4

The rapid growth of online information and the increasing reliance onsearch engines have highlighted the need for effective methods to measure and maximize the value of search engine processes. This research focuses on the development of information models that facilitate the calculation of maximum value in search engine algorithms. The study begins by examining the current landscape of search engines and the challenges associated with maximizing value. It identifies key factors such as user satisfaction, information accessibility, trust, business success, user engagement, and innovation as crucial elements in defining value within search engine processes.To address these challenges, the research proposes the development of comprehensive information models that integrate various metrics and parameters to assess the value of search engine algorithms

  • O'qishlar soni 4
  • Nashr sanasi 01-08-2024
  • Asosiy tilIngliz
  • Sahifalar1114-1116
English

The rapid growth of online information and the increasing reliance onsearch engines have highlighted the need for effective methods to measure and maximize the value of search engine processes. This research focuses on the development of information models that facilitate the calculation of maximum value in search engine algorithms. The study begins by examining the current landscape of search engines and the challenges associated with maximizing value. It identifies key factors such as user satisfaction, information accessibility, trust, business success, user engagement, and innovation as crucial elements in defining value within search engine processes.To address these challenges, the research proposes the development of comprehensive information models that integrate various metrics and parameters to assess the value of search engine algorithms

№ Muallifning F.I.Sh. Lavozimi Tashkilot nomi
1 Saidova F.M. teacher University of Tashkent for Applied Sciences,
№ Havola nomi
1 [1]Паук -Описание системы. RASER Company. 1995.[2]Kahle, B., and Medlar, A., "An Information System for Corporate Users: Wide Area Information Servers," Technical Report TMC-199, Thinking Machines, Inc., April 1991.[3]Budi Yuwono, Dik L.Lee. Search and Ranking Algorithms for Locating Resources on the World Wide Web. In Proceedings of the Forth International Conference on the World Wide Web, New York, November, 1995.[4]Koster, M., "ALIWEB: Archie-like Indexing in the Web,"Computer Networks and ISDN Systems, 27(2), pp. 175-182, 1994.[5]Martin Bartschi. An Overview of Information Retrieval Subjects. IEEE Computer, # 5, 1985, p. 67-84[6]Дж. Солтон. Динамические библиотечно-информационные системы. Мир, Москва, 1979.[7]Попов И.И. Оценка и оптимизация информационных систем. -М: МИФИ,. 1981.[8]Решетников В.Н. Алгебраическая теория информационного поиска. Программирование, # 3, 1979, стр. 68-73.[9]Yu C.T., Salton G. Effective Information Retrieval Using Term Accuracy. Communication ACM, V.20, # 3, p. 135-142.[10]T.Norault, M. McGill, and M.B. Koll. "A performance Evaluation of Similarity Measures, Document Term Weighing Schemes and Representations in Boolean Environment, Information Retrieval Search," R.N. Oddy et al., eds., Butterworth, London, 1981, p. 57-76.[11]Yu C.T., Lam K., Salton G. "Term Weighting in Information Retrieval Using the Term Precession Model. Communication ACM, V.29, 1982, p. 152-170.[12]И.И. Попов, П.Б. Храмцов. Распределение частоты встречаемости терминов для линейной модели информационного потока. НТИ, Сер.2, # 2, стр. 23-26, 1991.[13]С.А. Айвазян, И.С. Енюков, Л.Д. Мешалкин. Прикладная статистика. Исследование Зависимостей. Москва, ФиС 1985.[14]Васильев Ф. П. Методы оптимизации. —М.: Факториал Пресс, 2002. —824 с.[15]Груздева Т. В., Стрекаловский А. С. Локальный поиск в задачах с невыпуклыми ограничениями // Журн. вычисл. математики и мат. физики. —2007. —Т. 47, No 3. —C. 397–413., Стрекаловский А. С. 16.Элементы невыпуклой оптимизации. —Новосибирск: Наука, 2003. —352 с.[16]Николаев А. И. Эффективный подход на основе машинного обучения для решения задачи о максимальной клике // Информационные технологии, Т. 22, No 4, 2016, С. 249-254. San Segundo P., [17]Nikolaev A., Batsyn M., Pardalos P.M. Improved Infra-Chromatic Bound for Exact Maximum Clique Search // Informatica. 2016. Vol. 27. No. 2. P. 463-487, San Segundo P., Lopez A., Batsyn M. V., Nikolaev A. I., Pardalos [18]P. M. Improved initial vertex ordering for exact maximum clique search // Applied Intelligence. 2016. Vol. 45. No. 3. P. 868-880.
Kutilmoqda