| Project | May Lead to
MSc | Taken by | Brief Description |
|---|
| Conference Ranking |
Yes |
|
Conferences are currently ranked subjectively by
reputation. The project consists of devising a metric to rank
conferences based on their paper citation, the reputation of the
authors publishing in them, etc. This information could be extracted
from scholar.google or citeseer in addition to the public database dblp. |
| Plan Protein Localization |
Yes |
|
This project consist of using an associative classifier to
build a model to identify whether a protein is intra or extra cellular
and compare the accuracy of the classifier with results obtained with
SVM and Adaboot. In addition to features such as protein composition
and frequent subsequences, the location of frequent subsequences
should also be considered in the model then the accuracy again compared. |
| Assymetric Parallel Frequent Itemset Mining |
Yes |
Scott B. |
Typically, a parallel data mining program runs the same
program on all processors. This project consists of identifying
transactional data features that wouyld identify the most appropriate
algorithm to run on each processor given its data partition. |
| Emmerging Sequences |
Yes |
Pouria P. |
Comparing sets of sequences is relevant to many
applications. This project consists of implementing algorithms to
identify contrasting sequences among sets of sequences. |
| Mammography Classification |
Yes |
|
An associative classifier should be used to classify
mammograms into cancerous and normal cases. An interface is to be
built receiving mammograms and simulating the diagnostic is to be built. |
| Feature Space Conversion for SVM |
Possible |
|
The associative classifier can be used to transform the
feature space of a training set. Would this transformation help SVM in
its prediction? The project is to test this hypothesis. |
| Question-Answer recommender System |
Yes |
|
In the context of a search engine, one could send a question
instead of keywords. The idea is to expend the question, retrieve
pretinent documents using search engines, then summarise these
resources and provide the concise summaries as recommeded answers to
the original question. |
| Spatial Outlier Detection with Constraints |
Yes |
Jeff B. & John M. |
DBCluC is a variation of DBSCAN to cluster date while
considering constratins. Can we do a similar update in the definitions
used in LOF for outlier detection to discover spatial outliers given
physical constraints? |
| Classification Explanation Generation for Associative Classifiers |
Possible |
|
When a classifier predicts a class for a new object a straight
forward question is "how was the conclusion drawn?" The project is to
built an UI that would explain the results of an associative classifier. |
| Interface for Constraint based Frequent Itemset Mining |
Possible |
Ananth V. |
The project is to build a user interface allowing the
expression of constraints to be pushed in frequent itemset mining. |