Luận văn:Vietnamese word clustering and Antonym identification = Phân tích cụm từ tiếng Việt và nhận diện từ trái nghĩa. Luận văn ThS. Công nghệ thông tin: 60 48 01
Nhà xuất bản:ĐHCN
Ngày:2013
Chủ đề:Khoa học máy tính
Xử lý ngôn ngữ tự nhiên
Cụm từ
Từ trái nghĩa
Miêu tả:45 p. + CD-ROM + tóm tắt
Luận văn ThS. Khoa học máy tính -- Trường Đại học Công nghệ. Đại học Quốc gia Hà Nội, 2013
Automatically constructing and clustering of words similarity have many important applications in Natural Language Processing (NLP) tasks, such as dictionary construction, statistical machine translation, named-entity recognition, functional labeling, word segmentation… In recent years, it is a common trend that word clustering is researched in some languages as English, Germany, Chinese… However, the task of word clustering in Vietnamese is a more recent one. In this thesis, I use a large unlabeled data of Vietnamese of about 15 millions words which is equivalent to approximately 700 thousands of sentences. This unlabeled data is extracted from newspapers: Lao dong, PC World, Tuoi tre and then part-of-speech tagged. I investigated some approaches for constructing word clusters in Vietnamese, in which I mainly focus on two main methods by Brown and Dekang Lin. I use the same Vietnamese corpus and the same evaluating tool for these two methods so that I can compare and evaluate the effects of those methods in certain NLP tasks. Besides, I use the statistics method to suggest 20 frames of antonym which can be used to identify antonym classes in clusters.
Electronic Resources
Kiểu:text
Định dạng:text/pdf
Link tải Free download cho anh em Ket-noi:
00051000108_Noi_dung.pdf

---