LIBRARIANSHIP AND INFORMATION ORGANIZATION STUDIES (JOURNAL OF NATIONAL STUDIES ON LIBRARIANSHIP AND INFORMATION ORGANIZATION)
Year:2020 | Volume:31 | Issue:3 (123)|Papers Count:8

Purpose: To identify factors influencing the future of text information retrieval systems with a forward-looking approach. Methodology: Document analysis and survey are used to identify factors. The research population in the document analysis section consists of literature related to the textual information retrieval field and in the survey section consists of the specialists in information retrieval. Purposive sampling is applied in both sections. Findings: The results reveal that among the examined indicators, technology index is the most important index in the future of information retrieval systems. in technology index, artificial intelligence with an importance factor of 93 in the political index, copyright with 86 importance factor; in the sociocultural index, business reliance on the information with 87 importance factor; and in the economic index, programs associated with 86 importance factor are among the highest. Conclusion: Information science professionals should concentrate more on all key identified factors if they want to have a more effective contributive role in the future of textual information retrieval systems, because knowing the past, understanding the present, and focusing on these existing factors can make the future more effectively.

Purpose: To propose a basis for a library classification scheme based on cultural and doctrinal values of the Islamic world. Methodology: Views of Muslim scholars on classification of sciences are reviewed and compared with existing library classification schemes. Finding &Results: Since early 8th century Muslim scholars have proposed classifications for sciences in accordance to their jurisprudential-moral, ethical-educational, and moral-educational approaches, some having novel features and merits which could be used in developing alternative library classification schemes.

Background and Purpose: Considering the important role of social networks, this study aims to identify factors affecting relevance in LinkedIn. Method: 17 information specialists participated in the study. Data was collected using semi-structured interviews, then coded and analyzed using Dickelman method. Results: 441 primary codes and seven categories including information system, retrieval system, document attributes, database attributes, user attributes, requests and queries, and feedback. Conclusion: LinkedIn plays an important role in meeting the information needs of the participants

Purpose: The main purpose of information retrieval systems is to retrieve relevant information for users. This means that the results of the search must answer the questions provided to the system. Therefore, the evaluation of relevance is very important in such systems. In addition to relevance, the order and placement of articles are also important to the user. The retrieval systems should put more relevant articles at the top of the retrieval list. Evaluating the quality of ranking performance is a key activity in the field of information retrieval. This article assesses relevance and ranking of two databases. Methodology: The sample includes 390 Persian articles retrieved in each of the Noormags and RICeST databases. For each topic inquired were carried out in both databases in two phases within the span of one month. The first 10 articles retrieved from each database were recorded based on the system ranking. Relevance score was given by 3 subject specialists within the range of zero to ten. Spearman correlation test was used to compare the ranking of the system with the ranking of the user. Data analysis was performed using descriptive and inferential statistics using SPSS software. The distance precision formula carried out to check the accuracy of the retrieval precision of related documents in the two databases, and the expected Reciprocal Rank was used to evaluate the quality of the ranking of articles. Results: Users were far less familiar with RICeST database. Significant, consistent, and moderate correlation was found between system rankings and user rankings at the Noormags database in the first phase, i. e., ranking by users increases or decreases as the system rank increases or decreases. We found significant, consistent, and strong correlation between system’ s ranking and user ranking in Noormags in the second phase. However, there was no correlation between system ranking and user ranking in RICeST database in both the first and second phases. Therefore, Noormags database ranking was found closer to the users’ ranking. Ranking quality by Noormags was relatively better than that of RICeST. Also, accuracy of the relevance precision of Noormags articles was higher than RICeST. From the users’ point of view, Noormags database retrieved more relevant documents. Conclusion: Noormags’ new algorithms and capabilities have increased the relevance and ranking of its output. The findings could help database administrators to upgrade their databases by taking advantage of technologies to make semantic retrieval possible.

Purpose: To uncover the phenomenon of otherness in assigning subjects to library materials by the Library of Congress. Methodology: 384 titles on the subjects of Islam catalogued between 2016 to 2019 were retrieved from LC’ s OPAC and compared with the tags assigned to them by users in the website of LibraryThing. Findings: Average number of subjects assigned by social tagging to each title was around 15, much higher than the average 3. 5 by LCHS. In addition, 83% of the tags did not match either conceptual or linguistic with the subject headings assigned. Around 68% of the tags which did not match the subject heading were taken from the content of titles. Conclusion: The structure of subject headings has resulted in marginalizing some subjects, whereas tags provide an opportunity to representation others views.

Objective: To explore future components of entrepreneurial business research in information science with a meta-analytical approach. Methodology: 1709 LIS journals articles on the topic published between 2000 and 2019 were reviewed. Sixteen were selected for metaanalysis. A total of 31 components were identified. CMA2 software and Cohen’ s effect size approach were used for data analysis. Finedings: The single and combined effect size of all components were significant. Physical infrastructure showed the highest effect size (0. 83). Scientific morale of the educators (0. 78) and “ Self Confidence” (0. 75) were in the next ranks. Conclusion: In order to enhance entrepreneurship business among LIS graduates, the above variables should be considered in desing and implementing programs.

Purpose: The objective of the present study has been to systematically review semantic research studies on social tagging systems in order to identify the researchers’ areas of interest, to investigate the impact of semantic issues on information retrieval in such systems, and to identify research gaps in this area. Methodology: Ninety-eight studies were found by searching relevant databases. After initial investigation and consultation with two specialists in the field, 41 studies published in 2003-2018 were reviewed. Findings: Important topics of semantic research on social tagging systems include producing an automatic semantic tagging algorithm, designing a semantic tagging system, producing an algorithm, extracting hierarchical relationship f rom a set of tags, and using Wo rdNet to determine semantic relatio n ships among tags. In addition, research gaps identified include de v ising a method for identifying sources containing a specific mea n ing of a tag without having to review all sources, exploring the possibility of using clustering methods to cluster sources or users of folk s onomies, and designing a semant ic tagging system which is user-friendly. All of these issues should be taken into account in future research. Conclusion: Given the gaps identified, the subject of semantics in tagging systems needs further investigation, as it has a direct impact on search and retrieval by these systems.