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Text Retrieval and Search Engines · LearnSpace
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Text Retrieval and Search Engines

Курс от University of Illinois Urbana-Champaign
Уровень не указан≈ 30.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text. This course will cover search engine technologies, which play an important role in any data mining applications involving text data for two reasons. First, while the raw data may be large for any particular problem, it is often a relatively small subset of the data that are relevant, and a search engine is an essential tool for quickly discovering a small subset of relevant text data in a large text collection. Second, search engines are needed to help analysts interpret any patterns discovered in the data by allowing them to examine the relevant original text data to make sense of any discovered pattern. You will learn the basic concepts, principles, and the major techniques in text retrieval, which is the underlying science of search engines.

Навыки, которые вы освоите

Natural Language ProcessingText MiningProbability & StatisticsApplied Machine LearningStatistical MethodsStatistical ModelingModel OptimizationData MiningData EngineeringModel EvaluationMachine LearningWeb Analytics and SEONetwork AnalysisWeb ScrapingAI PersonalizationUnstructured DataMachine Learning AlgorithmsBig Data

Программа курса

7 модулей · 76 учебных материалов

01Orientation11 материалов

About the Course

Welcome to Text Retrieval and Search Engines!ЧтениеSyllabusЧтениеAbout the Discussion ForumsЧтениеUpdating your ProfileЧтение

Учитесь у экспертов

ChengXiang Zhai

Professor

Text Retrieval and Search Engines
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 30.8 ч

7 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
Social MediaЧтение
Course ErrataЧтение

Orientation Activities

Course Welcome VideoВидеоCourse Introduction VideoВидеоOrientation QuizЗаданиеPre-QuizЗаданиеWelcome! Please tell us about yourself.PLUGIN
02Week 19 материалов

Week 1 Information

Week 1 OverviewЧтение

Week 1 Lessons

Lesson 1.1: Natural Language Content AnalysisВидеоLesson 1.2: Text AccessВидеоLesson 1.3: Text Retrieval ProblemВидеоLesson 1.4: Overview of Text Retrieval MethodsВидеоLesson 1.5: Vector Space Model - Basic IdeaВидеоLesson 1.6: Vector Space Retrieval Model - Simplest InstantiationВидео

Week 1 Activities

Week 1 Practice QuizЗаданиеWeek 1 QuizЗадание
03Week 29 материалов

Week 2 Information

Week 2 OverviewЧтение

Week 2 Lessons

Lesson 2.1: Vector Space Model - Improved InstantiationВидеоLesson 2.2: TF TransformationВидеоLesson 2.3: Doc Length NormalizationВидеоLesson 2.4: Implementation of TR SystemsВидеоLesson 2.5: System Implementation - Inverted Index ConstructionВидеоLesson 2.6: System Implementation - Fast SearchВидео

Week 2 Activities

Week 2 Practice QuizЗаданиеWeek 2 QuizЗадание
04Week 311 материалов

Week 3 Information

Week 3 OverviewЧтение

Week 3 Lessons

Lesson 3.1: Evaluation of TR SystemsВидеоLesson 3.2: Evaluation of TR Systems - Basic MeasuresВидеоLesson 3.3: Evaluation of TR Systems - Evaluating Ranked Lists - Part 1ВидеоLesson 3.4: Evaluation of TR Systems - Evaluating Ranked Lists - Part 2ВидеоLesson 3.5: Evaluation of TR Systems - Multi-Level JudgementsВидеоLesson 3.6: Evaluation of TR Systems - Practical IssuesВидео

Week 3 Activities

Week 3 Practice QuizЗаданиеWeek 3 QuizЗадание

Honors Track Programming Assignment

Programming Assignments OverviewЧтениеProgramming Assignment 1Программирование
05Week 410 материалов

Week 4 Information

Week 4 OverviewЧтение

Week 4 Lessons

Lesson 4.1: Probabilistic Retrieval Model - Basic IdeaВидеоLesson 4.2: Statistical Language ModelВидеоLesson 4.3: Query Likelihood Retrieval FunctionВидеоLesson 4.4: Statistical Language Model - Part 1ВидеоLesson 4.5: Statistical Language Model - Part 2ВидеоLesson 4.6: Smoothing Methods - Part 1ВидеоLesson 4.7: Smoothing Methods - Part 2Видео

Week 4 Activities

Week 4 Practice QuizЗаданиеWeek 4 QuizЗадание
06Week 511 материалов

Week 5 Information

Week 5 OverviewЧтение

Week 5 Lessons

Lesson 5.1: Feedback in Text RetrievalВидеоLesson 5.2: Feedback in Vector Space Model - RocchioВидеоLesson 5.3: Feedback in Text Retrieval - Feedback in LMВидеоLesson 5.4: Web Search: Introduction & Web CrawlerВидеоLesson 5.5: Web IndexingВидеоLesson 5.6: Link Analysis - Part 1ВидеоLesson 5.7: Link Analysis - Part 2ВидеоLesson 5.8: Link Analysis - Part 3Видео

Week 5 Activities

Week 5 Practice QuizЗаданиеWeek 5 QuizЗадание
07Week 615 материалов

Week 6 Information

Week 6 OverviewЧтение

Week 6 Lessons

Lesson 6.1: Learning to Rank - Part 1ВидеоLesson 6.2: Learning to Rank - Part 2ВидеоLesson 6.3: Learning to Rank - Part 3ВидеоLesson 6.4: Future of Web SearchВидеоLesson 6.5: Recommender Systems: Content-Based Filtering - Part 1ВидеоLesson 6.6: Recommender Systems: Content-Based Filtering - Part 2ВидеоLesson 6.7: Recommender Systems: Collaborative Filtering - Part 1ВидеоLesson 6.8: Recommender Systems: Collaborative Filtering - Part 2ВидеоLesson 6.9: Recommender Systems: Collaborative Filtering - Part 3ВидеоLesson 6.10: Course SummaryВидео

Week 6 Activities

Week 6 Practice QuizЗаданиеWeek 6 QuizЗаданиеHow was the course?PLUGIN

Honors Track Programming Assignment

Programming Assignment 2Программирование