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Bisociative Knowledge Discovery

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Cover of 'Bisociative Knowledge Discovery'

Table of Contents

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    Book Overview
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    Chapter 1 Bisociative Knowledge Discovery
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    Chapter 2 Bisociative Knowledge Discovery
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    Chapter 3 Bisociative Knowledge Discovery
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    Chapter 4 Network Creation: Overview
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    Chapter 5 Selecting the Links in BisoNets Generated from Document Collections
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    Chapter 6 Bridging Concept Identification for Constructing Information Networks from Text Documents
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    Chapter 7 Discovery of Novel Term Associations in a Document Collection
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    Chapter 8 Cover Similarity Based Item Set Mining
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    Chapter 9 Patterns and Logic for Reasoning with Networks
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    Chapter 10 Network Analysis: Overview
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    Chapter 11 BiQL: A Query Language for Analyzing Information Networks
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    Chapter 12 Review of BisoNet Abstraction Techniques
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    Chapter 13 Simplification of Networks by Edge Pruning
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    Chapter 14 Network Compression by Node and Edge Mergers
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    Chapter 15 Finding Representative Nodes in Probabilistic Graphs
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    Chapter 16 Bisociative Knowledge Discovery
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    Chapter 17 Bisociative Knowledge Discovery
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    Chapter 18 Bisociative Knowledge Discovery
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    Chapter 19 Exploration: Overview
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    Chapter 20 Data Exploration for Bisociative Knowledge Discovery: A Brief Overview of Tools and Evaluation Methods
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    Chapter 21 Bisociative Knowledge Discovery
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    Chapter 22 Bisociative Knowledge Discovery by Literature Outlier Detection
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    Chapter 23 Exploring the Power of Outliers for Cross-Domain Literature Mining
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    Chapter 24 Bisociative Literature Mining by Ensemble Heuristics
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    Chapter 25 Applications and Evaluation: Overview
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    Chapter 26 Biomine: A Network-Structured Resource of Biological Entities for Link Prediction
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    Chapter 27 Semantic Subgroup Discovery and Cross-Context Linking for Microarray Data Analysis
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    Chapter 28 Contrast Mining from Interesting Subgroups
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    Chapter 29 Link and Node Prediction in Metabolic Networks with Probabilistic Logic
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    Chapter 30 Modelling a Biological System: Network Creation by Triplet Extraction from Biological Literature
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    Chapter 31 Bisociative Exploration of Biological and Financial Literature Using Clustering
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    Chapter 32 Bisociative Discovery in Business Process Models
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    Chapter 33 Bisociative Music Discovery and Recommendation
Overall attention for this book and its chapters
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Mentioned by

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1 blog
twitter
3 tweeters

Citations

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9 Dimensions

Readers on

mendeley
159 Mendeley
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1 CiteULike
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Title
Bisociative Knowledge Discovery
Published by
Springer-Verlag Berlin Heidelberg, January 2012
DOI 10.1007/978-3-642-31830-6
ISBNs
978-3-64-231829-0, 978-3-64-231830-6
Editors

Michael R. Berthold

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Brazil 1 <1%
Unknown 157 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 25%
Student > Master 37 23%
Student > Bachelor 17 11%
Researcher 13 8%
Student > Doctoral Student 11 7%
Other 23 14%
Unknown 18 11%
Readers by discipline Count As %
Computer Science 66 42%
Engineering 20 13%
Social Sciences 17 11%
Arts and Humanities 6 4%
Design 5 3%
Other 22 14%
Unknown 23 14%