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Discovery Science

Overview of attention for book
Cover of 'Discovery Science'

Table of Contents

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    Book Overview
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    Chapter 1 On the Expressive Power of Deep Architectures
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    Chapter 2 Learning from Label Preferences
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    Chapter 3 Information Distance and Its Extensions
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    Chapter 4 Models for Autonomously Motivated Exploration in Reinforcement Learning
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    Chapter 5 Optimal Estimation
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    Chapter 6 Monotone Instance Ranking with mira
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    Chapter 7 MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data
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    Chapter 8 Application of Semantic Kernels to Literature-Based Gene Function Annotation
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    Chapter 9 “Tell Me More”: Finding Related Items from User Provided Feedback
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    Chapter 10 MEI: Mutual Enhanced Infinite Generative Model for Simultaneous Community and Topic Detection
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    Chapter 11 A Methodology for Mining Document-Enriched Heterogeneous Information Networks
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    Chapter 12 Multiple Hypothesis Testing in Pattern Discovery
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    Chapter 13 A Parameter-Free Method for Discovering Generalized Clusters in a Network
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    Chapter 14 Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model
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    Chapter 15 Discovery Science
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    Chapter 16 Mining Classification Rules without Support: an Anti-monotone Property of Jaccard Measure
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    Chapter 17 Bootstrapping Parameter Estimation in Dynamic Systems
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    Chapter 18 Network Effects on Tweeting
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    Chapter 19 Context-Aware Personal Route Recognition
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    Chapter 20 Scalable Detection of Frequent Substrings by Grammar-Based Compression
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    Chapter 21 A Statistical Model for Topically Segmented Documents
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    Chapter 22 Predicting Structured Outputs k-Nearest Neighbours Method
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    Chapter 23 The Augmented Itemset Tree: A Data Structure for Online Maximum Frequent Pattern Mining
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    Chapter 24 Word Clouds for Efficient Document Labeling
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    Chapter 25 Global and Local Spatial Autocorrelation in Predictive Clustering Trees
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    Chapter 26 Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier
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    Chapter 27 Graph Clustering Based on Optimization of a Macroscopic Structure of Clusters
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    Chapter 28 Modeling the Temperature of Hot Rolled Steel Plate with Semi-supervised Learning Methods
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    Chapter 29 Controlled Permutations for Testing Adaptive Classifiers
Overall attention for this book and its chapters
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Mentioned by

1 tweeter
1 Wikipedia page

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Discovery Science
Published by
Springer, Berlin, Heidelberg, January 2011
DOI 10.1007/978-3-642-24477-3
978-3-64-224476-6, 978-3-64-224477-3

Elomaa, Tapio, Hollmén, Jaakko, Mannila, Heikki


Tapio Elomaa, Jaakko Hollmén, Heikki Mannila

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 2%
Student > Ph. D. Student 1 2%
Student > Master 1 2%
Unknown 45 94%
Readers by discipline Count As %
Mathematics 1 2%
Computer Science 1 2%
Unknown 46 96%