Бакалавриат
2020/2021![Learning Objectives](/f/src/global/i/edu/objectives.svg)
![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Course Contents](/f/src/global/i/edu/sections.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Веб-поиск и ранжирование
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Статус:
Курс обязательный (Прикладная математика и информатика)
Направление:
01.03.02. Прикладная математика и информатика
Кто читает:
Департамент информатики
Когда читается:
4-й курс, 1 модуль
Формат изучения:
с онлайн-курсом
Преподаватели:
Шпильман Алексей Александрович
Язык:
английский
Кредиты:
5
Контактные часы:
60
Course Syllabus
Abstract
Discipline of the basic profile of the professional cycle. Students will receive basic web search algorithms, create their own web crawler, and evaluate the quality of the collected results. This discipline forms the following competencies. As a result of mastering the discipline, the student must: ● know the technology for assessing the quality of the search; ● be able to collect data from web resources; ● Own direct ranking methods and ranking methods using machine learning.
Learning Objectives
- The objectives of mastering the discipline "Web Search and Ranking" are the formation of students' theoretical knowledge and practical skills of web search and data ranking. Students will receive basic web search algorithms, create their own web crawler and evaluate the quality of the collected results.
Expected Learning Outcomes
- Knows: test collections; quality measures; user behavior; A \ B testing; interleaving.
- Has skills in obtaining and preparing data for search; Web crawling text processing: tokenization, normalization. Owns the concepts of: spam; indexing. Owns request processing skills
- Knows: classic ranking approaches. He has skills in applying ranking using semantic methods; machine learning ranking
- Owns the concepts of: federated search; click models.
Course Contents
- Assessment of the quality of information retrieval
- Preparation of data for search, request processing
- Classical approaches to ranking, application of semantic methods and machine learning
- Federated search, click models
Bibliography
Recommended Core Bibliography
- Gossen, T. (2015). Search Engines for Children : Search User Interfaces and Information-Seeking Behaviour. Wiesbaden: Springer Vieweg. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1159664
Recommended Additional Bibliography
- Levene, M. (2010). An Introduction to Search Engines and Web Navigation. Hoboken, N.J.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=335281