Showing 4 results for Database
Fatemeh Zandian, Anahita Dashti, Mohammad Hasanzade,
Volume 1, Issue 1 (4-2014)
Abstract
Background and Aim: The main objective of this research was to investigate the use of full-text databases in the LIS theses of Tehran State Universities within the years 2005 and 2009.
Method: For this purpose, the total of 9952 citations related to 172 existing theses in the academic central libraries were studied. The data collected were analyzed by the bibliometrics and citation analysis methods.
Results: The results showed that only 499 (5.01%) out of the total of 9952 citations were of full-text databases. By the use of Bradford law, the Emerald, Iran Doc. Pro Quest and Science Direct were chosen as the core databases in LIS. There was no statistically significance difference in the use of full-text databases with regard to database, university and subject. Citing the linguistic distribution of full-text data showed that most citations were in English language. Finally, the amount of the use of full-text databases by the theses has not been increased between the years 2005 and 2009.
Conclusion: The results obtained in the present research showed that the use of databases was very low and no growing trend for citing databases did show. Also English language was Dominant language in citing databases
Nosrat Riahinia, Forough Rahimi, , Leili Allahbakhshian,
Volume 2, Issue 1 (4-2015)
Abstract
Background and Aim: The main aim of Information storage and retrieval systems is keeping and retrieving the related information means providing the related documents with users’ needs or requests. This study aimed to answer this question that how much are the system relevance and User- Oriented relevance are matched in SID, SCI and Google Scholar databases.
Method: In this study 15 keywords of the most repeated ones that were related to “Human Information Interaction” and its subheadings were selected and searched both in Persian and in English in the mentioned databases for two one week periods. The results were arranged according to the system relevance based on the retrieval and displaying order. From each search the first 10 results were selected and sent to the subject experts and asked them to rank from 1 to 10. Data were descriptively and analytically (using Spearman correlation test) analyzed by SPSS software.
Results: Subject experts’ relevance score in Persian was lower in ISC than SID and higher than Google Scholar. The most subject relevant records were in the third score of system relevance. The records with the lowest system relevance score also had the lowest subject experts’ relevance score. SID in Persian had a strong and positive relation between the both scores but there was no relation in ISC. The highest matching level of the both scores was seen in SID in both languages on the both periods which means more likely to retrieve relevant records.
Conclusion: There is a similar retrieval pattern in both languages with subject expert’s view in SID showing the highest precision which was the lowest in Google scholar in Persian
Abbas Doulani, Nazila Khanoghlan, Masoumeh Karbala Aghaei Kamran,
Volume 7, Issue 3 (12-2020)
Abstract
Aim: The aim of this study is content and structural analysis of published articles in knowledge Management.
Methodology: The research method is analytical. The population encompassed all articles in the field of knowledge management indexed in the citation database of the Islamic world. Measurement tool is a checklist constructed based on research objectives.
Finding: Finding indicate that the utmost frequency is related to correlation research and the minimum is experimental and combined research method. Also the maximum data analysis methods is descriptive-deductive and the least of that is another methods. Most related to type of articles associated to research articles and journals. The most used research tool is the questionnaire. Co-authorship within the country is high. In contrast, it is insignificant at the international level. There is a meaningful relationship between the number, field and type of collaborations of authors and research methods used.
Conclusion: Instigating collaboration between authors, especially international teamwork is the requirements of scientific production processes. Revising knowledge management researches is necessary due to the recurrence of research methods that similarly cause data analysis methods repetition in most research articles.
Shabnam Refoua, Zahra Salimi,
Volume 8, Issue 2 (9-2021)
Abstract
Background and Aim: Scientific article recommender system assists and advance information retrieval process by proposing and offering articles tailored to the researchers needs. The main purpose of this study is to evaluate the performance of the recommender System in three scientific databases.
Method: This applied study is directed by the valuation method. Sample consisted of three scientific databases: Elsevier, Taylor & Francis, and Google Scholar, which share recommendation tools. "Information storage and retrieval" was selected as the search subject. Ten specialized keywords related to the topic of information storage and retrieval were selected. After searching each key words, the first retrieved article was reviewed. Then, for each first article, the first 5 recommended articles were mined in each of the three mentioned databases. Data was collected through direct observation using a researcher-made checklist. To evaluate subject relevance, bibliographic information of the first article retrieved in each subject and database along with the bibliographic information of 5 recommended articles was provided to two groups of librarians and IT professionals. Sample was selected by snowball method. Descriptive and inferential statistics were used to analyze the data.
Results: Findings showed that among the databases, Elsevier recommends more relevant results from the perspective of IT professionals and librarians in the field of information storage and retrieval, with Google Scholar and Taylor & Francis in the next ranks. In total, the most relevant articles in terms of subject experts were the articles that ranked fifth.
Conclusion: To sum up, Elsevier performed better than the other two databases in terms of recommending related articles. Also, there is a significant difference between the views of librarians and IT professionals regarding the relevance of recommended articles in the field of information storage and retrieval. Thus, from the point of view of IT professionals, the significance of the recommended articles is greater.
