Announcements

Comp 8920 (60-592-03)   WINTER 2022  Announcements.

PLEASE, CHECK THIS PAGE FOR COURSE INFORMATION AND EVENTS.  Just scroll down to read from recent to old announcements.

Course Web Page can be accessed through:  http://blackboard.uwindsor.ca

Or https://cezeife.myweb.cs.uwindsor.ca/courses/60-592/592index.htm

Important and urgent class announcements are also sent to students through their Uwindsor email accounts. Please, check your Uwindsor email account regularly.

 

Classes: Tue : 2:30 – 5:20pm (Online Through Black Board Collaborate Virtual Class Room)
To attend class, Log on to Black Board http://blackboard.uwindsor.ca. Then, click on Virtual classroom, and join Comp 8920 Class session for the day.

 

Office hours: Mons. 11:00am – 12:00pm, will be held through MSTeams. The following link is for joining the MSTeams group for class during my office hours:
https://teams.microsoft.com/l/channel/19%3anVo6_32DlAAICUPbAfLYrgBrvLYUnyUhd010rzJOP181%40thread.tacv2/General?groupId=02f3af68-8c56-4afa-90cf-10ed43dafdad&tenantId=12f933b3-3d61-4b19-9a4d-689021de8cc9

 

 

Get the course information through the link Course information Volume 1.

Get more course information through the link More course information Volume 2

 

 

Posted Wednesday, January 5, 2022.

 

Get the course information through the link Course information Volume 1.

Get more course information through the link More course information Volume 2

 

RECOMMENDED Materials:

 C.I Ezeife, Course Notes for 60-592, Selected Topics on Web Data Extraction Techniques for Recommendation Systems, University of Windsor, Winter 2022.

Course notes can be downloaded from the notes page of this site.

 

Course Texts:

Reference Materials:

Recommended Text:
1. Recommender Systems: The Textbook, by Aggarwal, Charu C., Springer publishers, ISBN 978-3-319-29657-9.  Available through the bookstore or online order from Springer

Reference Materials:

1.    Jiawei Han, Micheline Kamber and Jian Pei. Data Mining - Concepts and Techniques, published by Morgan Kaufmann/Elsevier, 2011, Third Edition, by (isbn: 978-0-12-381479-1). ****  Most comprehensive and useful to read for mining algorithms.

2.    Ian Witten, Eibe Frank, Mark Hall, and Christopher Pal. Data Mining: Practical Machine Learning Tools and Techniques, 4th Edition by Morgan Kaufamann, isbn: 978-3-540-37881-5     ****    Good for data mining tools like WEKA review. 

3.    Ryan Mitchell, Web Scraping with Python: Collecting Data from the Modern Web.
O’Reilly books, 2017, isbn: 9781491-910290.

4.     Bing Liu, 2008. Web Data Mining - Exploring Hyperlinks, Contents and Usage Data, Springer-Verlag, 2007, isbn 978-3-540-37881-5.  ** Good for Web Mining.

5.     Ezeife, C.I. and Titas Mutsuddy, Towards Comparative Mining of Web Document Objects with NFA: WebOMiner System, International Journal of Data Warehousing and Mining (IJDWM), 8(4), pp. 1-21, October-December 2012.      ****  Our Research and application in data extraction

6.     Ezeife, C.I. and Bindu Peravali, “ Comparative Mining of B2C Web Sites by Discovering Web Database Schemas”, in the proceedings of the 20th ACM International Database Engineering & Applications Symposium (IDEAS16), pp. 183-192 , Montreal, QC, CANADA , 11-13 July, 2016.  *** Our WebOMiner_S data extractor