Web Mining
Winter 2022
York University

Semester: Winter 2022
Course/Sect#: ITEC 4305
Lecture Time: Tue 19:00pm-22:00pm
Location: Virtual Zoom Room
Instructor: Jimmy Huang
Office: TEL 3048
Office Hours: By appointment
Phone #: 416-736-2100 x30149
e-mail: jhuang AT yorku DOT ca

Welcome to the Web Mining course, ITEC-4305 for Winter term 2022. Materials, instructions, and notices for the course will accumulate here over the semester.

Message Board

March 16, 2022
Assignment 3 is available (see below).

February 12, 2022
Assignment 2 is available (see below).

January 21, 2022
Assignment 1 is available (see below).

Course Description

The World Wide Web (or the Web for short) is officially defined as a "wide area hypermedia information retrieval initiative aiming to give universal access to a large universe of documents". The rapid growth of the Web in the last decade makes it the largest publicly accessible data source in the world. The Web has many unique characteristics, which make mining useful information and knowledge from the Web a fascinating and challenging task. This course is an advanced course after the courses ITEC4020 "Internet Client-Server Systems" and ITEC3020 "Introduction to Web Technology". It covers some advanced topics and the latest research topics on Web mining.

The major objectives of this course are to introduce Web mining technology from a practical point of view and for the students to obtain a solid grasp of how techniques in Web mining technology can be applied to solve problems in real-world applications.

Web mining aims to discover useful information or knowledge from Web hyperlinks, page contents and usage data. Due to the richness and diversity of information and other Web specific characteristics, Web mining is not just an application of data mining. Web mining has developed many of its own methods, ideas, models and algorithms. This course will cover the following topics:

  • Introduction to WWW and Web Mining Systems
  • Learning and Knowledge Discovery from the Web
  • Information Retrieval (IR) and Web Search
  • Web Crawling and Information Integration
  • Web Link Analysis such as Social Network Analyis, PageRank and HITS
  • Opinion and Sentiments Mining
  • Web Aspect Search and Mining
  • Web Usage Mining
  • Web Mining Applications such as Web Blogs Mining and Online Medical Data Analysis

Required Textbook

Web Data Mining
       Exploring Hyperlinks, Contents and Usage Data
532 pages.
Bing Liu
Springer, 2007
ISBN: 978-3-540-37881-5

Grading Criteria / Course Requirements

Percentage When
Final Exam 30% sometime in April
Assignments 70% 3 assigments, due through the semester



Useful On-line Information

This page is maintained by Jimmy Huang. Last modified on March 16, 2022.