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- 14 creator gerard-casamayor.
- 14 creator leo-wanner.
- 14 creator nadjet-bouayad-agha.
- 14 creator sergio-lopez-hernandez.
- 14 type InProceedings.
- 14 label "FootbOWL: Using a generic ontology of football competition for planning match summaries".
- 14 sameAs 14.
- 14 abstract "We present an approach to content selection and discourse structuring in text generation that work directly on a task-independent domain knowledge base (KB) modeled in OWL. In order to facilitate the representation of objects, events and semantic relations that are inferred from the basic facts of the domain to obtain richer and more fluent texts, we distinguish between an extended ontology and an upper layer ontology. The nodes in the KB are weighted according to learnt models of content selection, such that a subset of them can be extracted. The extraction is done using templates that also consider semantic relations between the nodes and the user profile. The discourse structuring submodule maps the semantic relations to discourse relations and forms discourse units to then arrange them into a coherent discourse graph. The approach is illustrated and evaluated on an ontology that models the First Spanish Football League.".
- 14 hasAuthorList authorList.
- 14 isPartOf proceedings.
- 14 keyword "inference rules".
- 14 keyword "natural language generation".
- 14 keyword "ontology".
- 14 keyword "text planning".
- 14 title "FootbOWL: Using a generic ontology of football competition for planning match summaries".
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- item-1 hasContent nadjet-bouayad-agha.
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- item-2 hasContent gerard-casamayor.
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- 17 creator dennis-spohr.
- 17 creator john-mccrae.
- 17 creator philipp-cimiano.
- 17 type InProceedings.
- 17 label "lemon: Linking Lexical Resources and Ontologies on the Semantic Web".
- 17 sameAs 17.
- 17 abstract "There are a large number of ontologies currently available on the Semantic Web. However, in order to exploit them within natural language processing applications, more morphosyntactic information than can be represented in current Semantic Web standards is required. Further, there are a large number of lexical resources available representing a wealth of linguistic information, but this data exists in varied formats and is difficult to link to ontologies and other resources. We present a model we call lemon (Lexicon Model for Ontologies) that supports the sharing of terminological and lexicon resources on the Semantic Web as well as their linking to the existing semantic representations provided by ontologies. We demonstrate that lemon can succinctly represent existing lexical resources and in combination with standard NLP tools we can easily generate new lexica for domain ontologies according to the lemon model. We demonstrate that by combining generated and existing lexica we can collaboratively develop rich lexical descriptions of ontology entities. We also show that the adoption of Semantic Web standards can provide added value for lexicon models by supporting a rich axiomatization of linguistic categories that can be used to constrain the usage of the model and to perform consistency checks.".
- 17 hasAuthorList authorList.
- 17 isPartOf proceedings.
- 17 keyword "Lexical Resource".
- 17 keyword "Lexicon".
- 17 keyword "Linked Data".
- 17 keyword "Ontology".
- 17 title "lemon: Linking Lexical Resources and Ontologies on the Semantic Web".
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- item-1 hasContent john-mccrae.
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- 4 creator eero-hyvoenen.
- 4 creator osma-suominen.
- 4 creator reetta-sinkkilae.
- 4 type InProceedings.
- 4 label "Automatic Semantic Subject Indexing of Web Documents in Highly Inflected Languages".
- 4 sameAs 4.
- 4 abstract "Structured semantic metadata about unstructured web documents can be created using automatic subject indexing methods, avoiding laborious manual indexing. A succesful automatic subject indexing tool for the web should work with texts in multiple languages and be independent of the domain of discourse of the documents and controlled vocabularies. However, analyzing text written in a highly inflected language requires word form normalization that goes beyond rule-based stemming algorithms. We have tested the state-of-the art automatic indexing tool Maui on Finnish texts using three stemming and lemmatization algorithms and tested it with documents and vocabularies of different domains. Both of the lemmatization algorithms we tested performed significantly better than a rule-based stemmer, and the subject indexing quality was found to be comparable to that of human indexers.".
- 4 hasAuthorList authorList.
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- 4 keyword "automatic annotation".
- 4 keyword "controlled vocabulary".
- 4 keyword "inflected languages".
- 4 keyword "subject indexing".
- 4 title "Automatic Semantic Subject Indexing of Web Documents in Highly Inflected Languages".
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- item-1 hasContent reetta-sinkkilae.
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- 11 creator hang-zhang.
- 11 creator jianfeng-chen.
- 11 creator wei-hu.