%A Nhu Thuat Tran
%A Huu Hong Nguyen
%A Thanh Tung Nguyen
%A Tien Son Dang
%A Thai Le Luong
%A Xuan Hieu Phan
%T Domain-independent Intent Extraction from Online Texts
%X Identifying user’s intents from texts on online channels has wide range of applications from entrepreneurship, banking to e-commerce. However, intent identification is not a simple task due to intent and its attributes are various and strongly depend on the domain of data. In our research, we study the problem of domain-independent intent identification from posts and comments crawled from social networks and discussion forums. We present ten general labels, i.e. labels do not depend on a specific domain, and utilize them when extracting intent and its related information. We also propose the map between general labels and domain-specific labels. We extensively conduct experiments to explore the efficiency of using general labels compared to specific labels in extracting user’s intents when the number of intent domains increases. Our study is conducted on a medium-sized dataset from three selected domains: Tourism, Real Estate and Transportation. In term of accuracy, when the number of domains grows, our proposal achieves significantly better results than the domain-specific method in identifying user’s intent.
%D 2018
%I VNU-UET
%R TR2018-FIT-01
%L SisLab3196