Standard corpus analysis tools function effectively for foreign languages
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Peer-reviewed literature and linguistic studies document the successful adaptation, development, and application of corpus analysis tools and resources for diverse foreign languages such as Uyghur, Czech, and various European languages.
With the development of our society, the languages are also constantly evolving. In order to master the word situation of modern Uyghur language, I regard modern Uyghur language data analysis technology as the study method, the standard Uyghur language textbooks frequency list of elementary and junior high school as the object of study, we can make a study of the word situation survey. In this article, first of all, introduces the theme types, theme source in the using corpus. Secondly, to state the algorithm research of modern Uyghur language data analysis system, Third I describe function of the modern Uyghur language data analysis software and working principle of each module. Forth, I regard the standard Uyghur language textbooks frequency list of elementary and junior high school as the object of study to validate the reliability and validity of frequency range analysis, coverage rate analysis and text number distribution analysis function of data analysis system. We obtained Ideal experimental results after the actual experiment. It provides advanced tools and techniques for the next step of modern Uyghur language further in-depth analysis study.
MULTEXT is a European Union project to identify and develop language resources, language-related software, and standards to make the resources maximally usable. MULTEXT-EAST is a spinoff project to develop significant resources for six Central and Eastern European (CEE) languages (Bulgarian, Czech, Estonian, Hungarian, Romanian, Slovenian) and adapt existing tools and standards to them. MULTEXT has developed a corpus encoding standard (CES), and MULTEXT-EAST is applying it to texts in the six languages. This has led to major revision of the CES, particularly to accommodate additional character
Recent advances in research tools for the systematic analysis of textual data are enabling exciting new research throughout the social sciences. For comparative politics, scholars who are often interested in non-English and possibly multilingual textual datasets, these advances may be difficult to access. This article discusses practical issues that arise in the processing, management, translation, and analysis of textual data with a particular focus on how procedures differ across languages. These procedures are combined in two applied examples of automated text analysis using the recently in
Learner corpora, linguistic collections documenting a language as used by learners, provide an important empirical foundation for language acquisition research and teaching practice. This book presents CzeSL, a corpus of non-native Czech, against the background of theoretical and practical issues in the current learner corpus research. Languages with rich morphology and relatively free word order, including Czech, are particularly challenging for the analysis of learner language. The authors address both the complexity of learner error annotation, describing three complementary annotation sche
Accurate opinion mining requires the exact identification of the source and target of an opinion. To evaluate diverse tools, the research community relies on the existence of a gold standard corpus covering this need. Since such a corpus is currently not available for German, the Interest Group on German Sentiment Analysis decided to create such a resource and make it available to the research community in the context of a shared task. In this paper, we describe the selection of textual sources, development of annotation guidelines, and first evaluation results in the creation of a gold standa
Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about specific topics are available online, which allows several parties such as customers, companies and even governments, to explore these opinions. The first task is to classify the text in terms of whether or not it expresses opinion or factual information. Polarity classification is the second task, which distinguishes between polarities (positive, negative or neutral) that sentences may carry. The analysis of natural language
The LinGO Redwoods initiative is a seed activity in the design and development of a new type of treebank. While several medium- to large-scale treebanks exist for English (and for other major languages), pre-existing publicly available resources exhibit the following limitations: (i) annotation is mono-stratal, either encoding topological (phrase structure) or tectogrammatical (dependency) information, (ii) the depth of linguistic information recorded is comparatively shallow, (iii) the design and format of linguistic representation in the treebank hard-wires a small, predefined range of ways
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