课程信息
4.4
392 个评分
85 个审阅
专项课程

第 2 门课程(共 6 门),位于

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为20 小时

建议:6 hours/week...
可选语言

英语(English)

字幕:英语(English)...

您将获得的技能

Information Retrieval (IR)Document RetrievalMachine LearningRecommender Systems
专项课程

第 2 门课程(共 6 门),位于

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
完成时间(小时)

完成时间大约为20 小时

建议:6 hours/week...
可选语言

英语(English)

字幕:英语(English)...

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 2 小时

Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course....
Reading
2 个视频(共 15 分钟), 6 个阅读材料, 2 个测验
Video2 个视频
Course Introduction Video11分钟
Reading6 个阅读材料
Welcome to Text Retrieval and Search Engines!10分钟
Syllabus10分钟
About the Discussion Forums10分钟
Updating your Profile10分钟
Social Media10分钟
Course Errata10分钟
Quiz2 个练习
Orientation Quiz15分钟
Pre-Quiz30分钟
完成时间(小时)
完成时间为 4 小时

Week 1

During this week's lessons, you will learn of natural language processing techniques, which are the foundation for all kinds of text-processing applications, the concept of a retrieval model, and the basic idea of the vector space model. ...
Reading
6 个视频(共 94 分钟), 1 个阅读材料, 2 个测验
Video6 个视频
Lesson 1.2: Text Access9分钟
Lesson 1.3: Text Retrieval Problem26分钟
Lesson 1.4: Overview of Text Retrieval Methods10分钟
Lesson 1.5: Vector Space Model - Basic Idea9分钟
Lesson 1.6: Vector Space Retrieval Model - Simplest Instantiation17分钟
Reading1 个阅读材料
Week 1 Overview10分钟
Quiz2 个练习
Week 1 Practice Quiz分钟
Week 1 Quiz分钟
2
完成时间(小时)
完成时间为 4 小时

Week 2

In this week's lessons, you will learn how the vector space model works in detail, the major heuristics used in designing a retrieval function for ranking documents with respect to a query, and how to implement an information retrieval system (i.e., a search engine), including how to build an inverted index and how to score documents quickly for a query. ...
Reading
6 个视频(共 102 分钟), 1 个阅读材料, 2 个测验
Video6 个视频
Lesson 2.2: TF Transformation9分钟
Lesson 2.3: Doc Length Normalization18分钟
Lesson 2.4: Implementation of TR Systems21分钟
Lesson 2.5: System Implementation - Inverted Index Construction18分钟
Lesson 2.6: System Implementation - Fast Search17分钟
Reading1 个阅读材料
Week 2 Overview10分钟
Quiz2 个练习
Week 2 Practice Quiz分钟
Week 2 Quiz分钟
3
完成时间(小时)
完成时间为 7 小时

Week 3

In this week's lessons, you will learn how to evaluate an information retrieval system (a search engine), including the basic measures for evaluating a set of retrieved results and the major measures for evaluating a ranked list, including the average precision (AP) and the normalized discounted cumulative gain (nDCG), and practical issues in evaluation, including statistical significance testing and pooling....
Reading
6 个视频(共 75 分钟), 2 个阅读材料, 3 个测验
Video6 个视频
Lesson 3.2: Evaluation of TR Systems - Basic Measures12分钟
Lesson 3.3: Evaluation of TR Systems - Evaluating Ranked Lists - Part 115分钟
Lesson 3.4: Evaluation of TR Systems - Evaluating Ranked Lists - Part 210分钟
Lesson 3.5: Evaluation of TR Systems - Multi-Level Judgements10分钟
Lesson 3.6: Evaluation of TR Systems - Practical Issues15分钟
Reading2 个阅读材料
Week 3 Overview10分钟
Programming Assignments Overview10分钟
Quiz2 个练习
Week 3 Practice Quiz分钟
Week 3 Quiz分钟
4
完成时间(小时)
完成时间为 4 小时

Week 4

In this week's lessons, you will learn probabilistic retrieval models and statistical language models, particularly the detail of the query likelihood retrieval function with two specific smoothing methods, and how the query likelihood retrieval function is connected with the retrieval heuristics used in the vector space model. ...
Reading
7 个视频(共 88 分钟), 1 个阅读材料, 2 个测验
Video7 个视频
Lesson 4.2: Statistical Language Model17分钟
Lesson 4.3: Query Likelihood Retrieval Function12分钟
Lesson 4.4: Statistical Language Model - Part 112分钟
Lesson 4.5: Statistical Language Model - Part 29分钟
Lesson 4.6: Smoothing Methods - Part 19分钟
Lesson 4.7: Smoothing Methods - Part 213分钟
Reading1 个阅读材料
Week 4 Overview10分钟
Quiz2 个练习
Week 4 Practice Quiz分钟
Week 4 Quiz分钟
4.4
85 个审阅Chevron Right
工作福利

83%

通过此课程获得实实在在的工作福利
职业晋升

33%

加薪或升职

热门审阅

创建者 JHSep 21st 2016

Great course for those trying to understand how ro analyse and process text data. It has the right amount of tools to help you understand the basics of information retrieval and search engines.

创建者 PMAug 29th 2016

A great overview of text retrieval methods. Good coverage of search engines. A longer course will cover search engine better (remember this is a 6 weeker)

讲师

Avatar

ChengXiang Zhai

Professor
Department of Computer Science
Graduation Cap

Start working towards your Master's degree

This 课程 is part of the 100% online Master of Computer Science in Data Science from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

关于 University of Illinois at Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs. ...

关于 Data Mining 专项课程

The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization....
Data Mining

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