My Account Log in

1 option

Case-Based Reasoning Research and Development : 27th International Conference, ICCBR 2019, Otzenhausen, Germany, September 8-12, 2019, Proceedings / edited by Kerstin Bach, Cindy Marling.

SpringerLink Books Computer Science (2011-2024) Available online

View online
Format:
Book
Contributor:
Bach, Kerstin, Editor.
Marling, Cindy, Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11680
Lecture Notes in Artificial Intelligence, 2945-9141 ; 11680
Language:
English
Subjects (All):
Artificial intelligence.
Information technology-Management.
Information storage and retrieval systems.
Data mining.
Artificial Intelligence.
Computer Application in Administrative Data Processing.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Local Subjects:
Artificial Intelligence.
Computer Application in Administrative Data Processing.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Physical Description:
1 online resource (XXI, 405 pages) : 158 illustrations, 88 illustrations in color.
Edition:
1st ed. 2019.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
System Details:
text file PDF
Summary:
This book constitutes the refereed proceedings of the 27th International Conference on Case-Based Reasoning Research and Development, ICCBR 2019, held in Otzenhausen, Germany, in September 2019. The 26 full papers presented in this book were carefully reviewed and selected from 43 submissions. 15 were selected for oral presentation and 11 for poster presentation. The theme of ICCBR 2019, "Explainable AI (XAI)," was highlighted by several activities. These papers, which are included in the proceedings, address many themes related to the theory and application of case-based reasoning and its future direction.
Contents:
Comparing Similarity Learning with Taxonomies and One-Mode Projection in Context of the FEATURE-TAK Framework
An Algorithm Independent Case-Based Explanation Approach for Recommender Systems Using Interaction Graphs
Explanation of Recommender Systems using Formal Concept Analysis
FLEA-CBR { A Flexible Alternative to the Classic 4R Cycle of Lazy Learned Screening for Efficient Recruitment
Case-Based Reasoning
On the Generalization Capabilities of Sharp Minima in Case-Based Reasoning
CBR Confidence as a Basis for Confidence in Black Box Systems
Probabilistic Selection of Case-Based Explanations in an Underwater Mine Clearance Domain
A Data-Driven Approach for Determining Weights in Global Similarity Functions
Personalized case-based explanation of matrix factorization Recommendations
How Case-Based Reasoning Explains Neural Networks
Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI)
Learning Workflow Embeddings to Improve the Performance of Similarity-Based Retrieval for Process-Oriented Case-Based Reasoning
On Combining Case Adaptation Rules
Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs
An approach to case-based reasoning based on local enrichment of the case base
Improving analogical extrapolation using case pair competence
Towards Finding Flow in Tetris
Scoring Performance on the Y-Balance Test
An Optimal Case-base Maintenance Method for Compositional Adaptation Applications
Towards Human-like Bots using Online Interactive Case-Based Reasoning
Show me your friends, I'll tell you who you are: Recommending products based on hidden evidence
A Tale of Two Communities: An Analysis of Three Decades of Case-Based Reasoning Research
Going Further with Cases: Using Case-Based Reasoning to Recommend Pacing Strategies for Ultra-Marathon Runners
NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery
Adaptation of Scientific Workflows by Means of Process-Oriented Case-Based Reasoning.
Other Format:
Printed edition:
ISBN:
978-3-030-29249-2
9783030292492
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Library Catalog Using Articles+ Library Account