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Learning in the Inductive Logic Programming framework

Inductive Logic Programming for Corpus Based Acquisition of Semantic Lexicons

Inductive Logic Programming for Corpus Based Acquisition of Semantic Lexicons

... The aim of this paper is therefore to present a machine learning method, developed in the Inductive Logic Programming framework, that enables us to automatically ex- tract[r] ...

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The connectionist inductive learning and logic programming system

The connectionist inductive learning and logic programming system

... ulwkp iurp jhqhudo orjlf surjudpv wr qhxudo qhwzrunv zlwk elqdu| wkuhvkrog qhxurqv ^58`1 Zh dovr suhvhqw d wkhruhp vkrzlqj wkdw Q frpsxwhv wkh {hg0srlqw rshudwru +W , ri S1 Wkh wkhruhp [r] ...

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Learning from Ordinal Data with Inductive Logic Programming in Description Logic

Learning from Ordinal Data with Inductive Logic Programming in Description Logic

... Description Logic (DL) based Inductive Logic Pro- gramming (ILP) algorithm for learning relations of ...of learning user preferences from pairwise ...

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Efficient Learning and Evaluation of Complex Concepts in Inductive Logic Programming

Efficient Learning and Evaluation of Complex Concepts in Inductive Logic Programming

... Inductive Logic Programming (ILP) is a subfield of Machine Learning with foundations in logic ...ILP, logic programming, a subset of first-order logic, is used as ...

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An abductive-inductive algorithm for probabilistic inductive logic programming

An abductive-inductive algorithm for probabilistic inductive logic programming

... Inductive Logic Programming (ILP) is concerned with learning logic programs that, together with a background knowledge, explain given examples (or ...not logic-based machine ...

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A History of Probabilistic Inductive Logic Programming

A History of Probabilistic Inductive Logic Programming

... Regarding learning systems, parameter learning should be com- bined with lifted inference to speed up the ...Markov Logic. For structure learning, other search approaches can be investigated, ...

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BET : An Inductive Logic Programming Workbench

BET : An Inductive Logic Programming Workbench

... machine learning and Mining communities who are less familiar with prolog and where it is im- portant to interface learning tools in Java (such as BET) with applications largely written in procedural ...

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Inductive Logic Programming as Abductive Search

Inductive Logic Programming as Abductive Search

... partial hypotheses are already in their final form and are implicitly tested for correctness whenever a new example is selected in the abductive derivation. 5. Discussion and related work We have implemented tal in YAP ...

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CiteSeerX — Learning Information Extraction Rules: An Inductive Logic Programming approach

CiteSeerX — Learning Information Extraction Rules: An Inductive Logic Programming approach

... 4.2 Results The first results include the baseline performance of the learner, plus the F scores obtained by adding each of the five knowledge sources to the learning input individually:[r] ...

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A framework for employee appraisals based on inductive logic programming and data mining methods

A framework for employee appraisals based on inductive logic programming and data mining methods

... Track the progress of the objectives √ √ Χ Table 21 The Main Characteristics of the Developed System and Related Systems 6.5 Summary In this chapter, a description of the system implementation was given. An explanation ...

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Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming

Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming

... reinforcement learning to search for the optimal management strategy for specific dialogue ...reinforcement learning suffers from the fact that it is state ...by learning rules that generalize the ...

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Logic Programs as Declarative and Procedural Bias in Inductive Logic Programming

Logic Programs as Declarative and Procedural Bias in Inductive Logic Programming

... machine learning, such as decision trees, neural networks and support vec- tor machines, in which examples are represented as vectors and hypotheses take the form of trees, weights and hyperplanes respectively, ...

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Incorporating Linguistics Constraints into Inductive Logic Programming

Incorporating Linguistics Constraints into Inductive Logic Programming

... Using linguistic constraints on, for example, head features and gap threading, re- duces the search space to such an extent that, in the small-scale experiments [r] ...

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Combining inductive logic programming, active learning and robotics to discover the function of genes

Combining inductive logic programming, active learning and robotics to discover the function of genes

... a learning cycle in which a learner formulates a plan, monitors the execution of the plan to detect violated expectations and then diagnoses and corrects awed beliefs ...the learning cycle of ASE-Progol if ...

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Learning Constraint Grammar style disambiguation rules using Inductive Logic Programming

Learning Constraint Grammar style disambiguation rules using Inductive Logic Programming

... Learning Constraint Grammar style disambiguation rules using Inductive Logic Programming Learning Constraint Grammar style disambiguation rules using Inductive Logic Programming Nikolaj L i n d b e r[.] ...

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Learning Constraint Grammar style Disambiguation Rules using Inductive Logic Programming

Learning Constraint Grammar style Disambiguation Rules using Inductive Logic Programming

... In the study reported here, the Progol machine-learning system was used to induce CG-style tag eliminating rules from a one mil- lion word part of speech tagged [r] ...

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Explaining clusters with inductive logic programming and linked data

Explaining clusters with inductive logic programming and linked data

... Programming and Linked Data Ilaria Tiddi, Mathieu d’Aquin, Enrico Motta Knowledge Media Institute, The Open University, United Kingdom ...an Inductive Logic Programming process, where they ...

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Inductive logic programming using bounded hypothesis space

Inductive logic programming using bounded hypothesis space

... and learning with constraint- driven ...using learning tasks that highlight the differences between ...for learning a user’s behaviour on a mobile phone from data collected from a real ...a ...

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Predicting the Evolution of Communities with Online Inductive Logic Programming

Predicting the Evolution of Communities with Online Inductive Logic Programming

... supervised learning problem with a variety of classifiers, the problem is that the “knowledge” of a classifier is opaque and consequently incomprehensible to a ...order logic, and in particular the event ...

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A sequence-length sensitive approach to learning biological grammars using inductive logic programming.

A sequence-length sensitive approach to learning biological grammars using inductive logic programming.

... when learning natural grammars, the main focus is on positive examples, the legal sentences of the given language; we want our grammars to be able to parse legal sentences ...grammar learning is not a ...

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