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3,517
Learning Stochastic Logic Programs
, 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a firstorder r ..."
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Cited by 1194 (81 self)
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Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a firstorder
Markov Logic Networks
 MACHINE LEARNING
, 2006
"... We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
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Cited by 816 (39 self)
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learned from relational databases by iteratively optimizing a pseudolikelihood measure. Optionally, additional clauses are learned using inductive logic programming techniques. Experiments with a realworld database and knowledge base in a university domain illustrate the promise of this approach.
Higherorder logic programming
 HANDBOOK OF LOGIC IN AI AND LOGIC PROGRAMMING, VOLUME 5: LOGIC PROGRAMMING. OXFORD (1998
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Uniform proofs as a foundation for logic programming
 ANNALS OF PURE AND APPLIED LOGIC
, 1991
"... A prooftheoretic characterization of logical languages that form suitable bases for Prologlike programming languages is provided. This characterization is based on the principle that the declarative meaning of a logic program, provided by provability in a logical system, should coincide with its ..."
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Cited by 428 (122 self)
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that respects the interpretation of the logical connectives as search instructions. The concept of a uniform proof is used to define the notion of an abstract logic programming language, and it is shown that firstorder and higherorder Horn clauses with classical provability are examples of such a language
HiLog: A foundation for higherorder logic programming
 JOURNAL OF LOGIC PROGRAMMING
, 1993
"... We describe a novel logic, called HiLog, and show that it provides a more suitable basis for logic programming than does traditional predicate logic. HiLog has a higherorder syntax and allows arbitrary terms to appear in places where predicates, functions and atomic formulas occur in predicate calc ..."
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Cited by 252 (42 self)
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We describe a novel logic, called HiLog, and show that it provides a more suitable basis for logic programming than does traditional predicate logic. HiLog has a higherorder syntax and allows arbitrary terms to appear in places where predicates, functions and atomic formulas occur in predicate
BottomUp Relational Learning of Pattern Matching Rules for Information Extraction
, 2003
"... Information extraction is a form of shallow text processing that locates a specified set of relevant items in a naturallanguage document. Systems for this task require significant domainspecific knowledge and are timeconsuming and difficult to build by hand, making them a good application for ..."
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Cited by 406 (20 self)
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for machine learning. We present an algorithm, RAPIER, that uses pairs of sample documents and filled templates to induce patternmatch rules that directly extract fillers for the slots in the template. RAPIER is a bottomup learning algorithm that incorporates techniques from several inductive logic
Knowledge Representation, Computation, and Learning in Higherorder Logic
 In preparation
, 2001
"... This paper contains a systematic study of the foundations of knowledge representation, computation, and learning in higherorder logic. First, a polymorphicallytyped higherorder logic, whose origins can be traced back to Church's simple theory of types, is presented. A model theory and proof ..."
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Cited by 12 (7 self)
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This paper contains a systematic study of the foundations of knowledge representation, computation, and learning in higherorder logic. First, a polymorphicallytyped higherorder logic, whose origins can be traced back to Church's simple theory of types, is presented. A model theory and proof
HIGHERORDER LOGIC LEARNING AND λPROGOL
"... Abstract. We present our research produced about Higherorder Logic Learning (HOLL), which consists of adapting Firstorder Logic Learning (FOLL), like Inductive Logic Programming (ILP), within a Higherorder Logic (HOL) context. We describe a first working implementation of λProgol, a HOLL system a ..."
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Abstract. We present our research produced about Higherorder Logic Learning (HOLL), which consists of adapting Firstorder Logic Learning (FOLL), like Inductive Logic Programming (ILP), within a Higherorder Logic (HOL) context. We describe a first working implementation of λProgol, a HOLL system
Evolutionary HigherOrder Concept Learning
 Stanford University Bookstore
, 1998
"... Current concept learners are limited in their applicability as they generally rely on comparatively poor knowledge representation facilities (e.g. attribute value pairs, flattened horn clauses). The work carried out in support of my thesis has involved extending concept learning to a higher order se ..."
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Cited by 1 (1 self)
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an investigation into the use of genetic programming techniques to allow the exploitation of higherorder features during the induction of structured concept descriptions. 1 Introduction Escher (Lloyd 1995) is a new programming language which combines optimal features of both functional and logic programming
HigherOrder Functions for parsing
, 1993
"... In combinator parsing, the text of parsers resembles BNF notation. We present the basic method, and a number of extensions. We address the special problems presented by white space, and parsers with separate lexical and syntactic phases. In particular, a combining form for handling the "offsi ..."
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Cited by 114 (3 self)
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analyses text to determine its logical structure. For example, the parsing phase in a compiler takes a program text, and produces a parse tree which expounds the structure of the program. Many programs can be improved by having their input parsed. The form of input which is acceptable is usually defined
Results 1  10
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