Web Development Platforms

This course focuses on extracting knowledge from the web by applying Machine Learning techniques to classify and cluster hypertext documents. Basic approaches from Information Retrieval and text analysis are also discussed. The students use recent Machine Learning and Data Mining software to implement practical web document retrieval, classification and clustering applications.

News

Work Groups

Assessment methods and criteria

[PDF]

Lectures

Lecture #00: Web Mining [PDF]

Lecture #01: Information Retrieval and Web Search [PDF]

Lecture #02: Hyperlink Based Ranking [PDF]

Lecture #03: Clustering [PDF]

Lecture #04: Evaluating Clustering [PDF]

Lecture #05: Classification [PDF]

Assessment Labs (100% - 20 Values)

Assessment Lab #01 (30% - 6V): Web Crawler

• Extract and Load (20% - 4V) + Web Interface (10% - 2V)
• Resources
  • Scrapy
  • HultigCrawler
  • SocialNetCrawler
  • OpenWebSpider
  • Full-Text Search - MySQL
  • Full-Text Search - MS SQL
• Deadline: (12/10/2022)

Assessment Lab #02 (30% - 6V): [Web Document Classification]

• Classifier (20% - 4V) + Web Interface (10% - 2V)
• Resources
  • Paper 1
  • Weka] Tutorial
  • PyTorch
  • TensorFlow
  • scikit-learn
• Deadline: (16/11/2022)

Assessment Lab #03 (40% - 8V): [Intelligent Search Engine]

• Deadline: (04/01/2023)

Resources

Web Data Mining [PDF]

Data Mining [PDF]

Mining of Massive Datasets [PDF]