors resulting from the information needs of Asthma and allergy specialists, their needs are recognized, and this is one of the measures that provides the basis for effective research, appropriate findings and ,consequently, informational decision-making for those involved in this field.
کلیدواژه‌ها
Clustering؛ Clinical Information؛ Seeking Behavior؛ Cohesion Self؛ Organized Neural Network؛ Asthma & Allergy Research Institute (IAARI)؛ Iran
مراجع
Ahmad, M. and Abawajy, J.H. (2014a), “Digital library service quality assessment model”, Procedia –

Social and Behavioral Sciences, Vol. 129, pp. 571-580.

Ahmad, M. and Abawajy, J.H. (2014b), “Service level agreements for the digital library”, Procedia –Social and Behavioral Sciences, Vol. 147, pp. 237-243.

Alizadeh, S. Malek Mohammadi, Q. (2011),” Data Mining and Step-by-Step Knowledge Discovery with Clementine Software”, Tehran: Khaje Nasir al-Din Tusi University, [in Persian]

Badr, A. Mohammadesmaeil, S. (2015), “Classification of Target Users of Central Library of Isfahan University of Technology by Data Mining Approach, MSc Thesis, Faculty of Humanities”, Islamic Azad University, Science and Research Branch, Tehran, Iran, Supervisor: Sedigheh Mohammadesmaeil. [in Persian]

Brooks, R.F., Lings, I.N. and Botschen, M.A. (1999), “Internal marketing and customer driven wavefronts”, The Service Industries Journal, Vol. 19 No. 4, pp. 49-67.

Dadzie, P.S. (2005), “Electronic resources: access and usage at Ashesi university college”, Campus-Wide Information Systems, Vol. 22 No. 5, pp. 290-297.

Edwards, S. and Browne, M. (1995), “Quality in information services: do users and librarians differ in their expectations?”, Library and Information Science Research, Vol. 17 No. 2, pp. 163-182.

Hersh, W. (2020), Information Retrieval: A Biomedical and Health Perspective. 4th ed. USA, Springer.

Kennedy, M.L. (2018), “The opportunity for research libraries in 2018 and Beyond”, Portal: Libraries and the Academy, Vol. 18 No. 4, pp. 629-637.

Kim, J.-A. (2016), “Dimensions of user perception of academic library as place”, The Journal of Academic Librarianship, Vol. 42 No. 5, pp. 509-514.

Kiran, K. (2010), “Service quality and customer satisfaction in academic libraries”, Library Review, Vol. 59 No. 4, pp. 261-273.

Kiran, K. and Diljit, S. (2012), “Modeling web-based library service quality”, Library and Information Science Research, Vol. 34 No. 3, pp. 184-196.

Lane, F.C., Anderson, B., Ponce, H.F. and Natesan, P. (2012), “Factorial invariance of LibQUALþVR as a measure of library service quality over time”, Library and Information Science Research, Vol. 34

No. 1, pp. 22-30.

McCaffrey, C. (2019), “Transforming the university library one step at a time: a ten year LibQUALþ review”, New Review of Academic Librarianship, Vol. 25 No. 1, pp. 59-75.

Mirghafoori, S. H., Sayyadi Tooranloo, H., & Saghafi, S. (2020). Diagnosing and routing electronic service quality improvement of academic libraries with the FMEA approach in an intuitionistic fuzzy environment. Electronic Library, Vol.38 No.3, pp. 597–631. https://doi.org/10.1108/EL-09-2019-0218

Mirza, M.S. and Mahmood, K. (2012), “Electronic resources and services in Pakistani university libraries: a survey of users’ satisfaction”, The International Information and Library Review, Vol. 44 No. 3, pp. 123-131.

Moghaddassi, H. Hoseini, A. Asadi, F. (2012), Jahanbakhsh M. Application of Data Mining. Heal Inf Manag, Vol. 9 No. 2, p.304. [Persian]

Montgomery, S.E. (2014), “Library space assessment: user learning behaviors in the library”, The Journal of Academic Librarianship, Vol. 40 No. 1, pp. 70-75.

Nabovati E, Azizi A, Abbasi E, Vakili-Arki H, Zarei J, Razavi A. (2014), Using Data Mining to Predict Outcome in Burn Patients: A Comparison between Several Algorithms. Heal Inf Manag, Vol.10 No.6, p.799. [Persian]

Naimi J, Mohammadesmaeil S, Heydari H. (2019), “Determining Information Needs and Information Behavior of Khorasan Razavi Seminary Students Using Neural Network Approach”, Journal of Library and Information Science, Vol.4, No.1, pp.118-91 [in Persian]

Parhamnia F. (2008),” Introduction to Information”, Kermanshah: Islamic Azad University [in Persian]

Poll, R. (2005), “Measuring the impact of new library services”, World Library and Information Congress: 71th IFLA General Conference and Council.

Sinclair, B. (2014), “The university library as incubator for digital scholarship”, Educause Review, Vol. 24.

Zare_Farashbandi F, Yarahmadi A. (2015), ”Information Therapy: A New Approach with Old Concept in Improvement of Chronic Diseases”, Health Inf Manage, Vol.12, No.1, p.135 [in Persian]

آمار
تعداد مشاهده مقاله: 127
تعداد دریافت فایل اصل مقاله: 38


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب
login