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A transformation method for aspect-based sentiment analysis

A transformation method for aspect-based sentiment analysis

 Đặng, Văn Thìn
 tr.323-333 English
Sentiment analysisNatural language processingPhân tích văn bảnAspect-based sentiment analysisText analysisXử lí ngôn ngữ
Tác giả CN Đặng, Văn Thìn
Nhan đề A transformation method for aspect-based sentiment analysis / Đặng Văn Thìn,...
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.
Từ khóa tự do Sentiment analysis
Từ khóa tự do Natural language processing
Từ khóa tự do Phân tích văn bản
Từ khóa tự do Aspect-based sentiment analysis
Từ khóa tự do Text analysis
Từ khóa tự do Xử lí ngôn ngữ
Tác giả(bs) CN Vũ, Đức Nguyên
Tác giả(bs) CN Nguyễn, Văn Kiệt
Tác giả(bs) CN Nguyễn Lưu, Thủy Ngân
Nguồn trích Tạp chí Tin học và Điều khiển học- Vol.34, No 4/2018
MARC
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245[1 0] |a A transformation method for aspect-based sentiment analysis / |c Đặng Văn Thìn,...
300[1 0] |a tr.323-333
520[ ] |a 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.
653[0 ] |a Sentiment analysis
653[0 ] |a Natural language processing
653[0 ] |a Phân tích văn bản
653[0 ] |a Aspect-based sentiment analysis
653[0 ] |a Text analysis
653[0 ] |a Xử lí ngôn ngữ
700[0 ] |a Vũ, Đức Nguyên
700[0 ] |a Nguyễn, Văn Kiệt
700[0 ] |a Nguyễn Lưu, Thủy Ngân
773[0 ] |t Tạp chí Tin học và Điều khiển học |g Vol.34, No 4/2018
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