Takashi Washio; Jun Luo Emerging Trends in Knowledge Discovery and Data Mining 9783642367779

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Автор: Takashi Washio; Jun Luo
Название: Emerging Trends in Knowledge Discovery and Data Mining
ISBN: 9783642367779
Издательство: Springer
Классификация: ISBN-10: 3642367771
Обложка/Формат: Paperback
Страницы: 157
Вес: 0.25 кг.
Дата издания: 20.02.2013
Серия: Lecture Notes in Artificial Intelligence
Язык: English
Размер: 234 x 156 x 9
Основная тема: Computer Science
Подзаголовок: PAKDD 2012 International Workshops: DMHM, GeoDoc, 3Clust, and DSDM, Kuala Lumpur, Malaysia, May 29 -- June 1, 2012, Revised Selected Papers
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:

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.

Emerging Trends in Knowledge Discovery and Data Mining, Takashi Washio; Jun Luo