Contrastive Analysis of Relative Pronouns Between English and Karonese

This study deals with contrastive analysis of relative pronouns between English and Karonese. The objective of this study is analyzed the differences and the similarities of relative pronouns in English and Karonese. This study used qualitative research by doing the documentary technique. The data collected by reading some references which are related to the subject matters. The data which has been collected can be qualified to solve the problem of the research. After analyzing the data, found that the similarities in both languages: Relative Pronouns in English and Karonese has the same position in a sentence, it can be: ‘after the subject or before the object'. Relative Pronouns in Ennglish and Karonese have the same form, Si can be used as subject, object, preposition and possessive for People and Things. And there are no differences of Relative Pronouns between English and Karonese as subject, object and possessive functions based on the position and form

Contrastive Analysis on the Theme/rheme Structure on Headlines of the Jakarta Post and Media Indonesia

This study is to investigate the contrastive structure of Theme/ Rheme analysis in identifying marked and unmarked Themes in English and Indonesian headlines. The study takes as its starting point the assumption that the different choices of Theme/ Rheme, their organization at the local and global structures and the pres-entation of Given/New information of the headlines presented in English and Indonesian. This study designs a Discourse Analysis. It analyzes Theme/Rheme in Indonesian and English clauses. The study seeks to ana-lyze and compare the different choices of Theme/Rheme in the thematic structures. These issues are investi-gated in a corpus of English and Indonesian headline about lieu of law on direct regional election. Most of the Theme used was marked themes. Keywords: Contrastive, Theme and Rheme, Headline

A Contrastive Analysis of English and Arabic Tenses

The study deals with the similarities and differences of Tenses in English andArabic Tenses. The application to the language teaching and learning process. Inthis study the researcher focuses on the three main tenses of both languagesnamely simple Present Tense, simple Past Tense, and Future Tense, that isdescribing the verb systems of both languages based on to each tense. The datathat support this study are obtained by applying a documentary technique thatselected by reading some references related to the subject matters. The data areanalyzed by using the theory of Contrastive Analysis to found out the similaritiesand differences of tenses in English and Arabic. The findings show some aspectsof tenses in English are similar to those in Arabic. The differences are bothEnglish and Arabic has different number of pronoun. English consists of sevenpronouns while Arabic pronouns are fourteen which influence the verb formation

A Contrastive Analysis of Interrogative Sentences in English and Indonesian

The aim of this paper is to investigate the forms of questions in English and Indonesian in order to identify the similarities and differences between them. CA may look at linguistic structures in a twofold way: predictability power and wash back effect (Cheng, Watanabe & Curtis, 2004). The former deals with foreseeing the areas of problems the English learners may commit and the latter refers to the effect of diagnostic value of CA on improvement of teaching processes. In this case, the researcher emphasizes her study in analyzing CA based on the first perspective; this study focuses on interrogative sentences which are in the form of questions which play an important role in learning English among junior English students. This study has found the differences and similarities between Indonesian and English. Recognizing this will contribute to the accuracy of English questions made by the students

A Theoretical Analysis of Contrastive Unsupervised Representation Learning

Recent empirical works have successfully used unlabeled data to learn feature representations that are broadly useful in downstream classification tasks. Several of these methods are reminiscent of the well-known word2vec embedding algorithm: leveraging availability of pairs of semantically "similar" data points and "negative samples," the learner forces the inner product of representations of similar pairs with each other to be higher on average than with negative samples. The current paper uses the term contrastive learning for such algorithms and presents a theoretical framework for analyzing them by introducing latent classes and hypothesizing that semantically similar points are sampled from the same latent class. This framework allows us to show provable guarantees on the performance of the learned representations on the average classification task that is comprised of a subset of the same set of latent classes. Our generalization bound also shows that learned representations can reduce (labeled) sample complexity on downstream tasks. We conduct controlled experiments in both the text and image domains to support the theory.Comment: 19 pages, 5 figure

Target Contrastive Pessimistic Discriminant Analysis

Domain-adaptive classifiers learn from a source domain and aim to generalize to a target domain. If the classifier's assumptions on the relationship between domains (e.g. covariate shift) are valid, then it will usually outperform a non-adaptive source classifier. Unfortunately, it can perform substantially worse when its assumptions are invalid. Validating these assumptions requires labeled target samples, which are usually not available. We argue that, in order to make domain-adaptive classifiers more practical, it is necessary to focus on robust methods; robust in the sense that the model still achieves a particular level of performance without making strong assumptions on the relationship between domains. With this objective in mind, we formulate a conservative parameter estimator that only deviates from the source classifier when a lower or equal risk is guaranteed for all possible labellings of the given target samples. We derive the corresponding estimator for a discriminant analysis model, and show that its risk is actually strictly smaller than that of the source classifier. Experiments indicate that our classifier outperforms state-of-the-art classifiers for geographically biased samples.Comment: 9 pages, no figures, 2 tables. arXiv admin note: substantial text overlap with arXiv:1706.0808

Linguocultural Peculiarities of German and Georgian Phraseological Units – Contrastive Analysis

Knowledge about the world begins with gaining knowledge about the language. Language is a part of our national culture and plays one of the main roles in its formation. Unity of language, culture and thinking determines and forms not only national mentality, but national character as well. Specific features of the national identity are reflected in phraseological units. Phraseological unit in German, as well as in Georgian language, is a complex verbal formation. Linguistic and extralinguistic factors play an importanat role in the formation and development of phraseological units. But there are still questions – how are these phraseological units created and which language is the source language and which one is the target one. Our goal is to study the origin and structure of some German phraseological units (especially idiomatic phraseology)and to find their equivalents in Georgian. We also aim at enriching idiomatic phraseologisms with the examples of their actual use in current parlance, finding their Georgian equivalents. The present work tries to contribute to broadening the scope of investigation and methodology of the previous contrastive German-Georgian phraseology research and fill research gaps in this field