About
Pattern Analysis and Statistical Learning cover a wide range of technologies and theoretical frameworks, and significant activity in the past years has resulted in a remarkable convergence and many advances in the theory and principles underlying the field.
Bringing these technologies to real world demanding applications is however often treated as a separate problem, one that does not directly affect the field as a whole. It is instead important to consider the field of Pattern Analysis as fully including all issues involved with the applications of this technology, and hence all issues that arise when deploying, scaling, implementing and using the technology.
We call for constributions in the form of Demos, Case Studies, Working Systems, Real World Applications and Usage Scenarios. Challenges may stem from the violation of common theoretical assumptions, from the specific types of patterns and noise arising in certain scenarios, or from the problem of scaling up the implementation of state of the art algorithms to real world sizes, or from the creation of integrated software systems that contain multiple pattern-analysis components.
We are also interested in new application areas, where Pattern Analysis has been deployed with success, and in issues involving the visualisation and delivery and exploitation of the patterns discovered by PA technologies. Systems working in noisy and unstructured environments and situations are particularly interesting.
The goal is to discuss and reward work aimed at making theory useful and relevant, without requesting the researchers to propose new theoretical methods, but rather requesting to show how they solved the many challenges related to applying these methods to real world scenarios, or how they benefited other fields of research. Getting ideas to work in real scenarios is what this is about.
More information can be found at WAPA 2011.
Videos
Opening

Opening
Nov 11, 2011
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2552 views
Invited Talks

Medical Text Mining
Nov 11, 2011
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4937 views

Utilizing Unlabeled Data for Classification-Prediction Learning
Nov 11, 2011
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3741 views
Open Text Analysis

Detecting Sentiment Change in Twitter Streaming Data
Nov 11, 2011
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6247 views

Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classific...
Nov 11, 2011
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3093 views
Classification

Streaming Multi-label Classification
Nov 11, 2011
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6119 views

Comparing classification methods for predicting distancestudents' performance
Nov 11, 2011
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4389 views
Images and Vision

Employing The Complete Face in AVSR to Recover from Facial Occlusions
Nov 11, 2011
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2908 views

Bayesian Probabilistic Models for Image Retrieval
Nov 11, 2011
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3375 views
Harvest

Introduction to KNIME
Nov 11, 2011
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6842 views

Self-Tuning Association Rules for KNIME
Nov 11, 2011
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3973 views

The Pascal-2 Harvest Programme
Nov 11, 2011
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2924 views

The "yacaree" approach to association rules
Nov 11, 2011
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3085 views

Treeler: Open-source Structured Prediction for NLP
Nov 11, 2011
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5098 views
Change Tracking

MOA Concept Drift Active Learning Strategies for Streaming Data
Nov 11, 2011
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5987 views

Automating Quantitative Narrative Analysis of News Data
Nov 11, 2011
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9298 views

A Software System for the Microbial Source Tracking Problem
Nov 11, 2011
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3079 views