TAILIEUCHUNG - Báo cáo khoa học: "Word to Sentence Level Emotion Tagging for Bengali Blogs"

In this paper, emotion analysis on blog texts has been carried out for a less privileged language like Bengali. Ekman’s six basic emotion types have been selected for reliable and semi automatic word level annotation. An automatic classifier has been applied for recognizing six basic emotion types for different words in a sentence. Application of different scoring strategies to identify sentence level emotion tag based on the acquired word level emotion constituents have produced satisfactory performance. . | Word to Sentence Level Emotion Tagging for Bengali Blogs Dipankar Das Sivaji Bandyopadhyay Department of Computer Science Department of Computer Science Engineering Jadavpur University India Engineering Jadavpur University India sivaj i_cse_ju@ Abstract In this paper emotion analysis on blog texts has been carried out for a less privileged language like Bengali. Ekman s six basic emotion types have been selected for reliable and semi automatic word level annotation. An automatic classifier has been applied for recognizing six basic emotion types for different words in a sentence. Application of different scoring strategies to identify sentence level emotion tag based on the acquired word level emotion constituents have produced satisfactory performance. 1 Introduction Emotion is a private state that is not open to objective observation or verification. So the identification of the emotional state of natural language texts is really a challenging issue. Most of the related work has been conducted for English. The approach in this paper is to assign emotion tags on the Bengali blog sentences with one of the Ekman s 1993 six basic emotion types such as happiness sadness anger fear surprise and disgust. The system consists of two phases machine learning based word level emotion classification followed by assignment of sentence level emotion tags based on the word level constituents using sense based scoring mechanism. The classifier accuracy has been measured through confusion matrix. Corpus based and sense based tag weights have been calculated for each of the six emotion tags and then these emotion tag weights have been used to identify sentence level emotion tag. The tuned reference ranges selected from the development set have proved effective on the test set. The rest of the paper is organized as follows. Section 2 describes the related work. Section 3 briefly describes the resource preparation. Ma chine learning based word .

• Báo cáo khoa học
• Word to Sentence Level Emotion Tagging
• Bengali Blogs
• Dipankar Das Sivaji Bandyopadhyay
• báo cáo khoa học
• báo cáo ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học