(Mirror of my homepage on Concordia U)
Department of Computer Science
Email: bs_surya [AT] cs [dot] concordia [dot] ca
· I successfully defended my Master’s thesis "A New Class of Techniques for Web Personalization" on March 9, 2006.
Currently at SAP Labs,
· New Contact: bhushan [DOT] suryavanshi [AT] sap [DOT] com
Master of Science – Computer Science Jan 2004 - Mar 2006
· THESIS: A New Class of Techniques for Web Personalization.
Bachelor of Engineering – Computer Engineering Jun 1999 - Jun 2003
Jijabai Technological Institute (V.J.T.I.),
If we knew what it was we were doing, it would not be called research, would it?
- Albert Einstein.
v Data Warehousing
v Data Mining
v Web Personalization & Web Mining
v Fuzzy Sets, Fuzzy Logic & Fuzzy Clustering
· Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur, "Adaptive Web Usage Profiling", Book chapter in Advances in Web Mining and Web Usage Analysis, Lecture Notes in Artificial Intelligence, O. Nasraoui et al. (Eds.), Springer, Sept. 2006.
· Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur, "Analysis of Fuzzy Clustering Techniques Used for Web Personalization", In Proc. of NAFIPS 2006, Montréal, Canada, June 3-6, 2006, IEEE press.
· Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur, "Improving the Effectiveness of Model Based Recommender Systems for Highly Sparse and Noisy Web Usage Data", In Proc. of 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05), Compičgne, France, September 19-22, 2005, IEEE press.
· Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur, "Incremental Relational Fuzzy Subtractive Clustering for Dynamic Web Usage Profiling", In Proc. of WebKDD '05 - Taming Evolving, Expanding and Multi-faceted Web Clickstreams, in conjunction with the ACM-SIGKDD,Chicago, Illinois, August 2005, ACM press.
· Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur, "A Fuzzy Hybrid Collaborative Filtering Technique for Web Personalization", In Proc. of the Third Workshop on Intelligent Techniques for Web Personalization (ITWP 05), Held at IJCAI, Edinburgh, Scotland, August 2005.
· Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur, "An Efficient Technique for Mining Usage Profiles using Relational Fuzzy Subtractive Clustering", In Proc. Int'l Workshop on Challenges in Web Information Retrieval and Integration (WIRI 05), Held at ICDE, Tokyo, Japan, April 8-9, 2005, IEEE press.
· "A New Class of Techniques for Web Personalization", Dept. of Computer Science and Software Engineering, Concordia University, March 2006.
v Comp 442/6421: Compiler Design ( Prof. J. Opatrny)
This is a project oriented course. The project includes design and implementation of a compiler (all phases) for a pseudo programming language called SLANG. SLANG basically is a combination of Pascal and C syntax. Assembly Code for the Moon Machine is required to be generated. The student has a choice of choosing his/her host language (implementation language). I implemented it in C as C is a widely used language for Systems Programming.
To download sample SLANG programs click here. I have also included the exe of my compiler, compilation instructions (file README.txt) and the documentation of the project.
v Comp 451/6511: Database Design ( Prof. Khaled Jababo)
The main focus of this course is storage management and indexing, query processing and optimization and transaction processing. This course has a project to be implemented in ObjectStore DBMS. The front end of the main project is to be implemented in Tcl/Tk. The project and main exam are completely disparate. This course requires a good understanding of pointers and C++.
For useful tutorials on ObjectStore and Tcl/Tk click here.
v Comp 6591: Introduction to Knowledge-Base Systems (Prof. N. Shiri)
The main focus of this course is Fundamentals of logic programming, FOL, Foundation of deductive databases and Datalog. This course has a project which forms large chunk of the course. It is a good course to be taken after Comp 6511.
v ENCS 6191: Fuzzy Sets and Fuzzy Logic (Prof. K. Demirli)
This course is a good introduction to fuzzy sets and fuzzy logic concepts. It also deals with fuzzy system modeling in depth. Also covers Fuzzy Clustering. It has a final project to be submitted based on fuzzy logic.
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Data Warehouse, Data mining & OLAP