Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
321
result(s) for
"Turkish language Texts"
Sort by:
A Student Grammar of Turkish
A Student Grammar of Turkish is a concise introduction to Turkish grammar, designed specifically for English-speaking students and professionals. Written with the needs of the learner very much in mind, it sets out the grammar of the language in a clear and jargon-free style. The book not only explains the fundamentals of the grammar, but also tests students' understanding in an interactive way with more than 200 exercises. Key grammar points are summarised in tables and there are numerous illustrative examples. A list of grammatical terms used in the book and a key to all the exercises are also provided. This essential grammar and exercise book can be used as a supplement for students studying the language, with a dual function as a reference guide to look up grammar points, and as a resource from which exercises can be set and language skills practised.
eBook
Study of automatic text summarization approaches in different languages
Nowadays we see huge amount of information is available on both, online and offline sources. For single topic we see hundreds of articles are available, containing vast amount of information about it. It is really a difficult task to manually extract the useful information from them. To solve this problem, automatic text summarization systems are developed. Text summarization is a process of extracting useful information from large documents and compressing them into short summary preserving all important content. This survey paper hand out a broad overview on the work done in the field of automatic text summarization in different languages using various text summarization approaches. The focal centre of this survey paper is to present the research done on text summarization on Indian languages such as, Hindi, Punjabi, Bengali, Malayalam, Kannada, Tamil, Marathi, Assamese, Konkani, Nepali, Odia, Sanskrit, Sindhi, Telugu and Gujarati and foreign languages such as Arabic, Chinese, Greek, Persian, Turkish, Spanish, Czeh, Rome, Urdu, Indonesia Bhasha and many more. This paper provides the knowledge and useful support to the beginner scientists in this research area by giving a concise view on various feature extraction methods and classification techniques required for different types of text summarization approaches applied on both Indian and non-Indian languages.
Journal Article
The effect of the conceptual metaphor theory on the teaching of orientation idioms in teaching Turkish as a foreign language
The Challenge Learners who attend a foreign language course aim to learn the lexis and grammar of that language and develop their basic language skills. Does this mean that idioms which are among the essential elements of any language are taught at a satisfactory level to learners? Can learners be taught a strategy that would enable them to guess the meanings of unknown idioms in the contexts they are used? This article presents the results of a study that developed activities to teach idioms that contained orientation metaphors and incorporated them into a language program. In this study, the effects of the conceptual metaphor theory (CMT) on the teaching of orientation idioms was investigated. The study was designed as an action research project and was conducted with 45 B2 level students from 21 countries who were native speakers of 10 different languages. The students were learning Turkish to pursue the undergraduate degrees in Turkish universities. The students were learning and using Turkish for their daily interactions with Turkish people but continued to use their native languages in their closely knit communities. Thus, they formed good examples of true bilingual individuals. At the planning stage of the study, the orientation idioms in the Turkish as a foreign language course books were identified to be used in the teaching activities during the study and a list of orientation idioms was prepared. The students were asked to write the meanings of those idioms and use each one in a sentence to determine whether they had already learned those idioms. The orientation idioms in the B2 level course books were taught through activities based on CMT. At the end of the study, the students were asked to write the meanings of the idioms and use each one in a sentence once again. Pre‐ and poststudy mean scores of the students' performances were compared. It was determined that the implementation based on CMT developed the students' ability to learn metaphors and use them contextually appropriately. Furthermore, it was observed that the teaching activities based on the theory made it easier for the students to learn the idioms and increased their retention in the students' minds. It was also observed that the students had developed the skills of guessing the meanings of new orientation idioms from the contexts they were used in and using them more easily.
Journal Article
A new methodology for automatic creation of concept maps of Turkish texts
Concept maps are two-dimensional visual tools that describe the relationships between concepts belonging to a particular subject. The manual creation of these maps entails problems such as requiring expertise in the relevant field, minimizing visual complexity, and integrating maps, especially in terms of text-intensive documents. In order to overcome these problems, automatic creation of concept maps is required. On the other hand, the production of a fully automated and human-hand quality concept map from a document has not yet been achieved satisfactorily. Motivated by this observation, this study aims to develop a new methodology for automatic creation of the concept maps from Turkish text documents for the first time in the literature. In this respect, within the scope of this study, a new heuristic algorithm has been developed using the Turkish Natural Language Processing software chain and the Graphviz tool to automatically extract concept maps from Turkish texts. The proposed algorithm works with the principle of obtaining concepts based on the dependencies of Turkish words in sentences. The algorithm also determines the sentences to be added to the concept map with a new sentence scoring mechanism. The developed algorithm has been applied on a total of 20 data sets in the fields of Turkish Literature, Geography, Science, and Computer Sciences. The effectiveness of the algorithm has been analyzed with three different performance evaluation criteria, namely precision, recall and F-score. The findings have revealed that the proposed algorithm is quite effective in Turkish texts containing concepts. It has also been observed that the sentence selection algorithm produces results close to the average value in terms of the performance criteria being evaluated. According to the findings, the concept maps automatically obtained by the proposed algorithm are quite similar to the concept maps extracted manually. On the other hand, there is a limitation of the developed algorithm since it is dependent on a natural language processing tool and therefore requires manual intervention in some cases.
Journal Article
Named-entity recognition in Turkish legal texts
Natural language processing (NLP) technologies and applications in legal text processing are gaining momentum. Being one of the most prominent tasks in NLP, named-entity recognition (NER) can substantiate a great convenience for NLP in law due to the variety of named entities in the legal domain and their accentuated importance in legal documents. However, domain-specific NER models in the legal domain are not well studied. We present a NER model for Turkish legal texts with a custom-made corpus as well as several NER architectures based on conditional random fields and bidirectional long-short-term memories (BiLSTMs) to address the task. We also study several combinations of different word embeddings consisting of GloVe, Morph2Vec, and neural network-based character feature extraction techniques either with BiLSTM or convolutional neural networks. We report 92.27% F1 score with a hybrid word representation of GloVe and Morph2Vec with character-level features extracted with BiLSTM. Being an agglutinative language, the morphological structure of Turkish is also considered. To the best of our knowledge, our work is the first legal domain-specific NER study in Turkish and also the first study for an agglutinative language in the legal domain. Thus, our work can also have implications beyond the Turkish language.
Journal Article