Text Retrieval and Search Engines

课程
en
英语
24 时
此内容评级为 0/5
来源
  • 来自www.coursera.org
状况
  • 自定进度
  • 免费获取
  • 收费证书
更多信息
  • 6 序列
  • 等级 介绍

Their employees are learning daily with Edflex

  • Safran
  • Air France
  • TotalEnergies
  • Generali
Learn more

课程详情

教学大纲

  • Week 1 - 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.
  • Week 1 - 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.
  • Week 2 - 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 e...
  • Week 3 - 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 precisio...
  • Week 4 - 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 co...
  • Week 5 - Week 5
    In this week's lessons, you will learn feedback techniques in information retrieval, including the Rocchio feedback method for the vector space model, and a mixture model for feedback with language models. You will also learn how web search engines work, inclu...
  • Week 6 - Week 6
    In this week's lessons, you will learn how machine learning can be used to combine multiple scoring factors to optimize ranking of documents in web search (i.e., learning to rank), and learn techniques used in recommender systems (also called filtering systems...

先决条件

没有。

讲师

ChengXiang Zhai
Professor
Department of Computer Science

编辑

伊利诺伊大学香槟分校(UIUC)成立于 1867 年。伊利诺伊大学的主校区位于芝加哥以南 200 公里处的香槟和厄巴纳双城。

根据世界大学排名中心(Center for World University Rankings)等多项排名,这所重点大学跻身全球最负盛名的大学之列,2020-21 年的全球排名为第 22 位。

平台

Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

此内容评级为 4.5/5
(没有评论)
此内容评级为 4.5/5
(没有评论)
完成这个资源,写一篇评论