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Computer Science - Database Management & Information Retrieval | Emerging Trends in Knowledge Discovery and Data Mining - PAKDD 2012 International Workshops: DMHM,

Emerging Trends in Knowledge Discovery and Data Mining

PAKDD 2012 International Workshops: DMHM, GeoDoc, 3Clust, and DSDM, Kuala Lumpur, Malaysia, May 29 -- June 1, 2012, Revised Selected Papers

Washio, Takashi, Luo, Jun (Eds.)

2013, XII, 157 p. 49 illus.

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  • High quality selected papers
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This book constitutes the thoroughly refereed proceedings of the PAKDD 2012 International Workshops: Third Workshop on Data Mining for Healthcare Management (DMHM 2012), First Workshop on Geospatial Information and Documents (GeoDoc 2012), First Workshop on Multi-view data, High-dimensionality, External Knowledge: Striving for a Unified Approach to Clustering (3Clust 2012), and the Second Doctoral Symposium on Data Mining (DSDM 2012); held in conjunction with the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2012), in Kuala Lumpur, Malaysia, May/June 2012.
The 12 revised papers presented were carefully reviewed and selected from numerous submissions. DMHM 2012 aimed at providing a common platform for the discussion of challenging issues and potential techniques in this emerging field of data mining for health care management; 3Clust 2012 focused on solving emerging problems such as clustering ensembles, semi-supervised clustering, subspace/projective clustering, co-clustering, and multi-view clustering; GeoDoc 2012 highlighted the formalization of geospatial concepts and relationships with a focus on the extraction of geospatial relations in free text datasets to offer to the database community a unified framework for geodata discovery; and DSDM 2012 provided the opportunity for Ph.D. students and junior researchers to discuss their work on data mining foundations, techniques and applications.

Content Level » Research

Keywords » classification - health informatics - information retrieval - machine learning - process mining

Related subjects » Artificial Intelligence - Database Management & Information Retrieval

Table of contents 

Modality Classification for Medical Images Using Sparse Coded Affine-Invariant Descriptors.- Mining Web Data for Epidemiological Surveillance.- Getting a Grasp on Clinical Pathway Data: An Approach Based on Process Mining.- ALIVE: A Multi-relational Link Prediction Environment for the Healthcare Domain.- The Relevance of Spatial Relation Terms and Geographical Feature Types.- Applying NLP Techniques for Query Reformulation to Information Retrieval with Geographical References.- Adaptive Evidence Accumulation Clustering Using the Confidence of the Objects’ Assignments.- An Explicit Description of the Extended Gaussian Kernel.- An Improved Genetic Clustering Algorithm for Categorical Data.- Instance-Ranking: A New Perspective to Consider the Instance Dependency for Classification.- Triangular Kernel Nearest-Neighbor-Based Clustering Algorithm for Discovering True Clusters.- DisClose: Discovering Colossal Closed Itemsets via a Memory Efficient Compact Row-Tree.- Mining Web Data for Epidemiological Surveillance.- Getting a Grasp on Clinical Pathway Data: An Approach Based on Process Mining.- ALIVE: A Multi-relational Link Prediction Environment for the Healthcare Domain.- The Relevance of Spatial Relation Terms and Geographical Feature Types.- Applying NLP Techniques for Query Reformulation to Information Retrieval with Geographical References.- Adaptive Evidence Accumulation Clustering Using the Confidence of the Objects’ Assignments.- An Explicit Description of the Extended Gaussian Kernel.- An Improved Genetic Clustering Algorithm for Categorical Data.- Instance-Ranking: A New Perspective to Consider the Instance Dependency for Classification.- Triangular Kernel Nearest-Neighbor-Based Clustering Algorithm for Discovering True Clusters.- DisClose: Discovering Colossal Closed Itemsets via a Memory Efficient Compact Row-Tree.  

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