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- 473 creator michael-roth.
- 473 creator sabine-schulte-im-walde.
- 473 type InProceedings.
- 473 label "Corpus Co-Occurrence, Dictionary and Wikipedia Entries as Resources for Semantic Relatedness Information".
- 473 sameAs 473.
- 473 abstract "Distributional, corpus-based descriptions have frequently been applied to model aspects of word meaning. However, distributional models that use corpus data as their basis have one well-known disadvantage: even though the distributional features based on corpus co-occurrence were often successful in capturing meaning aspects of the words to be described, they generally fail to capture those meaning aspects that refer to world knowledge, because coherent texts tend not to provide redundant information that is presumably available knowledge. The question we ask in this paper is whether dictionary and encyclopaedic resources might complement the distributional information in corpus data, and provide world knowledge that is missing in corpora. As test case for meaning aspects, we rely on a collection of semantic associates to German verbs and nouns. Our results indicate that a combination of the knowledge resources should be helpful in work on distributional descriptions.".
- 473 hasAuthorList authorList.
- 473 hasTopic Linguistics.
- 473 isPartOf proceedings.
- 473 keyword "Corpus (creation, annotation, etc.)".
- 473 keyword "Lexicon, lexical database".
- 473 keyword "Semantics".
- 473 title "Corpus Co-Occurrence, Dictionary and Wikipedia Entries as Resources for Semantic Relatedness Information".
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- item-1 hasContent michael-roth.
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- item-2 hasContent sabine-schulte-im-walde.
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- 475 creator bettina-schrader.
- 475 creator jonas-kuhn.
- 475 creator kathrin-spreyer.
- 475 type InProceedings.
- 475 label "Identification of Comparable Argument-Head Relations in Parallel Corpora".
- 475 sameAs 475.
- 475 abstract "We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (languages with no or few NLP tools). The approach exploits advanced existing analysis tools for high-density languages and word-aligned multi-parallel corpora to bridge across languages. The goal is to find a methodology that minimizes the amount of human expert intervention needed, while producing high-quality search and annotation tools. One of the main challenges is the susceptibility of a complex system combining various automatic analysis components to hard-to-control noise from a number of sources. We present systematic experiments investigating to what degree the noise issue can be overcome by (i) exploiting more than one perspective on the target language data by considering multiple translations in the parallel corpus, and (ii) using minimally supervised learning techniques such as co-training and self-training to take advantage of a larger pool of data for generalization. We observe that while (i) does help in the training individual machine learning models, a cyclic bootstrapping process seems to suffer too much from noise. A preliminary conclusion is that in a practical approach, one has to rely on a higher degree of supervision or on noise detection heuristics.".
- 475 hasAuthorList authorList.
- 475 hasTopic Linguistics.
- 475 isPartOf proceedings.
- 475 keyword "Acquisition, Machine Learning".
- 475 keyword "Multilinguality".
- 475 keyword "Syntax".
- 475 title "Identification of Comparable Argument-Head Relations in Parallel Corpora".
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- item-1 hasContent kathrin-spreyer.
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- 477 creator martin-reynaert.
- 477 type InProceedings.
- 477 label "All, and only, the Errors: more Complete and Consistent Spelling and OCR-Error Correction Evaluation".
- 477 sameAs 477.
- 477 abstract "Some time in the future, some spelling error correction system will correct all the errors, and only the errors. We need evaluation metrics that will tell us when this has been achieved and that can help guide us there. We survey the current practice in the form of the evaluation scheme of the latest major publication on spelling correction in a leading journal. We are forced to conclude that while the metric used there can tell us exactly when the ultimate goal of spelling correction research has been achieved, it offers little in the way of directions to be followed to eventually get there. We propose to consistently use the well-known metrics Recall and Precision, as combined in the F score, on 5 possible levels of measurement that should guide us more informedly along that path. We describe briefly what is then measured or measurable at these levels and propose a framework that should allow for concisely stating what it is one performs in one s evaluations. We finally contrast our preferred metrics to Accuracy, which is widely used in this field to this day and to the Area-Under-the-Curve, which is increasingly finding acceptance in other fields.".
- 477 hasAuthorList authorList.
- 477 hasTopic Linguistics.
- 477 isPartOf proceedings.
- 477 keyword "Authoring tools, proofing".
- 477 keyword "Evaluation methodologies".
- 477 keyword "Standards for LRs".
- 477 title "All, and only, the Errors: more Complete and Consistent Spelling and OCR-Error Correction Evaluation".
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- item-1 hasContent martin-reynaert.
- 478 creator eelco-mossel.
- 478 creator kiril-simov.
- 478 creator petya-osenova.
- 478 type InProceedings.
- 478 label "Language Resources for Semantic Document Annotation and Crosslingual Retrieval".
- 478 sameAs 478.
- 478 abstract "This paper describes the interaction among language resources for an adequate concept annotation of domain texts in several languages. The architecture includes domain ontology, domain texts, language specific lexicons, regular grammars and disambiguation rules. Ontology plays a central role in the architecture. We assume that it represents the meaning of the terms in the lexicons. Thus, the lexicons for the languages of the project (http://www.lt4el.eu/ - the LT4eL (Language Technology for eLearning) project is supported by the European Community under the Information Society and Media Directorate, Learning and Cultural Heritage Unit.) are constructed on the base of the ontology. The grammars and disambiguation rules facilitate the annotation of the text with concepts from the ontology. The established in this way relation between ontology and text supports different searches for content in the annotated documents. This is considered the preparatory phase for the integration of a semantic search facility in Learning Management Systems. The implementation and performance of this search are discussed in the context of related work as well as other types of searches. Also the results from some preliminary steps towards evaluation of the concept-based and text-based search are presented.".
- 478 hasAuthorList authorList.
- 478 hasTopic Linguistics.
- 478 isPartOf proceedings.
- 478 keyword "Information Extraction, Information Retrieval".
- 478 keyword "Multilinguality".
- 478 keyword "Ontologies".
- 478 title "Language Resources for Semantic Document Annotation and Crosslingual Retrieval".
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- item-1 hasContent petya-osenova.
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