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- item-1 hasContent corina-forascu.
- 818 creator dirk-geeraerts.
- 818 creator dirk-speelman.
- 818 creator kris-heylen.
- 818 creator yves-peirsman.
- 818 type InProceedings.
- 818 label "Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms.".
- 818 sameAs 818.
- 818 abstract "Vector-based models of lexical semantics retrieve semantically related words automatically from large corpora by exploiting the property that words with a similar meaning tend to occur in similar contexts. Despite their increasing popularity, it is unclear which kind of semantic similarity they actually capture and for which kind of words. In this paper, we use three vector-based models to retrieve semantically related words for a set of Dutch nouns and we analyse whether three linguistic properties of the nouns influence the results. In particular, we compare results from a dependency-based model with those from a 1st and 2nd order bag-of-words model and we examine the effect of the nouns frequency, semantic speficity and semantic class. We find that all three models find more synonyms for high-frequency nouns and those belonging to abstract semantic classses. Semantic specificty does not have a clear influence.".
- 818 hasAuthorList authorList.
- 818 hasTopic Linguistics.
- 818 isPartOf proceedings.
- 818 keyword "Lexicon, lexical database".
- 818 keyword "Ontologies".
- 818 keyword "Semantics".
- 818 title "Modelling Word Similarity: an Evaluation of Automatic Synonymy Extraction Algorithms.".
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- item-1 hasContent kris-heylen.
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- 819 creator alexiei-dingli.
- 819 creator hugo-pinto.
- 819 creator roberta-catizone.
- 819 creator yorick-wilks.
- 819 type InProceedings.
- 819 label "Information Extraction Tools and Methods for Understanding Dialogue in a Companion".
- 819 sameAs 819.
- 819 abstract "This paper discusses how Information Extraction is used to understand and manage Dialogue in the EU-funded Companions project. This will be discussed with respect to the Senior Companion, one of two applications under development in the EU-funded Companions project. Over the last few years, research in human-computer dialogue systems has increased and much attention has focused on applying learning methods to improving a key part of any dialogue system, namely the dialogue manager. Since the dialogue manager in all dialogue systems relies heavily on the quality of the semantic interpretation of the user s utterance, our research in the Companions project, focuses on how to improve the semantic interpretation and combine it with knowledge from the Knowledge Base to increase the performance of the Dialogue Manager. Traditionally the semantic interpretation of a user utterance is handled by a natural language understanding module which embodies a variety of natural language processing techniques, from sentence splitting, to full parsing. In this paper we discuss the use of a variety of NLU processes and in particular Information Extraction as a key part of the NLU module in order to improve performance of the dialogue manager and hence the overall dialogue system.".
- 819 hasAuthorList authorList.
- 819 hasTopic Linguistics.
- 819 isPartOf proceedings.
- 819 keyword "Dialogue & Natural Interactivity".
- 819 keyword "Information Extraction, Information Retrieval".
- 819 keyword "Named Entity recognition".
- 819 title "Information Extraction Tools and Methods for Understanding Dialogue in a Companion".
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- 820 creator anthony-levas.
- 820 creator branimir-boguraev.
- 820 creator david-ferrucci.
- 820 creator paul-keyser.
- 820 creator youssef-drissi.
- 820 type InProceedings.
- 820 label "A Development Environment for Configurable Meta-Annotators in a Pipelined NLP Architecture".
- 820 sameAs 820.
- 820 abstract "Information extraction from large data repositories is critical to Information Management solutions. In addition to prerequisite corpus analysis, to determine domain-specific characteristics of text resources, developing, refining and evaluating analytics entails a complex and lengthy process, typically requiring more than just domain expertise. Modern architectures for text processing, while facilitating reuse and (re-)composition of analytical pipelines, do place additional constraints upon the analytics development, as domain experts need not only configure individual annotator components, but situate these within a fully functional annotator pipeline. We present the design, and current status, of a tool for configuring model-driven annotators, which abstracts away from annotator implementation details, pipeline composition constraints, and data management. Instead, the tool embodies support for all stages of ontology-centric model development cycle from corpus analysis and concept definition, to model development and testing, to large scale evaluation, to easy and rapid composition of text applications deploying these concept models. With our design, we aim to meet the needs of domain experts, who are not necessarily expert NLP practitioners.".
- 820 hasAuthorList authorList.
- 820 hasTopic Linguistics.
- 820 isPartOf proceedings.
- 820 keyword "Information Extraction, Information Retrieval".
- 820 keyword "Tools, systems, applications".
- 820 keyword "Usability, user satisfaction".
- 820 title "A Development Environment for Configurable Meta-Annotators in a Pipelined NLP Architecture".
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