Read e-book online Ontology Learning and Population from Text: Algorithms, PDF

By Philipp Cimiano

ISBN-10: 0387306323

ISBN-13: 9780387306322

ISBN-10: 0387392521

ISBN-13: 9780387392523

Standard formalisms for wisdom illustration resembling RDFS or OWL were lately built by way of the semantic internet group and are actually in position. despite the fact that, the an important query nonetheless continues to be: how can we gather all of the wisdom on hand in people's heads to feed our machines?

Natural language is THE technique of verbal exchange for people, and therefore texts are hugely on hand on the net. Terabytes and terabytes of texts containing reviews, principles, proof and data of all types are ready to be mined for fascinating styles and relationships, or used to annotate files to facilitate their retrieval. A semantic net which ignores the big quantity of knowledge encoded in textual content, may well really be a semantic, yet now not a really invaluable, net. wisdom acquisition, and specifically ontology studying from textual content, really needs to be considered as a very important step in the imaginative and prescient of a semantic web.

Ontology studying and inhabitants from textual content: Algorithms, evaluate and Applications offers techniques for ontology studying from textual content and should be proper for researchers engaged on textual content mining, common language processing, details retrieval, semantic internet and ontologies. Containing introductory fabric and a volume of comparable paintings at the one hand, but in addition distinctive descriptions of algorithms, assessment strategies and so forth. at the different, this booklet is acceptable for beginners, and specialists within the box, in addition to lecturers.

Datasets, algorithms and path fabric may be downloaded at http://www.cimiano.de/olp. Ontology studying and inhabitants from textual content: Algorithms, assessment and Applications is designed for practitioners in undefined, to boot researchers and graduate-level scholars in machine science.

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Extra resources for Ontology Learning and Population from Text: Algorithms, Evaluation and Applications

Example text

2001]). In addition to instantiations of these axiom schemata, other general axioms have to be added to the logical theory. e. it depends on the fact whether a type of general a;xiom occurs often enough to deserve the status of an axiom schema. For example, we will assume the following two axioms as being part of our logical theory: Va; {country{x) -> 3y capitaljof{y,x) A\/z{capitaljof{z,x) -^ z = y)) Vx {capital{x) f> 3y capital JO f{x,y) A country{y)) The first axiom states that every country has a unique capital, while the second defines the concept capital as equivalent to saying that there is a country which stands in a capitaLof relation with the corresponding city.

One crucial requirement is thus that the input data is representative for the domain one aims to learn an ontology for. Input data can be schemata such as XML-DTDs, UML diagrams or database schemata. , 2003] as it mainly consists of 'lifting' or mapping definitions from the schema to corresponding ontological definitions. , 2005]). In case ontology learning is performed on the basis of unstructured textual resources, we will speak of ontology learning from text. 20 Ontology Learning from Text :*W': / ^ , Fig.

1 Terms The literature provides many examples of term extraction methods that could be used as a first step in ontology learning from text. , 2001], [Pantel and Lin, 2001]). e. phrase analysis to identify complex noun phrases that may express terms and dependency structure analysis to identify their internal structure. As such parsers are not always available, much of the research on this layer in ontology learning has remained rather restricted. The state-of-the-art is mostly to run a part-of-speech tagger over the domain corpus used for the ontology learning task and then to identify possible terms by manually constructing ad-hoc patterns.

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Ontology Learning and Population from Text: Algorithms, Evaluation and Applications by Philipp Cimiano


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