Maryam Azimian; Nusrat Riahi Nia; Ali azimi vaghar; Keyvan Borna
Abstract
Purpose: The main purpose of this study is to design and evaluate a book recommender system in digital and public libraries. The solution has been provided by receiving and reviewing the preferences and experiences of users and profile information and studying the background of each user, as well as ...
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Purpose: The main purpose of this study is to design and evaluate a book recommender system in digital and public libraries. The solution has been provided by receiving and reviewing the preferences and experiences of users and profile information and studying the background of each user, as well as considering groups of features recorded in the recommendation process. Method: This research is applied in terms of purpose and survey method. The statistical population studied in this research consists of 263 questionnaires of users and 30 questionnaires of librarian experts. In order to find similarity between users and books, clustering and grouping have been used. Findings: There are two criteria for grouping: users grouping that can be used on the three indicators of age, gender, educational level, and thematic classification of books can be based on scope, branch, and sub-category. In analyzing the data in the descriptive statistics section, Excel software is used and in the analytical section, SPSS software. Findings indicate that the accuracy criterion has been improved by calculating MAE and RSME in the proposed method compared to the basic method in this field. The results also showed that classification can have a significant impact on the forecast and performance of book forecasting systems. Conclusion: The evaluation of the conceptual design showed that by focusing on user characteristics and obtaining real feedback of Iranian libraries, the recommender can serve as a key and effective element in the service of the Iranian readership community and play a good role as a virtual reference librarian.
Sedigheh Mohammadesmaeil
Abstract
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, ...
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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.