Inductive Logic Programming: 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers

Author:   Jesse Davis ,  Jan Ramon
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2015
Volume:   9046
ISBN:  

9783319237077


Pages:   211
Publication Date:   27 December 2015
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Inductive Logic Programming: 24th International Conference, ILP 2014, Nancy, France, September 14-16, 2014, Revised Selected Papers


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Author:   Jesse Davis ,  Jan Ramon
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2015
Volume:   9046
Dimensions:   Width: 15.50cm , Height: 1.20cm , Length: 23.50cm
Weight:   0.454kg
ISBN:  

9783319237077


ISBN 10:   3319237071
Pages:   211
Publication Date:   27 December 2015
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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.

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