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  • A transformation method for aspect-based sentiment analysis /
Tác giả CN Đặng, Văn Thìn
Nhan đề A transformation method for aspect-based sentiment analysis / Đặng Văn Thìn...
Thông tin xuất bản 2018.
Mô tả vật lý tr.323-333
Tóm tắt Along with the explosion of user reviews on the Internet, sentiment analysis has becomeone of the trending research topics in the field of natural language processing. In the last five years,many shared tasks were organized to keep track of the progress of sentiment analysis for various lan-guages. In the Fifth International Workshop on Vietnamese Language and Speech Processing (VLSP2018), the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese lan-guage. In this paper, we describe our system for this shared task. We employ a supervised learningmethod based on the Support Vector Machine classifiers combined with a variety of features. Weobtained the F1-score of 61% for both domains, which was ranked highest in the shared task. For theaspect detection subtask, our method achieved 77% and 69% in F1-score for the restaurant domainand the hotel domain respectively.
Đề mục chủ đề Sentiment analysis
Thuật ngữ không kiểm soát Natural language processing
Thuật ngữ không kiểm soát Phân tích văn bản
Thuật ngữ không kiểm soát Aspect-based sentiment analysis
Thuật ngữ không kiểm soát Text analysis
Thuật ngữ không kiểm soát Ngôn ngữ tự nhiên
Thuật ngữ không kiểm soát Phân tích cảm tính
Tác giả(bs) CN Vũ, Đức Nguyên
Tác giả(bs) CN Nguyễn, Lưu Thủy Ngân
Tác giả(bs) CN Nguyễn, Văn Kiệt
Nguồn trích Tạp chí Tin học và Điều khiển học- Vol.34, No 4
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1000 |aĐặng, Văn Thìn
24510|aA transformation method for aspect-based sentiment analysis / |cĐặng Văn Thìn...
260|c2018.
30010|atr.323-333
520|aAlong with the explosion of user reviews on the Internet, sentiment analysis has becomeone of the trending research topics in the field of natural language processing. In the last five years,many shared tasks were organized to keep track of the progress of sentiment analysis for various lan-guages. In the Fifth International Workshop on Vietnamese Language and Speech Processing (VLSP2018), the Sentiment Analysis shared task was the first evaluation campaign for the Vietnamese lan-guage. In this paper, we describe our system for this shared task. We employ a supervised learningmethod based on the Support Vector Machine classifiers combined with a variety of features. Weobtained the F1-score of 61% for both domains, which was ranked highest in the shared task. For theaspect detection subtask, our method achieved 77% and 69% in F1-score for the restaurant domainand the hotel domain respectively.
65010|aSentiment analysis
6530 |aNatural language processing
6530 |aPhân tích văn bản
6530 |aAspect-based sentiment analysis
6530 |aText analysis
6530 |aNgôn ngữ tự nhiên
6530 |aPhân tích cảm tính
7000|aVũ, Đức Nguyên
7000|aNguyễn, Lưu Thủy Ngân
7000|aNguyễn, Văn Kiệt
7730 |tTạp chí Tin học và Điều khiển học|gVol.34, No 4
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