Inductive Logic Programming : 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers / edited by Jesse Davis, Jan Ramon.
- 1st ed. 2015.
- Cham : Springer International Publishing : Imprint: Springer, 2015.
- Computer Science (Springer-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 9046
Lecture Notes in Artificial Intelligence ; 9046
1 online resource (X, 211 pages) : 62 illustrations in color.
- Logic, Symbolic and mathematical.
- Local subjects:
- Mathematical Logic and Formal Languages. (search)
Artificial Intelligence. (search)
Programming Techniques. (search)
Information Systems Applications (incl. Internet). (search)
Logics and Meanings of Programs. (search)
Computation by Abstract Devices. (search)
- System Details:
- text file PDF
- This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Conference on Inductive Logic Programming, ILP 2014, held in Nancy, France, in September 2014. The 14 revised papers presented were carefully reviewed and selected from 41 submissions. The papers focus on topics such as the inducing of logic programs, learning from data represented with logic, multi-relational machine learning, learning from graphs, and applications of these techniques to important problems in fields like bioinformatics, medicine, and text mining.
- Reframing on Relational Data
Inductive Learning using Constraint-driven Bias
Nonmonotonic Learning in Large Biological Networks
Construction of Complex Aggregates with Random Restart Hill-Climbing
Logical minimisation of meta-rules within Meta-Interpretive Learning
Goal and plan recognition via parse trees using prefix and infix probability computation
Effectively creating weakly labeled training examples via approximate domain knowledge
Learning Prime Implicant Conditions From Interpretation Transition
Statistical Relational Learning for Handwriting Recognition
The Most Probable Explanation for Probabilistic Logic Programs with Annotated Disjunctions
Towards machine learning of predictive models from ecological data
PageRank, ProPPR, and Stochastic Logic Programs
Complex aggregates over clusters of elements
On the Complexity of Frequent Subtree Mining in Very Simple Structures.
- Davis, Jesse, editor., Editor,
Ramon, Jan, editor., Editor,
SpringerLink (Online service)
- Contained In:
- Springer eBooks
- Other format:
- Printed edition:
- Publisher Number:
- 10.1007/978-3-319-23708-4 doi
- Access Restriction:
- Restricted for use by site license.
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