Course information Comp 8920 (60-592) 2022, Vol 1

 

Hello Class,

   Welcome to my Comp 8920 (60-592) class this Winter 2022,  and you can download course notes and get information

regarding the course from the course web site found through UWindsor

blackboard site www.blackboard.uwindsor.ca or directly through:

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

Ensure you have all materials so far handed out (or to be handed out) in class (also posted on the web site) which are:

1. course outline,

2. course information sheet found through the announcement link at(https://cezeife.myweb.cs.uwindsor.ca/courses/60-592/announce/crseinfo_v1.htm),

3. seminar topic list to choose from (also available through seminar link)at https://cezeife.myweb.cs.uwindsor.ca/courses/60-592/seminar/semindex.htm,

4. seminar presentation schedule (posted or to be posted on the web page through the seminar link) at https://cezeife.myweb.cs.uwindsor.ca/courses/60-592/seminar/semindex.htm,

5. More Course Information sheet (on test, seminar and project), (to be given later through the announcement page)at https://cezeife.myweb.cs.uwindsor.ca/courses/60-592/announce/crseinfo_v2.htm.

6. Practice Midterm Test (only when it is ready and to be kept in Test folder in Blackboard),

7. project presentation schedule (yet to be handed out and to be found through the project link on course web site)

 

 

Read the course information below carefully and the seminar topic

list from additional topics from the Web data extraction book with Python, and

recommendation systems books or from the recent ACM related conference

ACM Conference on Recommender Systems (RecSys 2021), which are in the file handed out in

class and found through the Comp 8920 (60-592) course web link (seminar topics):   They take time to compile.

 

Here is a summary of course expectations as presented in the

course outline and discussed in class.

 

****

A. On Test

  As announced in class, date for midterm test is Tuesday, Mar. 15, 2022,

2:30 pm ONLINE in class through Blackboard. A copy of sample midterm exam will be handed

Out in class or in BB only for practice and as a model.

 

****

B.  On Seminar presentations

I have posted a text file that has all the seminar topics I would

like each student to pick one of.  Remember

that each student is responsible for providing copies of the

paper that they will deliver to the class (students who

will participate in grading that student's seminar - student grading

of the seminar will be worth 25% or 0% while my grading makes up 75% or

100%). Regardless, students' grading of other students' seminars as part

of course work is important for their seminar contribution marks even if

it is only my seminar grading that counts for each student seminar.

 

For seminar, students are expected to have chosen their seminar topic

by Feb. 15, 2022.

No one seminar topic is to be picked by more than one student. That is,

every topic is to be picked and presented once. Thus, if you pick a

topic already picked by someone, you have to choose another from the

remaining topics. Email your topic to me (cezeife@uwindsor.ca) or discuss

during class or office hour.

 

All students will grade other students' seminar presentations. 

I will provide a tentative list below. Since reading

the seminar papers in your seminar group is part of course work, I

expect every student to also provide a summary of at least one seminar

they graded in addition to the seminar they presented.

 

Note that it is every student's responsibility to make copies of

their seminar available to all students who will be grading him/her.

Copies of seminar papers should be provided to student graders not

later than Feb. 27, 2022.

 

Seminars begin, Tuesday, March 22, 2022 as announced earlier (and in course outline).

Thus, the seminar report should be a 5 page report (double line

spaced with 12 point font) on only one seminar paper that you

presented.

 

Seminar report should clearly state title of paper, authors, proceeding

or journal it came from, year of publication, name of student and

seminar group. Then, include clearly, problem addressed by paper,

contributions of this paper, solution provided with clear algorithms and

running example, limitations and advantages of solution and your opinion of work.  Seminar reports are due on the day of presentation or the day the second paper you summarize is presented.

 

****

C. On Project Topics,

 

Students should have chosen project topics by Feb. 15, 2022. Projects can be worked on individually or in group.  If it is a group project, each

group member's contribution has to be clearly indicated. Projects

can be research or application based.  You can select your own

project topic on issues related to course material and present it for

approval.  However, here are some project topic suggestions.

 

Research-Based

 

 

A Survey of Collaborative Mining Approaches

Web Content Mining and automatic wrapper generation

A survey of Web Recommendation Systems

New Research Problems in Web data extraction

Web Data extraction using Python

Any other, propose for approval

 

****

Application-Based

This includes implementing existing web recommendation or data extraction

algorithms that we can use later as well as learning a web recommendation

or extraction tool and implementing/demonstrating some process with the tool.

 

1. Implementation of Web recommendation and extraction algorithms or languages. I am

  interested in a complete teaching of the Python language as a web data extraction

  language and someone can take on that as a project. That is, “Use of Python Language”.

 

Students can explore any of these systems in detail and develop applications based on their methodologies for project.

1. GroupLens Recommender System for Usenet News which collected ratings from Usenet readers and predicted whether other readers readers would like an article before they read it.

Extensions to other products are BookLens, MovieLens.  Thus.

2. BookLens Recommender System.

3. MovieLens Recommender System.

4. Amazon.com Recommender system.

5. Netflix movie recommender system.

6. Google news personalization systems.

7. Facebook friend recommendation system

8. From the course book on Recommendation system, students’ projects can also be taken as any of these readings.

Other topics on recommender system models are left as assigned reading and they include the following:

i. Content-based Recommender Systems

– ii. Knowledge-based Recommender Systems

On Web Data Extraction,

Students can also explore these other topics from the book with Python

9. Dealing with children and other descendants.

10. Dealing with siblings.

11. Dealing with parents.

12. Other topics as use of regular expression, crawling to other pages, using APIs, storing data and reading documents can be assigned as extra reading and presentation topics.

 

As announced in class, work on projects should proceed gradually

starting now as project reports and complete implementation results

are due on the last day of classes.  Project presentations will

occur during the last 2 classes. You are encouraged to show me

the outline of how you wish to proceed with your project once you

have it ready.

 

Tentative Seminar Grading Groups and Papers so far Picked:

 

All students grade other students

Students in seminar grading group A will grade seminars for students in seminar grading group B and vice versa. Ensure that you have given every student grading your seminar a copy of your seminar paper by Tues, Feb. 15, 2022.

Seminar Class (for Tuesday, 2:30pm – 5:20pm in ONLINE BLACKBOARD)

(GRADING GROUP A)                         SEMINAR PAPER NUMBER

Deepanshu

Ahmed,Tauseef

Awari,Parth Pandurang

Ayomide,Oduba Elijah

Bandreddy,Saadhika

Bangalore Vijayadas,Nethra

Sabbella,Krishna Kalyan

Shaikh,Noor Ali

Sharma,Varnita

 

 

Seminar Class (for Tuesday, 2:30pm – 5:20pm in ONLINE BLACKBOARD)

(GRADING GROUP B)                         SEMINAR PAPER NUMBER

Gupta,Rohit

Jamal,Asim

John,Daniel

Kantamaneni,Raja Venkata

Mehna,Avleen Kaur

Muhib,Raghib Barkat

Bharucha,Vrushit Nileshkumar

Bhathal,Ramandeep Singh

Chavda,Yash Ashwinbhai


Note: seminars are graded based on clarity(2), organization(2), quality (3), technical content(3). Ensure that your paper is not less than 9 pages or you may need to present two such short papers.

 

I have used the updated SIS class list of today to form my

mailing list and if you know any student still in the class

but not yet registered, please forward this to them and let

them register soon as they will not be receiving class emails.

 

It is your responsibility to provide copies of your own paper to other

student graders of your research seminar. But provide copies only after

your picked topic has been confirmed.

 

Everyone needs to give me a hard copy of their seminar paper.

 

***************************

Dr. Christie Ezeife

Professor

School of Computer Science

University of Windsor

Ont N9B 3P4.

 

Phone: (519) 253-3000 ext. 3012

email: cezeife@uwindsor.ca