Archive for the ‘Inductive Logic Programming (ILP)’ Category

Inductive Logic Programming (and Martian Identifications)

Thursday, December 30th, 2010

Inductive Logic Programming: Theory and Methods Authors: Stephen Muggleton, Luc De Raedt

Abstract:

Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. We survey the most important theories and methods of this new eld. Firstly, various problem specifications of ILP are formalised in semantic settings for ILP, yielding a “model-theory” for ILP. Secondly, a generic ILP algorithm is presented. Thirdly, the inference rules and corresponding operators used in ILP are presented, resulting in a “proof-theory” for ILP. Fourthly, since inductive inference does not produce statements which are assured to follow from what is given, inductive inferences require an alternative form of justification. This can take the form of either probabilistic support or logical constraints on the hypothesis language. Information compression techniques used within ILP are presented within a unifying Bayesian approach to confirmation and corroboration of hypotheses. Also, different ways to constrain the hypothesis language, or specify the declarative bias are presented. Fifthly, some advanced topics in ILP are addressed. These include aspects of computational learning theory as applied to ILP, and the issue of predicate invention. Finally, we survey some applications and implementations of ILP. ILP applications fall under two different categories: firstly scientific discovery and knowledge acquisition, and secondly programming assistants.

A good survey of Inductive Logic Programming (ILP) if a bit dated. Feel free to suggest more recent surveys of the area.

As I mentioned under Mining Travel Resources on the Web Using L-Wrappers, the notion of interpretative domains is quite interesting.

I suspect, but cannot prove (at least at this point), that most useful mappings exist between closely related interpretative domains.

Closely related interpretative domains being composed of identifications of a subject that I will quickly recognize as alternative identifications.

Showing me a mapping that includes a Martian identification of my subject, which is not a closely related interpretative domain is unlikely to be useful, at least to me. (I can’t speak for any potential Martians.)

Mining Travel Resources on the Web Using L-Wrappers

Thursday, December 30th, 2010

Mining Travel Resources on the Web Using L-Wrappers Authors Elvira Popescu, Amelia Bădică , and Costin Bădică

Abstract:

The work described here is part of an ongoing research on the application of general-purpose inductive logic programming, logic representation of wrappers (L-wrappers) and XML technologies (including the XSLT transformation language) to information extraction from the Web. The L-wrappers methodology is based on a sound theoretical approach and has already proved its efficacy on a smaller scale, in the area of collecting product information. This paper proposes the use of L-wrappers for tuple extraction from HTML in the domain of e-tourism. It also describes a method for translating L-wrappers into XSLT and illustrates it with the example of a real-world travel agency Web site.

Deeply interesting work in part due to the use of XSLT to extract tuples from HTML pages but also because a labeled ordered tree is used as an interpretive domain for patterns matched against the tree.

If that latter sounds familiar, it should, most data mining techniques specifying a domain in which results (intermediate or otherwise), are going to be interpreted.

I will look around for other material on L-wrappers and inductive logic programming.