MODELS AND ALGORITHMS FOR OPTIMIZING LEGAL INFORMATION RETRIEVAL IN THE CORPORATE NETWORK OF ACADEMIC LIBRARIES
DOI:
https://doi.org/10.17770/sie2023vol1.7123Keywords:
algorithmizing, functional modeling, fuzzy set theory, hierarchical analysis, mathematical modeling, mathematical statistics, semantic searchAbstract
With the rapid growth of information in the global network, the challenges of finding information quickly and easily in a narrow range of fields of study and specialization are increasing. People are constantly looking for information in some form throughout their lives. This is the result of the constant striving of human beings for innovation, efforts to improve personal and professional competencies. One of the main objectives of libraries is to meet people’s needs for information. In short, this process can be called the type of informational support. The main purpose of this research is to develop models and algorithms to optimize the effective search of information about health information in corporate networks. Electronic libraries in the field of jurisprudence serve not only to train personnel in the field of jurisprudence, but also to increase legal literacy in society, to make citizens aware of their rights and obligations, and to prevent them from becoming victims of various frauds. For organizations, it serves as the most important repository of knowledge for their employees to constantly update their legal knowledge, to draw up normative-legal documents, contracts and agreements within the framework of legal requirements. Despite the fact that the field of jurisprudence is one of the most important areas of activity, the provision of scientific information to this field is not sufficiently systematized. Different organizations and institutions store their existing legal literature in the way they choose, and there is no single mechanism for making it available to users, digitizing, classifying, and searching for it. Most library users rate the efficiency of the library by the availability of the necessary literature. A survey of law students and professors was conducted to examine the interest of library users in legal electronic literature and their use. More than 50% of respondents use the electronic library daily, 93% are looking for legal literature, and 50% of participants said it is difficult to find legal literature. Also, all respondents (100%) approved the need to create a single corporate network by pooling electronic resources of higher education institutions providing legal training.
References
Avram, H. D. (1975). MARC: its history and implications. Library of Congress MARC Development Office. Retrieved from https://files.eric.ed.gov/fulltext/ED127954.pdf
Bufnea, D. (2012). Analyzing and Tuning User Queries to Search Engines. Studia Universitatis Babeş-Bolyai, Seria Informatica. LVII. 41-48.
Cassell, K. A., Hiremath, U. (2014) Information and information systems in the 21st century. 2en edition. 131-146.
Davies, D. (2020). How Search Engines Display Search Results. Retrieved from https://www.searchenginejournal.com/search-engines/display-search-results/
Gunjal, A. (2016). The Process of Information Retrieval. Retrieved from https://amitgunjal.wordpress.com/2016/11/21/the-process-of-information-retrieval-from-scratch/
Jo, D. T., Lee, M., & Gatton, T. (2006). Keyword Extraction from Documents Using a Neural Network Model. Hybrid Information Technology, International Conference on. 2. 194-197. DOI:10.1109/ICHIT.2006.253612
Karimov, U., & Rakhmatullaev, M. (2008). Corporate information-library systems and networks. Monograph. Retrieved from https://scholar.google.com/citations?view_op=view_citation&hl=ru&user=swaB3GoAAAAJ&citation_for_view=swaB3GoAAAAJ:qxL8FJ1GzNcC
Kuchimov, Sh. (2020). Legal terminology of the Uzbek language: problems and solutions. Retrieved from https://cyberleninka.ru/article/n/yuridicheskaya-terminologiya-uzbekskogo-yazyka-problemy-i-resheniya
Okogwu, F. (2021). Understanding Electronic Resources Collection Development Practices Through Selected Theories. Retrieved from https://www.researchgate.net/publication/352835142_Understanding_Electronic_Resources_Collection_Development_Practices_Through_Selected_Theories
Siddiqi, S., & Sharan, A.. (2015). Keyword and Keyphrase Extraction Techniques: A Literature Review. International Journal of Computer Applications. 109. 18-23. DOI: 10.5120/19161-0607
Soumya, Sh. (2021). Klink search: enabling exploratory browsing activities in digital libraries. Retrieved from https://ourspace.uregina.ca/bitstream/handle/10294/14366/Shukla_Soumya_MSC_CS_Spring2021.pdf
Taylor, M. (2020). Search Results: Predicting Ranking Algorithms With User Ratings and User-Driven Data. Retrieved from https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=9609&context=dissertations
The National Electronic Library of the Russian Federation. (2023). Information for libraries. Retrieved from https://rusneb.ru/for-libraries/