Phonological properties of word classes and directionality in conversion

2017 ◽  
Vol 10 (2) ◽  
pp. 204-234 ◽  
Author(s):  
Arne Lohmann
Keyword(s):  
Random Forests ◽  
Large Scale ◽  
Word Formation ◽  
Conditional Inference ◽  
Limited Attention ◽  
Word Class ◽  
Conditional Inference Trees ◽  
Word Classes ◽  
Accurate Indicator ◽  
English Noun

In the study of the word-formation process of conversion, one particularly difficult task is to determine the directionality of the process, that is, to decide which word represents the base and which the derived word. One possibility to inform this decision that has received only limited attention is to capitalize on word-class-specific phonological properties. This paper empirically investigates this option for English noun-verb conversion by building on recent findings on phonological differences between these two word classes. A large-scale study of phonological properties is carried out on CELEX data, employing the quantitative techniques of conditional inference trees and random forests. An important result of this analysis is that the accuracy of phonological cues varies widely across different subsamples in the data. Essentially this means that phonological cues can be used as a criterion to determine the directionality of words that are at least two syllables in length. When restricted to this part of the lexicon, phonological properties represent a fairly accurate indicator of source word class and are therefore a useful addition to the linguist's toolkit for determining directionality in conversion. Based on this result, the paper also discusses the relations of phonological properties to other criteria commonly employed to determine directionality.

scholarly journals Morfem Derivasional dalam Bahasa Mandarin

2016 ◽  
Vol 3 (1) ◽  
pp. 78
Author(s):  
Yulie Neila Chandra
Keyword(s):  
Word Formation ◽  
Compound Word ◽  
Word Class ◽  
Formation Processes ◽  
Functional Categories ◽  
New Words ◽  
Word Classes ◽  
Inflectional Morphemes ◽  
Derivational Morphemes ◽  
Derivation Process

<p>Affixation is one of the process of morphological in Mandarin. Affixes are bound morphemes that are added to other morphemes to form larger units such as words, especially to form a compound word (成词 héchéng cí). Mandarin has two types of affixes: prefixes (precedes the morpheme) and suffixes (follows the morpheme). Prefixes are rare in Mandarin, such as {初chū-}, {第dì-}, {非fēi-}, {可kĕ-}, etc;while suffixes are more numerous, such as {儿-er}, {化 –huā}, {家 –jiā}, {们 –men}, {员 –yuán}, {者 –zhĕ}, {子-zi}, etc. In Mandarin, affix morphemes can also be divided into two functional categories, namely inflectional morphemes and derivational morphemes, both refers two principal word formation processes: inflection and derivation. Although, Mandarin is not the inflection language, only prefix {初chū-} and suffix {们–men} are inflectional morphemes. Therefore, the derivation process is more productive in Mandarin. Derivational morphemes form new words by changing the meaning of the base (root) and the word class. In consequence, derivation in Mandarin may cause a change of word classes; such as nouns, verbs, and adjective, but generally form nouns.</p>

scholarly journals Generating Tree-Level Harvest Predictions from Forest Inventories with Random Forests

Forests ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 20 ◽  
Author(s):  
Philipp Kilham ◽  
Christoph Hartebrodt ◽  
Gerald Kändler
Keyword(s):  
Random Forests ◽  
Prediction Models ◽  
Training Data ◽  
Conditional Inference ◽  
Tree Level ◽  
Data Sets ◽  
Wood Supply ◽  
Forest Inventories ◽  
Conditional Inference Trees ◽  
Harvest Decisions

Wood supply predictions from forest inventories involve two steps. First, it is predicted whether harvests occur on a plot in a given time period. Second, for plots on which harvests are predicted to occur, the harvested volume is predicted. This research addresses this second step. For forests with more than one species and/or forests with trees of varying dimensions, overall harvested volume predictions are not satisfactory and more detailed predictions are required. The study focuses on southwest Germany where diverse forest types are found. Predictions are conducted for plots on which harvests occurred in the 2002–2012 period. For each plot, harvest probabilities of sample trees are predicted and used to derive the harvested volume (m³ over bark in 10 years) per hectare. Random forests (RFs) have become popular prediction models as they define the interactions and relationships of variables in an automatized way. However, their suitability for predicting harvest probabilities for inventory sample trees is questionable and has not yet been examined. Generalized linear mixed models (GLMMs) are suitable in this context as they can account for the nested structure of tree-level data sets (trees nested in plots). It is unclear if RFs can cope with this data structure. This research aims to clarify this question by comparing two RFs—an RF based on conditional inference trees (CTree-RF), and an RF based on classification and regression trees (CART-RF)—with a GLMM. For this purpose, the models were fitted on training data and evaluated on an independent test set. Both RFs achieved better prediction results than the GLMM. Regarding plot-level harvested volumes per ha, they achieved higher variances explained (VEs) and significantly (p < 0.05) lower mean absolute residuals when compared to the GLMM. VEs were 0.38 (CTree-RF), 0.37 (CART-RF), and 0.31 (GLMM). Root means squared errors were 138.3, 139.9 and 145.5, respectively. The research demonstrates the suitability and advantages of RFs for predicting harvest decisions on the level of inventory sample trees. RFs can become important components within the generation of business-as-usual wood supply scenarios worldwide as they are able to learn and predict harvest decisions from NFIs in an automatized and self-adapting way. The applied approach is not restricted to specific forests or harvest regimes and delivers detailed species and dimension information for the harvested volumes.

scholarly journals PROSES MORFOLOGIS DALAM BAHASA DAYAK TUNJUNG DI KABUPATEN KUTAI BARAT, PROVINSI KALIMANTAN TIMUR

SUAR BETANG ◽  
2018 ◽  
Vol 12 (2) ◽  
pp. 183
Author(s):  
Halimi Hadibrata
Keyword(s):  
Qualitative Method ◽  
Word Formation ◽  
Word Class ◽  
Note Taking ◽  
Morphological Process ◽  
East Kalimantan ◽  
Word Classes ◽  
The Given

The aim of this research is to discover word class and describing the morphological process of word-formation in Dayak Tunjung. This language is spoken by citizen of West Kutai Region, East Kalimantan. This research applies the qualitative method. The data is collected through survey and note-taking technique. The data is analyzed by using the word-paradigm and valency approach. The word-formation paradigm by affixation, reduplication, and composition to discover word derivation as noun, verb, adjective, and adverb. The valency model of word in sentence is applied to discover preposition and conjunction word class. The result shows that the given language has several word classes, namely noun, verb, adjective, adverb, preposition and conjunction

USING CONDITIONAL INFERENCE TREES AND RANDOM FORESTS TO PREDICT THE BIOACCUMULATION POTENTIAL OF ORGANIC CHEMICALS

2013 ◽  
Vol 32 (5) ◽  
pp. 1187-1195 ◽  
Author(s):  
Sebastian Strempel ◽  
Monika Nendza ◽  
Martin Scheringer ◽  
Konrad Hungerbühler
Keyword(s):  
Random Forests ◽  
Conditional Inference ◽  
Organic Chemicals ◽  
Conditional Inference Trees

The interplay of complexity and subjectivity in opinionated discourse

2020 ◽  
pp. 146144562096692
Author(s):  
Katharina Ehret ◽  
Maite Taboada
Keyword(s):  
Kolmogorov Complexity ◽  
Large Scale ◽  
Online News ◽  
Conditional Inference ◽  
Text Complexity ◽  
Distinctive Features ◽  
Conditional Inference Trees ◽  
Evaluative Language ◽  
Reader Comments ◽  
Linguistic Methods

This paper brings together cutting-edge, quantitative corpus methodologies and discourse analysis to explore the relationship between text complexity and subjectivity as descriptive features of opinionated language. We are specifically interested in how text complexity and markers of subjectivity and argumentation interact in opinionated discourse. Our contributions include the marriage of quantitative approaches to text complexity with corpus linguistic methods for the study of subjectivity, in addition to large-scale analyses of evaluative discourse. As our corpus, we use the Simon Fraser Opinion and Comments Corpus (SOCC), which comprises approximately 10,000 opinion articles and the corresponding reader comments from the Canadian online newspaper The Globe and Mail, as well as a parallel corpus of hard news articles also sampled from The Globe and Mail. Methodologically, we combine conditional inference trees with the analysis of random forests, an ensemble learning technique, to investigate the interplay between text complexity and subjectivity. Text complexity is defined in terms of Kolmogorov complexity, that is, the complexity of a text is measured based on its description length. In this approach, texts which can be described more efficiently are considered to be linguistically less complex. Thus, Kolmogorov complexity is a measure of structural surface redundancy. Our take on subjectivity is inspired by research in evaluative language, stance and Appraisal and defined as the expression of evaluation and opinion in language. Drawing on a sentiment analysis lexicon and the literature on stance markers, a custom set of subjectivity and argumentation markers is created. The results show that complexity can be a powerful tool in the classification of text into different text types, and that stance adverbials serve as distinctive features of subjectivity in online news comments.

The positioning of concessive adverbial clauses in English: assessing the importance of discourse-pragmatic and processing-based constraints

2013 ◽  
Vol 17 (1) ◽  
pp. 1-23 ◽  
Author(s):  
DANIEL WIECHMANN ◽  
ELMA KERZ
Keyword(s):  
Language Processing ◽  
Random Forests ◽  
General Type ◽  
Main Clause ◽  
Conditional Inference ◽  
Relative Importance ◽  
Multifactorial Analysis ◽  
Subordinate Clauses ◽  
Conditional Inference Trees ◽  
Adverbial Clauses

English permits adverbial subordinate clauses to be placed either before or after their associated main clause. Previous research has shown that the positioning is conditioned by various factors from the domains of semantics, discourse pragmatics and language processing. With the exception of Diessel (2008), these factors have never been investigated in concert, which makes it difficult to understand their relative importance. Diessel's study, however, discusses only temporal constructions and identifies iconicity of sequence as the strongest predictor of clause position. Since this explanation is, in principle, unavailable for other types of subordinate clauses, the generalizability of Diessel's findings is somewhat limited. The present study offers a multifactorial analysis of 2,000 concessive constructions from the written part of the BNC and assesses the variable importance of six factors for the ordering choice, showing that semantic and discourse-pragmatic factors are much stronger predictors of clause position than processing-based, weight-related ones. On a methodological note, the study proposes that random forests using conditional inference trees constitute the preferred tool for the general type of problem investigated here.

scholarly journals Slovní druh jako základní jazykovědný a didaktický pojem

2017 ◽  
Vol 15 ◽  
pp. 41-53
Author(s):  
Květoslava Klímová
Keyword(s):  
Elementary Education ◽  
Primary School ◽  
Education Programme ◽  
Word Formation ◽  
Lower Grade ◽  
Word Class ◽  
Linguistic Term ◽  
Basic Functions ◽  
Word Classes ◽  
Definition Of

Word class as a basic linguistic and didactic termthe beginning of the article deals with a word class as a linguistic term. The emphasis is put on its application in both semantic and formal morphology, in lexicology, word formation and syntax. We pay attention to the fact that word classes are not disjunctive groups; it means that there are many words that convert from one word class to another one. In the second part of the contribution, we focus on the meaning of word classes for teaching at primary school, especially at the lower grade. The emphasis is put on three basic functions of words, the semantic, form and syntactic one, whose features are principal components for a definition of a word class. The attention is paid to the last curricular document, i.e. Framework Education Programme for Elementary Education, which was introduced into the education system in 2006/2007. We focus on the position of curriculum about word classes in this document. Finally, we offer possibilities of illustrative tasks that may be used when introducing Primary School Standards and that have been created on the basis of Bloom’s taxonomy minimal, optimal and excellent level. All of the exemplary tasks relate to the curriculum about word classes at lower primary school.

Do Anglian dialects of Old English have a partial pro-drop property?

2019 ◽  
pp. 53-92
Author(s):  
Kristian A. Rusten
Keyword(s):  
Old English ◽  
Random Forests ◽  
Fixed Effects ◽  
Analytical Techniques ◽  
Statistical Modelling ◽  
Descriptive Statistics ◽  
Conditional Inference ◽  
The West ◽  
Conditional Inference Trees ◽  
Logistic Regression Modelling

Chapter 3 deals with the question of whether Anglian dialects of Old English, in contrast to the West Saxon literary standard, had a partial pro-drop property. The chapter investigates this ‘dialect-split hypothesis’ by means of descriptive statistics and inferential statistical modelling. It is also noted that what has been interpreted as diatopic variation could also be representative of other types of variation, and consequently the variables of translation status, period, and genre are also investigated, in addition to dialect. The primary analytical techniques used in this chapter are generalized fixed-effects logistic regression modelling and random forests of conditional inference trees. The chapter concludes that the dialect-split hypothesis must be considered falsified.

Place-name Mutation Variation in Wales and Patagonia

2020 ◽  
Vol 21 (1) ◽  
pp. 143-172
Author(s):  
Morgan Sleeper
Keyword(s):  
Random Forests ◽  
Statistical Approach ◽  
Conditional Inference ◽  
Conversational Speech ◽  
Place Names ◽  
Mutation Strategy ◽  
Significant Difference ◽  
Conditional Inference Trees ◽  
Corpus Data

This study uses corpus data of modern conversational speech to examine variation in the mutation of place-names in Welsh as spoken in both Wales and Patagonia. Specifically, it considers how speakers from both areas mutate (or do not mutate) place-names following the nasal mutation trigger yn 'in', through a two-step statistical approach of conditional inference trees and random forests. Results show no significant difference in how speakers from Wales and Patagonia mutate place-names in this environment, but that the radical initial consonant, speaker age, and place-name type – including the geographical, linguistic, and cultural 'Welshness' of the place-name – all significantly affect mutation behaviour. Furthermore, while nasal mutation is present in the data, the results also illustrate the growing use of soft mutation as an alternate mutation strategy following yn.

Sign in / Sign up

Export Citation Format

Share Document