Matches in ScholarlyData for { ?s ?p ?o. }
- 219 label "Towards a Glossary of Activities in the Ontology Engineering Field".
- 219 sameAs 219.
- 219 abstract "The Semantic Web of the future will be characterized by using a very large number of ontologies embedded in ontology networks. It is important to provide strong methodological support for collaborative and context-sensitive development of networks of ontologies. This methodological support includes the identification and definition of which activities should be carried out when ontology networks are collaboratively built. In this paper we present the consensus reaching process followed within the NeOn consortium for the identification and definition of the activities involved in the ontology network development process. The consensus reaching process here presented produces as a result the NeOn Glossary of Activities. This work was conceived due to the lack of standardization in the Ontology Engineering terminology, which clearly contrasts with the Software Engineering field. Our future aim is to standardize the NeOn Glossary of Activities.".
- 219 hasAuthorList authorList.
- 219 hasTopic Linguistics.
- 219 isPartOf proceedings.
- 219 keyword "Ontologies".
- 219 keyword "Other".
- 219 keyword "Semantic Web".
- 219 title "Towards a Glossary of Activities in the Ontology Engineering Field".
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- item-1 hasContent mari-carmen-suarez-figueroa.
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- item-2 hasContent asuncion-gomez-perez.
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- 22 creator alfons-juan-ciscar.
- 22 creator jorge-civera.
- 22 type InProceedings.
- 22 label "Bilingual Text Classification using the IBM 1 Translation Model".
- 22 sameAs 22.
- 22 abstract "Manual categorisation of documents is a time-consuming task that has been significantly alleviated with the deployment of automatic and machine-aided text categorisation systems. However, the proliferation of multilingual documentation has become a common phenomenon in many international organisations, while most of the current systems have focused on the categorisation of monolingual text. It has been recently shown that the inherent redundancy in bilingual documents can be effectively exploited by relatively simple, bilingual naive Bayes (multinomial) models. In this work, we present a refined version of these models in which this redundancy is explicitly captured by a combination of a unigram (multinomial) model and the well-known IBM 1 translation model. The proposed model is evaluated on two bilingual classification tasks and compared to previous work.".
- 22 hasAuthorList authorList.
- 22 hasTopic Linguistics.
- 22 isPartOf proceedings.
- 22 keyword "Document Classification, Text categorisation".
- 22 keyword "Multilinguality".
- 22 keyword "Statistical methods".
- 22 title "Bilingual Text Classification using the IBM 1 Translation Model".
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- item-1 hasContent jorge-civera.
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- item-2 hasContent alfons-juan-ciscar.
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- 220 creator alain-desilets.
- 220 creator matthieu-hermet.
- 220 creator stan-szpakowicz.
- 220 type InProceedings.
- 220 label "Using the Web as a Linguistic Resource to Automatically Correct Lexico-Syntactic Errors".
- 220 sameAs 220.
- 220 abstract "This paper presents an algorithm for correcting language errors typical of second-language learners. We focus on preposition errors, which are very common among second-language learners but are not addressed well by current commercial grammar correctors and editing aids. The algorithm takes as input a sentence containing a preposition error (and possibly other errors as well), and outputs the correct preposition for that particular sentence context. We use a two-phase hybrid rule-based and statistical approach. In the first phase, rule-based processing is used to generate a short expression that captures the context of use of the preposition in the input sentence. In the second phase, Web searches are used to evaluate the frequency of this expression, when alternative prepositions are used instead of the original one. We tested this algorithm on a corpus of 133 French sentences written by intermediate second-language learners, and found that it could address 69.9% of those cases. In contrast, we found that the best French grammar and spell checker currently on the market, Antidote, addressed only 3% of those cases. We also showed that performance degrades gracefully when using a corpus of frequent n-grams to evaluate frequencies.".
- 220 hasAuthorList authorList.
- 220 hasTopic Linguistics.
- 220 isPartOf proceedings.
- 220 keyword "MultiWord Expressions & Collocations".
- 220 keyword "Statistical methods".
- 220 keyword "Tools, systems, applications".
- 220 title "Using the Web as a Linguistic Resource to Automatically Correct Lexico-Syntactic Errors".
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- item-1 type ListItem.
- item-1 hasContent matthieu-hermet.
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- item-2 hasContent alain-desilets.
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- item-3 hasContent stan-szpakowicz.
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- 221 creator antonio-vaquero-sanchez.
- 221 creator fernando-saenz-perez.
- 221 creator francisco-alvarez-montero.
- 221 type InProceedings.
- 221 label "Conceptual Modeling of Ontology-based Linguistic Resources with a Focus on Semantic Relations".
- 221 sameAs 221.
- 221 abstract "Although ontologies and linguistic resources play a key role in applied AI and NLP, they have not been developed in a common and systematic way. The lack of a systematic methodology for their development has lead to the production of resources that exhibit common flaws between them, and that, at least when it come to ontologies, negatively impact their results and reusability. In this paper, we introduce a software-engineering methodology for the construction of ontology-based linguistic resources, and present a sound conceptual schema that takes into account several considerations for the construction of software tools that allow the systematic and controlled construction of ontology-based linguistic resources.".
- 221 hasAuthorList authorList.
- 221 hasTopic Linguistics.
- 221 isPartOf proceedings.
- 221 keyword "Knowledge representation".
- 221 keyword "Lexicon, lexical database".
- 221 keyword "Ontologies".
- 221 title "Conceptual Modeling of Ontology-based Linguistic Resources with a Focus on Semantic Relations".
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- item-1 hasContent francisco-alvarez-montero.
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- item-2 hasContent antonio-vaquero-sanchez.