|
DOI: 10.14489/vkit.2022.11.pp.052-065
Филимонов И. А.
АВТОМАТИЗАЦИЯ АДМИНИСТРИРОВАНИЯ МЕТАДАННЫХ ЭЛЕКТРОННЫХ БИБЛИОТЕК, ПОДДЕРЖИВАЮЩИХ ОБЪЕКТНЫЙ ПОИСК
(с. 52-65)
Аннотация. Представлено совершенствование работы с сетью метаданных электронной научно-технической библиотеки путем автоматизации добавления элементов решения проблем с помощью программируемых сценариев. Для режима эксплуатации библиотеки предлагается более пригодный, по сравнению с ручным, способ пополнения сети кластерами узлов, обеспечивающий бо́льшую степень автоматизации при работе с метаданными электронной библиотеки. Представлена математическая модель оценки интерфейса. Предложен пример схемы добавления кластера узлов и сравнительная оценка методов и инструментов актуализации сети проблем.
Ключевые слова: электронная библиотека; архив документов; контент библиотеки; метаданные библиотеки; объектный поиск; граф знаний; сеть проблем; инновационный цикл; автоматизация; программирование.
Filimonov I. A.
AUTOMATION OF A NETWORK OF PROBLEMS USING PROGRAMMING TOOLS
(pp. 52-65)
Abstract. One of the directions of development of metadata of electronic libraries is their selective visualization with the provision of object search in the visual network representation of metadata. One of such systems is also developed by the author of EaAIS “PoiskUM”. In the “PoiskUM” system, an attempt has been made to programmatically implement an electronic library designed for personal use and providing object search functions. In contrast to the classical dictionary search, the object search system provides the reader with the opportunity to fully or partially search through the elements of the library collection and “identify” the desired objects among them on the basis of search features located in cognitive memory. In this system, the user can see a complex network consisting of a network of scientific and technical problems on the computer screen, a network of innovative cycles of technical products related to the problems shown, and a network of library documents. This network is visualized by a representative of a special class of applied software systems – a graph editor. The graph editor builds network elements in its memory in the form of objects and shows them in its windows in the form of a table displaying the attributes of objects. Maintaining and developing the functions of replenishing the network of problems require significant manual labor from the owner of the electronic library. This article discusses proposals for automating the replenishment of structural elements of the network of problems in relation to the metadata of an electronic library that supports object search.
Keywords: Digital library; Document archives; Library content; Library metadata; Entity search; Knowledge graph; Problem network; Innovation cycle; Automation; Programming.
И. А. Филимонов (Московский авиационный институт (национальный исследовательский университет), Москва, Россия) E-mail: ilafilimonov@mai.education
1. Cognitive Network Science: A Review of Research on Cognition Through the Lens of Network Representations, Processes, and Dynamics / C. S. Siew, Dirk U. Wulff, Nicole M. Beckage et al. // Complexity. V. 2019. P. 1 – 24. DOI: 10.1155/2019/2108423
2. ГОСТ Р 7.0.96–2016. Система стандартов по информации, библиотечному и издательскому делу. Электронные библиотеки. Основные виды. Структура. Технология формирования. М.: Стандартинформ, 2016.
3. ГОСТ Р ИСО 23081-1–2008. Система стандартов по информации, библиотечному и издательскому делу. Процессы управления документами. Метаданные для документов. М.: Стандартинформ, 2009.
4. Гагарин А. П., Филимонов И. А. Сеть проблем как вход в архив документов // Современные информационные технологии и ИТ-образование. 2020. Т. 16, № 3. С. 582 – 597. URL: http:// sitito.cs.msu.ru/index.php/SITITO/article/view/681 (дата обращения: 29.10.2022).
5. Гагарин А. П., Филимонов И. А. Обогащенная сеть проблем как ядро метаданных электронной библиотеки // Современные информационные технологии и ИТ-образование. 2021. T. 17, № 4. С. 860 – 870. DOI: 10.25559/SITITO.17.202104.860-870
6. Cytoscape Automation: Empowering Work-flow-Based Network Analysis / D. Otasek, J. Morris, J. Boucas, A. Pico et al. // Computer Science. 2019. No. 185. P. 1 – 15. URL: https://www. ncbi.nlm.nih.gov/pubmed/31477170 (дата обращения: 29.10.2022).
7. Balog K. Entity-Oriented Search // The Information Retrieval Series. 2018. No. 39. P. 11 – 17. URL: https://link.springer.com/content/pdf/10.1007/978-3-319-93935-3.pdf (дата обращения: 29.10.2022).
8. Zakariya A., Jakimi A., Hajar M. An Algorithm of Conversion Between Relational Data and Graph Schema // Information Systems and Technologies to Support Learning. 2018. No. 111. P. 594 – 602. URL: https://link.springer.com/chapter/10.1007/978-3-030-03577-8_65 (дата обращения: 29.10.2022).
9. Ruggero A. Entity Search: How to Build Virtual Documents Leveraging on Graph Embeddings // Computer Science, University of Padova. 2019. P. 56 – 65. URL: http://tesi.cab.unipd.it/63164/1/ anna_ruggero_tesi.pdf (дата обращения: 29.10.2022).
10. Goncalves M., Fox E., Watson L. Kipp N. Streams, Structures, Spaces, Scenarios, Societies (5S): A Formal Model for Digital Libraries // ACM Transactions on Information Systems. 2004. No. 2. P. 270 – 312. URL: http://ei.cs.vt.edu/~dlib/pdfs/5s5.pdf (дата обращения: 29.10.2022).
11. Ferro N., Silvello G. NESTOR: A Formal Model for Digital Archives // Information Processing & Management. 2013. No. 49. P. 1206 – 1240. URL: http://www.dei.unipd.it/~ferro/papers/2013/IPM2013.pdf (дата обращения: 29.10.2022).
12. Devezas J. Graph-Based Entity-Oriented Search // ACM SIGIR Forum. 2021. No. 55. P. 29 – 79. URL: https://repositorio-aberto.up.pt/bitstream/10216/ 133205/2/450176.pdf (дата обращения: 29.10.2022).
13. Филимонов И. А. Опыт создания персональной поисковой библиографической системы, ориентированной на конкретную область научных или инженерных знаний // Труды МАИ. 2020. № 114. С. 1 – 35. URL: http://mai.ru//upload/iblock/5a9/ Filimonov_rus.pdf (дата обращения: 29.10.2022).
14. Farber M. The Microsoft Academic Knowledge Graph: a Linked Data Source with 8 Billion Triples of Scholarly Data // International Semantic Web Conference. 2019. No. 11779. P. 113 – 129. URL: https://link.springer.com/chapter/10.1007/978-3-030-30796-7_8 (дата обращения: 29.10.2022).
15. Brack A., Hoppe A., Stocker M. Requirements Analysis for an Open Research Knowledge Graph // 24th International Conference on Theory and Practice of Digital Libraries. 2020. No. 1. P. 3 – 18. URL: https://arxiv.org/pdf/2005.10334.pdf (дата обращения: 29.10.2022).
16. Wandmacher J. GOMS-Analysen MIT GOMSED // Technische Universität Darmstadt. 2019. URL: https://www.researchgate.net/publication/ 267859320_GOMS-Analysen_mit_GOMSED (дата обращения: 29.10.2022).
17. Khaet F., Alfimtsev A. The Extended Model of Goals, Operators, Methods and Selection Rules (GOMS) for Gesture Interfaces // Proceedings of the 13th Central & Eastern European Software Engineering Conference in Russia. 2017. No. 8. P. 1 – 9. URL: https://dl.acm.org/doi/10.1145/3166094.3166102 (дата обращения: 29.10.2022).
18. Jokinen J., Oulasvirta A., Howes A. Cognitive Modelling: From GOMS to Deep Reinforcement Learning // CHI Conference on Human Factors in Computing Systems Extended Abstracts. 2022. No. 121. P. 1 – 3. URL: https://dl.acm.org/doi/10.1145/ 3491101.3503771 (дата обращения: 29.10.2022).
19. Mishra W., Chowdhury A., Dhar D. Optimizing Operation Research Strategy for Design Intervention: A Framework for GOMS Selection Rule // International Conference on Research into Design. 2017. No. 65. P. 61 – 70. URL: https://link.springer.com/chapter/10.1007/978-981-10-3518-0_6 (дата обращения: 29.10.2022).
20. Beckert B., Beuster G. A Method for Formalizing, Analyzing, and Verifying Secure User Interfaces // International Conference on Formal Engineering Methods. 2006. No. 4260. P. 55 – 73. URL: https://page-one.springer.com/pdf/preview/10.1007/ 11901433_4 (дата обращения: 29.10.2022).
21. Nyström A. Gesture-Level Model: A Modified Keystroke-Level Model for Tasks on Mobile Touchscreen Devices // Computer Science. 2018. No. 1. P. 1 – 44. URL: http://uu.diva-portal.org/smash/get/ di-va2:1235821/FULLTEXT01.pdf (дата обращения: 29.10.2022).
22. The Cytoscape Automation App Article Collection / B. Demchak, D. Otasek, A. Pico., D. Bader et al. // Computer Science F1000 Research. 2018. No. 1.P. 1 – 6. URL: https://pdfs.semanticscholar.org/272f/ 482e15a7ec4eefd3576fe878e018422e24cd.pdf (дата обращения: 29.10.2022).
1. Siew C. S., Wulff Dirk U., Beckage Nicole M. et al. (2019). Cognitive Network Science: A Review of Research on Cognition through the Lens of Network Representations, Processes, and Dynamics. Complexity, Vol. 2019, pp. 1 – 24. DOI:10.1155/2019/2108423
2. System of standards on information, librarianship and publishing. Electronic libraries. Main types. Structure. Formation technology. (2016). Standard No. GOST R. 7.0.96–2016. Moscow: Standartinform. [in Russian language]
3. System of standards on information, librarianship and publishing. Document management processes. Metadata for documents. (2009). National standard No. GOST R ISO 23081-1–2008. Moscow: Standartinform. [in Russian language]
4. Gagarin A. P., Filimonov I. A. (2020). A network of problems as an entrance to the archive of documents. Sovremennye informatsionnye tekhnologii i IT-obrazovanie, Vol. 16, (3), pp. 582 – 597. Available at: http://sitito.cs.msu.ru/index.php/SITITO/article/view/681 (Accessed: 29.10.2022). [in Russian language]
5. Gagarin A. P., Filimonov I. A. (2021). An enriched network of problems as the core of digital library metadata. Sovremennye informatsionnye tekhnologii i IT-obrazovanie, Vol. 17, (4), pp. 860 – 870. [in Russian language] DOI: 10.25559/SITITO.17.202104.860-870
6. Otasek D., Morris J., Boucas J., Pico A. et al. (2019). Cytoscape Automation: Empowering Workflow-Based Network Analysis. Computer Science, 185, pp. 1 – 15. Available at: https://www.ncbi.nlm. nih.gov/pubmed/31477170 (Accessed: 29.10.2022).
7. Balog K. (2018). Entity-Oriented Search. The Information Retrieval Series, 39, pp. 11 – 17. Available at: https://link.springer.com/content/pdf/10.1007/978-3-319-93935-3.pdf (Accessed: 29.10.2022).
8. Zakariya A., Jakimi A., Hajar M. (2018). An Algorithm of Conversion Between Relational Data and Graph Schema. Information Systems and Technol-ogies to Support Learning, 111, pp. 594 – 602. Available at: https://link.springer.com/chapter/10.1007/978-3-030-03577-8_65 (Accessed: 29.10.2022).
9. Ruggero A. (2019). Entity search: How to Build Virtual Documents Leveraging on Graph Embeddings. Computer Science, pp. 56 – 65. University of Padova. Available at: http://tesi.cab.unipd.it/63164/1/anna_ruggero_tesi.pdf (Accessed: 29.10.2022).
10. Goncalves M., Fox E., Watson L. Kipp N. (2004). Streams, Structures, Spaces, Scenarios, Societies (5S): A Formal Model for Digital Libraries. ACM Transactions on Information Systems, (2), pp. 270 – 312. Available at: http://ei.cs.vt.edu/~dlib/pdfs/5s5.pdf (Accessed: 29.10.2022).
11. Ferro N., Silvello G. (2013). NESTOR: A Formal Model for Digital Archives. Information Processing & Management, 49, pp. 1206 – 1240. Available at: http://www.dei.unipd.it/~ferro/papers/2013/IPM2013.pdf (Accessed: 29.10.2022).
12. Devezas J. (2021). Graph-Based Entity-Oriented Search. ACM SIGIR Forum, 55, pp. 29 – 79. Available at: https://repositorio-aberto.up.pt/bitstream/10216/133205/ 2/450176.pdf (Accessed: 29.10.2022).
13. Filimonov I. A. (2020). Experience in creating a personal bibliographic search system focused on a specific area of scientific or engineering knowledge. Trudy MAI, 114, pp. 1 – 35. Available at: http://mai.ru//upload/iblock/5a9/Filimonov_rus.pdf (Accessed: 29.10.2022). [in Russian language]
14. Farber M. (2019). The Microsoft Academic Knowledge Graph: a Linked Data Source with 8 Billion Triples of Scholarly Data. International Semantic Web Conference, 11779, pp. 113 – 129. Available at: https://link.springer.com/chapter/10.1007/978-3-030-30796-7_8 (Accessed: 29.10.2022).
15. Brack A., Hoppe A., Stocker M. (2020). Requirements Analysis for an Open Research Knowledge Graph. 24th International Conference on Theory and Practice of Digital Libraries, (1), pp. 3 – 18. Available at: https://arxiv.org/pdf/2005.10334.pdf (Accessed: 29.10.2022).
16. Wandmacher J. (2019). GOMS-Analysen MIT GOMSED. Technische Universität Darmstadt. Available at: https://www.researchgate.net/publication/267859320_GOMS-Analysen_mit_GOMSED (Accessed: 29.10.2022).
17. Khaet F., Alfimtsev A. (2017). The Extended Model of Goals, Operators, Methods and Selection Rules (GOMS) for Gesture Interfaces. Proceedings of the 13th Central & Eastern European Software Engineering Conference in Russia, (8), pp. 1 – 9. Available at: https://dl.acm.org/doi/10.1145/3166094.3166102 (Ac-cessed: 29.10.2022).
18. Jokinen J., Oulasvirta A., Howes A. (2022). Cognitive Modelling: From GOMS to Deep Reinforcement Learning. CHI Conference on Human Factors in Computing Systems Extended Abstracts, 121, pp. 1 – 3. Available at: https://dl.acm.org/doi/10.1145/ 3491101.3503771 (Accessed: 29.10.2022).
19. Mishra W., Chowdhury A., Dhar D. (2017). Optimizing Operation Research Strategy for Design Intervention: A Framework for GOMS Selection Rule. International Conference on Research into Design, 65, pp. 61 – 70. Available at: https://link.springer.com/chapter/10.1007/978-981-10-3518-0_6 (Accessed: 29.10.2022).
20. Beckert B., Beuster G. (2006). A Method for Formalizing, Analyzing, and Verifying Secure User Interfaces. International Conference on Formal Engineering Methods, 4260, pp. 55 – 73. Available at: https://page-one.springer.com/pdf/preview/10.1007/ 11901433_4 (Accessed: 29.10.2022).
21. Nyström A. (2018). Gesture-Level Model: A modified Keystroke-Level Model for Tasks on Mobile Touchscreen Devices. Computer Science, (1), pp. 1 – 44. Available at: http://uu.diva-portal.org/smash/get/diva2:1235821/FULLTEXT01.pdf (Accessed: 29.10.2022).
22. Demchak B., Otasek D., Pico A., Bader D.et al. (2018). The Cytoscape Automation app article collection. Computer Science F1000 Research, (1), pp. 1 – 6. Available at: https://pdfs.semanticscholar.org/272f/ 482e15a7ec4eefd3576fe878e018422e24cd.pdf (Accessed: 29.10.2022).
Статью можно приобрести в электронном виде (PDF формат).
Стоимость статьи 500 руб. (в том числе НДС 20%). После оформления заказа, в течение нескольких дней, на указанный вами e-mail придут счет и квитанция для оплаты в банке.
После поступления денег на счет издательства, вам будет выслан электронный вариант статьи.
Для заказа скопируйте doi статьи:
10.14489/vkit.2022.11.pp.052-065
и заполните форму
Отправляя форму вы даете согласие на обработку персональных данных.
.
This article is available in electronic format (PDF).
The cost of a single article is 500 rubles. (including VAT 20%). After you place an order within a few days, you will receive following documents to your specified e-mail: account on payment and receipt to pay in the bank.
After depositing your payment on our bank account we send you file of the article by e-mail.
To order articles please copy the article doi:
10.14489/vkit.2022.11.pp.052-065
and fill out the form
.
|
Архив номеров
Разработка концепции и создание сайта - ООО «Издательский дом «СПЕКТР»