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1、Univariate, bivariate and multivariate methods in corpus-based lexicography – a study of synonymyAntti Arppe 19.6.2007Table of Contents1. Introduction (IV: 40 sivua: 4 vkoa – 2 jäljellä) 1.1 Empirical study of
2、 language and the role of corpora 1.2 Synonymy and semantic similarity and their study 1.3 Theoretical premises and assumptions in this study 1.4 Goals of this study2. Materials and their linguistic analysis (II: 30 siv
3、ua: 14.5.-X.6.=5 vkoa) 2.1 Selection of the studied synonyms and contextual features 2.2 Present descriptions of the studied synonyms - Pajunen, PSK, (NS, etymology) 2.3 Compilation of research corpus and its general des
4、cription - HS, SFNET 2.5 Preparation of the corpus for statistical analysis3 Selection and implementation of statistical methods (I: 97 sivua: 23.2-14.5.=11 vkoa) 3.1 Univariate methods 3.1.1 Homogeneity vs. heterogeneit
5、y of the observed distribution 3.1.2 A Zipfian perspective to scrutinizing the distribution 3.1.3 Measures of association 3.2 Bivariate methods 3.3 Multivariate methods 3.3.1 Regression analysis with nominal variables 3.
6、3.2 Heuristics for regression analysis of polytomous cases 3.3.3 Evaluating the performance of multivariate models 3.4 Other possible methods4. Results (III: 50 sivua: X.6.-X.7=3 viikkoa) 4.1 Univariate analyses - genera
7、l: numbers of features, significances, directions of uncertainty reduction, overall and summarily by category - singular morphological features: simple, contextual, analytical - multiple morphological features: person/n
8、umber, mood?, infinitive/participle? - singular syntactic features: argument structure, argument+POS, argument+lexeme, argument+semantics/phrase - multiple syntactic/semantic features: AGENT, PATIENT, SOURCE, DURATION?,
9、 MANNER?, FREQUENCY?, QUANTITY? - singular extra-linguistic features: text category, medium, author, quotes, repetitionRemaining discussion points:- similarity of constructional context, cf. Divjak & Gries 2006. Wha
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