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AmosStorkey - 06 Feb 2009
Please could you enter your selections on this page of the wiki. If you have not formed a group then please indicate three papers and datasets you would be willing to work on to allow pairing.
Mini Project Group Selection
Paper Presentation Allocated
1st choice: Web document clustering: A feasibility demonstration - Philipp Petrenz, Srikanth Sundaram, Avinash Ranganath
2nd choice: Text Classification from Labeled and Unlabeled Documents using EM (1999) - Philipp Petrenz, Srikanth Sundaram, Avinash Ranganath
Pavel Petchko
- 1st: Collaborative Ensemble Learning
- 2nd: Empirical Analysis of Predictive Algorithms for Collaborative Filtering
- 3rd: Personalization of Supermarket Product Recommendations
Cen Zhe Qiao & Zhen Wei He
1st: mining the network value of customer
2nd: learning & making decisions when costs and probability are both unknown
3rd: mining a stream of transactions for customer patterns
Xudong He & Ailun Yi:
- 1st: Hierarchical Classification of Web Content
- 2nd: Conditional random fields: Probabilistic models for segmenting and labeling sequence data
- 3rd: Web Document Clustering: A Feasibility Demonstration (1998)
Nicolas Greffard & Stephane Clery : Using Bayesian networks to analyze expression data (2000)
Matching Words and Pictures - Dan Harvey & Sean Moran
Object Recognition with Informative Features and Linear Classification - Aciel Eshky & Marco Brigham
Papanikolaou Amalia (s0899733)-Makrymallis Antonios(s0897366)
1st choice: Discovery of Climate Indices using Clustering
2nd choice: Mining and Summarizing Customer Reviews
3d choice: Learning and Making Decisions When Costs and Probabilities are Both Unknown
Dimitrios Milios, Anastasios Polymeros:
1st choice: Optimizing Search Engines Using Clickthrough Data
2nd choice: ROCK:ARobust Clustering Algorithm for Categorical Attributes (1999)
3rd choice: Probabilistic latent semantic analysis (1999)
Kostantina Palla & Alfredo Kalaitzis
-1st choice: Robust Real-Time Face Detection
-2nd choice: Object Recognition with Informative Features and Linear Classification
-3rd choice: Blobworld: Image segmentation using Expectation-Maximization and its application to image querying
Andreas Damianou, Ioannis Pavlopoulos
- 1st choice: Probabilistic Latent Semantic Indexing (1999)
- 2nd choice: Latent Dirichlet allocation
- 3rd choice: Web Document Clustering: A Feasibility Demonstration (1998)
Giulio Meneghin, Javier Kreiner
1st: The boosting approach to machine learning: An overview
2nd: Detecting Group Differences: Mining Contrast Sets (2001)
3rd: An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data