课程已归档

Inside the Belly of a Search Engine

提供者 Dr. Anne Kayem
Inside the Belly of a Search Engine

They have made encyclopedias obsolete: Web search engines like Google or Bing provide us with the information we are looking for at lightning speed. Surveys have shown that every Internet user searches via Google 3 to 4 times a day on average. In total, estimates assume more than 2 trillion search queries* per year, and the trend is rising.

If you want to understand how these search engines work, this course is for you.

自三月 20, 2023起开始自学
语言: English
Beginner, Fundamentals

课程信息

Are you curious about how web search engines provide you with information daily? Are you surprised at the speed at which web search engines are able to respond to your complex and sometimes incomplete queries? Are you wondering how to build your website so that it can be easily found by others through the search engine (search engine optimization)?

This two-week workshop aims to provide an introduction to how search engines operate in terms of how web pages are discovered, indexed, and retrieved to display information in a structured form to respond to queries (words used to search for information). We discuss how documents are clustered based on similarity and ranked based on query relevance to generate responses to user queries. As a concluding highlight, we consider various forms of visualizing search engine results and why search engines like Google remain popular.

*source: Wikipedia

你将学到什么

  • understand how search engines structure queries
  • understand how search engines discover and index web pages
  • To make the best use of search engines
  • Structure web pages so that they can be found easily

本课程适用于谁

  • people who use search engines, and who are concerned about privacy issues or tracking
  • Students who conduct research on the Internet using search engines as part of their studies
  • Auditors who use search engines to obtain information about companies
  • General public

课程内容

  • Intro

  • Week 1:

    In this week we cover introductory material into the general field of web-based search engines, specifically ones that are index based. We study the basic architecture of search engines, in terms of its components and how they work together to respond to user queries. As a side effect, we discuss the implications for search engine optimisation and the reasons why highly linked web pages are generally more discoverable by search engines.
  • Week 2:

    We build on the learnings in Week 1, to proceed to cover material on the information gathering procedure that search engines employ to analyse documents on the web to determine relevance to queries. Data preparation and analysis are also studied as a means of understanding how search engines match document content to queries based on a relevance model guided primarily by keyword occurrences. As an example, we delve into the mechanisms used to evaluate or compute document relevance, discover documents and rank documents in terms of relative importance with respect to search engine queries. We conclude with some further considerations to take into account with respect to how search engines operate not just in terms of textual data, but also multimedia data such as images, and videos.
  • Final Exam:

    Final Exam
  • I like, I wish:

    Please provide your feedback on the course.

订阅本课程

该课程是免费的。 只需在openHPI上注册一个帐户并参加课程!
现在注册吧

Learners

Current
Today
3,422
Course End
3月 20 2023
3,005
Course Start
2月 22 2023
1,530

评分

本课程已由4位用户进行了五分制评分,平均得分为4.25

证书要求

  • 课程证书 授予者需要至少取得课程总分的百分之 50%
  • 参与证明 授予者需要至少学习了所有课程资料的百分之 50%
  • 完成课程可获得开放徽章

欲知详情,请访问证书指南.

该课程提供者

Dr. Anne Kayem

Dr. Anne Kayem is a senior researcher at the Hasso-Plattner-Institute (Digital Engineering Faculty, University of Potsdam, Germany). She leads the Data Privacy team embedded within the Internet Technologies and Systems Chair. Her research interests range from designing and analysing secure and privacy preserving data sharing algorithms, to evaluating their usability. She is a senior member of the ACM and IEEE. For more details about her research, please visit: https://hpi.de/sprite/home.html