Digital Information Retrieval System Research Articles

РОЗРОБКА АДАПТИВНИХ АЛГОРИТМІВ РОЄВОГО ІНТЕЛЕКТУ У ПРОЕКТУВАННІ ТА УПРАВЛІННІ ІНЖЕНЕРНИМИ СИСТЕМАМИ

The article examines the design and management of engineering systems in the context of growing data volumes in local computer networks. With the development of swarm intelligence, the probability of the existence of the necessary information for managing engineering systems increases, but the possibility of finding it decreases. This creates the need to develop new methods and tools for using adaptive algorithms of swarm intelligence. The purpose of such algorithms is to ensure the ability to process information and find queries with maximum relevance, generating the largest number of search results (SERPs) containing technical information. The development of swarm intelligence algorithms is impossible without their intellectualization, which includes semantic and syntactic analysis of texts, natural language tools, and intelligent algorithms for determining the significance of information resources. In digital information retrieval systems (DIRS), a query is formed in the form of keywords or their combinations, connected by logical operations. To search for the same information, different keywords are used, the choice of which is subjective. The first stage of the algorithm consists in determining the set of meaningful correspondences and forming the initial set of requests within the engineering system. To ensure the completeness of the selection, the total relevance of the SERP in relation to the group of significance criteria is considered. There is a need to develop an efficient neural network algorithm to solve the problem of assigning one SERP to each group of query criteria. This will make it possible to distribute SERPs by criteria groups so that each page is evaluated mainly by one criteria group, and the total relevance of all groups is maximized. Thus, the article emphasizes the importance of developing new methods and tools for implementing adaptive swarm intelligence algorithms in engineering systems. Special attention is paid to the development of effective neural network algorithms that will ensure optimal distribution of the relevance of search pages, which will increase the accuracy and efficiency of information search in complex engineering systems.

Ranking of Search Requests in the Digital Information Retrieval System Based on Dynamic Neural Networks

The article is devoted to the problem of optimization of search request ranking algorithms in the digital information retrieval system. The algorithm of functioning of the neural network ranking unit based on Hopfield neural network is built. The ability to generate a ranked list of pages found as a result of the request in the digital information retrieval system can be provided by solving two problems of integer optimization: the problem of assignment of combinatorial sets of criteria for assessing the relevance of web page search and the problem of sorting of numbers—relevance values. The architecture of the neural network model based on the dynamic Hopfield neural network with binary output function designed for combinatorial optimization of the final list of documents found in the digital information retrieval system was synthesized. Promising variants of neural network models with binary output function of neurons for synthesis of the optimal evaluation plan with a combinatorial set of criteria by solving the problem of assignment were built. It has been proven that the built models differ in the rules for determining the coefficients of synaptic connections and external shifts; each of the created rules can be used independently or in different combinations with one another. In the course of analytical research, it was found that the optimization formulation of the problem of sorting of relevance values of search pages is identical to the problem of assignment of combinatorial groups of evaluation criteria provided that the elements of the performance matrix of the latter are defined as linear combinations of relevance values.

Searching business information in digital information systems of Russian libraries

The author continues with her study initially presented in the article “The possibilities of information search in electronic platforms of Russian libraries” (A. V. Kulikova. The possibilities of information search in electronic platforms of russian libraries // The Journal of Encyclopaedic Studies. – 2019. – No 2. – P. 30–52). She demonstrates the methods to be applied for business information search related to local encyclopaedic book publications and identifies the principles to find recent publications promptly and to satisfy user demands most effectively. The bibliographic search success depends upon how the user understands the system. Optimum query formulation saves time and excludes information noise. The key characteristics of library digital information retrieval systems are discussed. The computer systems of 113 regional libraries were analyzed within the study. The following automated library information were tested objectively: IRBIS, RUSLAN, OPAC-Global, Foliant, MacWeb. The author does not intend to advertise or subvertise any ALIS. Her main goal is to reveal the convenient and speedy retrieval methods with existing functionalities.

Multilingual Dictionary of Keywords as a Tool for the Digital Bibliographic Database of World Slavic Linguistics

The paper presents the structure of a multilingual dictionary of keywords, which is an integral part of the bibliographic database of Slavic linguistics iSybislaw representing the digital information retrieval system (www.isybislaw.ispan.waw.pl). The lexical units (keywords) of the language of keywords used in the system are represented primarily by linguistic terms. In spite of a different denotation – the keywords directly denote sets of documents, and indirectly the non-documentary reality, while the terms denote elements of linguistic reality – they are formally equal with linguistic terms, which allows them to map the semantic field of a particular discipline, in this case Slavic linguistics. The dictionary is therefore a domain-based online specialist dictionary, which is a tool for users of the bibliographic database of Slavic linguistics. The dictionary is addressed to all those who deal with linguistics and linguistic terminology, first of all to scholar-linguists, Ph.D. students and students of philologies, as well as translators of academic papers in the field of linguistics.

Evaluating the effectiveness of thesauri in digital information retrieval systems

PurposeThe purpose of this study is to carry out a systematic literature review for evidence-based assessment of the effectiveness of thesaurus in digital information retrieval systems. It also aimed to identify the evaluation methods, evaluation measures and data collection tools which may be used in evaluating digital information retrieval systems.Design/methodology/approachA systematic literature review (SLR) of 344 publications from LISA and 238 from Scopus has been carried out to identify the evaluation studies for analysis, and 15 evaluation studies have been analyzed.FindingsThis study presents evidences for the effectiveness of thesaurus in digital information retrieval systems. Various methods for evaluating digital information systems have been identified. Also, a wide range of evaluation measures and data collection tools have been identified.Research limitations/implicationsThe study was limited to the literature published in English language and indexed in LISA and Scopus. The evaluation methods, evaluation measures and data collection tools identified in this study may be used to design more cognizant evaluation studies for digital information retrieval systems.Practical implicationsThe findings have significant implications for the administrators of any type of digital information retrieval systems in making more informed decisions toward implementation of thesaurus in resource description and access to digital collections.Originality/valueThis study extends our knowledge on the potentials of thesauri in digital information retrieval systems. It also provides cues for designing more cognizant evaluation studies for digital information systems.