Web Mining

Course Information
TitleΕξόρυξη Γνώσης απο Δεδομένα Ιστού / Web Mining
CodeDWS201
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
CoordinatorAthina Vakali
CommonYes
StatusActive
Course ID600016260

Programme of Study: PMS EPISTĪMĪ DEDOMENŌN KAI PAGKOSMIOU ISTOU (2018 éōs sīmera) PF

Registered students: 16
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization217.5

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600132035
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
General Prerequisites
Principles and technologies for Databases, Basic principles of Web technologies
Learning Outcomes
1. Identify data structures and models World Wide Web 2. Construct and analyze Web data models and understand data relevance metrics i 3. Learning important Web properties, attributes and algorithms to find and recognize common patterns, behaviors, and Web clusters
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Generate new research ideas
  • Appreciate diversity and multiculturality
  • Demonstrate social, professional and ethical commitment and sensitivity to gender issues
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
• Introduction to the basic concepts of information and data management within World Wide Web. • Data types on the web and representation. • World Wide Web Structure and Graph Model. • World Wide Web Performance Metrics and Information Sharing Techniques. • Information aggregation techniques in Social Networks. • Sentiment analysis and behavioral analytics on the Web. • Recommendations in Social Media and New Collaborative Web Environments.
Keywords
Web mining, Web data models, data mining, data analytics algorithms
Educational Material Types
  • Notes
  • Slide presentations
  • Multimedia
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
Description
Use of online courses platform. Email communication and course announcements forwarding to students. Upload all course material (slides, projects, extra material).
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39
Laboratory Work69
Reading Assigment39
Project54
Written assigments18
Exams6
Total225
Student Assessment
Description
2 compuslory projects (one of introductory implementation and one involving extended implementation)weighting 50% (assuming the final examination mark is at least 4.5/10). Written exams weighting 50%
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Extended Answer Questions (Summative)
  • Written Assignment (Formative)
  • Oral Exams (Summative)
  • Performance / Staging (Summative)
  • Report (Summative)
  • Labortatory Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
● B. Liu: Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications), Springer, 2011. ● R. Zafarani et al : Social Media Mining, Cambridge University Press, 2015 ● Isoni, Andrea. Machine Learning for the Web. Packt Publishing Ltd, 2016. ● Easley, David, and Jon Kleinberg. Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press, 2010. ● Α. Βακάλη, Ζ. Παπαμήτσιου: Πληροφοριακά Συστήματα Παγκόσμιου Ιστού, Εκδόσεις Νέες Τεχνολογίες, 2012. ● A. Vakali and G. Pallis: Web Data Management Practices, Idea Group Publishing, 2007. ● Published papers in scientific journals and conferences.
Additional bibliography for study
● A. Vakali and G. Pallis: Web Data Management Practices, Idea Group Publishing, 2007. ● Published papers in scientific journals and conferences.
Last Update
30-05-2019