Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications by Michael R. Berthold. (Lecture Notes in Computer Science, Volume 7250, 2012, DOI: 10.1007/978-3-642-31830-6)
The volume where Berthold’s Towards Bisociative Knowledge Discovery appears.
Follow the links for article abstracts and additional information. “PDFs” are available under Springer Open Access.
- Towards Bisociative Knowledge Discovery Michael R. Berthold
- Towards Creative Information Exploration Based on Koestler’s Concept of Bisociation Werner Dubitzky, Tobias Kötter, Oliver Schmidt and Michael R. Berthold
- From Information Networks to Bisociative Information Networks Tobias Kötter and Michael R. Berthold
- Network Creation: Overview Christian Borgelt
- Selecting the Links in BisoNets Generated from Document Collections Marc Segond and Christian Borgelt
- Bridging Concept Identification for Constructing Information Networks from Text Documents Matjaž Juršič, Borut Sluban, Bojan Cestnik, Miha Grčar and Nada Lavrač
- Discovery of Novel Term Associations in a Document Collection Teemu Hynönen, Sébastien Mahler and Hannu Toivonen
- Cover Similarity Based Item Set Mining Marc Segond and Christian Borgelt
- Patterns and Logic for Reasoning with Networks Angelika Kimmig, Esther Galbrun, Hannu Toivonen and Luc De Raedt
- Network Analysis: Overview Hannu Toivonen
- BiQL: A Query Language for Analyzing Information Networks Anton Dries, Siegfried Nijssen and Luc De Raedt
- Review of BisoNet Abstraction Techniques Fang Zhou, Sébastien Mahler and Hannu Toivonen
- Simplification of Networks by Edge Pruning Fang Zhou, Sébastien Mahler and Hannu Toivonen
- Network Compression by Node and Edge Mergers Hannu Toivonen, Fang Zhou, Aleksi Hartikainen and Atte Hinkka
- Finding Representative Nodes in Probabilistic Graphs Laura Langohr and Hannu Toivonen
- (Missing) Concept Discovery in Heterogeneous Information Networks Tobias Kötter and Michael R. Berthold
- Node Similarities from Spreading Activation Kilian Thiel and Michael R. Berthold
- Towards Discovery of Subgraph Bisociations Uwe Nagel, Kilian Thiel, Tobias Kötter, Dawid Piątek and Michael R. Berthold
- Exploration: Overview Andreas Nürnberger
- Data Exploration for Bisociative Knowledge Discovery: A Brief Overview of Tools and Evaluation Methods Tatiana Gossen, Marcus Nitsche, Stefan Haun and Andreas Nürnberger
- On the Integration of Graph Exploration and Data Analysis: The Creative Exploration Toolkit Stefan Haun, Tatiana Gossen, Andreas Nürnberger, Tobias Kötter and Kilian Thiel, et al.
- Bisociative Knowledge Discovery by Literature Outlier Detection Ingrid Petrič, Bojan Cestnik, Nada Lavrač and Tanja Urbančič
- Exploring the Power of Outliers for Cross-Domain Literature Mining Borut Sluban, Matjaž Juršič, Bojan Cestnik and Nada Lavrač
- Bisociative Literature Mining by Ensemble Heuristics Matjaž Juršič, Bojan Cestnik, Tanja Urbančič and Nada Lavrač
- Applications and Evaluation: Overview Igor Mozetič and Nada Lavrač
- Biomine: A Network-Structured Resource of Biological Entities for Link Prediction Lauri Eronen, Petteri Hintsanen and Hannu Toivonen
- Semantic Subgroup Discovery and Cross-Context Linking for Microarray Data Analysis Igor Mozetič, Nada Lavrač, Vid Podpečan, Petra Kralj Novak and Helena Motaln, et al.
- Contrast Mining from Interesting Subgroups Laura Langohr, Vid Podpečan, Marko Petek, Igor Mozetič, and Kristina Gruden
- Link and Node Prediction in Metabolic Networks with Probabilistic Logic Angelika Kimmig and Fabrizio Costa
- Modelling a Biological System: Network Creation by Triplet Extraction from Biological Literature Dragana Miljkovic, Vid Podpečan, Miha Grčar, Kristina Gruden and Tjaša Stare, et al.
- Bisociative Exploration of Biological and Financial Literature Using Clustering Oliver Schmidt, Janez Kranjc, Igor Mozetič, Paul Thompson and Werner Dubitzky
- Bisociative Discovery in Business Process Models Trevor Martin and Hongmei He
- Bisociative Music Discovery and Recommendation Sebastian Stober Stefan Haun and Andreas Nürnberger
If you are familiar with Steve Newcomb’s universes of discourse, this will sound hauntingly familiar.
How will diverse methodologies of bisociative knowledge discovery, being in different universes of discourse, interchange information?
Topic maps anyone?