Aspect Level Opinion Mining for Hotel Reviews in Myanmar Language

被引:0
|
作者
Hnin, Cho Cho [1 ]
Naw, Naw [1 ]
Win, Aung [2 ]
机构
[1] Univ Technol, Dept Informat Sci, Yatanarpon Cyber City, Pyin Oo Lwin, Myanmar
[2] Univ Technol, Yatanarpon Cyber City, Pyin Oo Lwin, Myanmar
关键词
Opinion mining; aspect extraction; sentiment classification; linguistic approach; Myanmar language;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As social networks and online sites are growing rapidly, people can express their opinions in the form of comments and reviews. To analyze such opinionated reviews, the proposed system presents a linguistic approach to opinion mining. This system analyzes hotel user reviews written in Myanmar language and performs the opinion mining tasks at the aspect level. Finally, the system classifies the aspects/features contained in the reviews as positive, negative or neutral. The important task of aspect level opinion mining is identifying the relations between aspects and opinion words in the reviews. This detection is a big challenge because of informal writing styles of reviews. Especially, it is a difficult task of aspect level opinion mining on Myanmar reviews due to the nature of Myanmar language. Therefore, the proposed system mainly focuses on extracting the relevant pairs of aspects and opinion words from the user reviews using the syntactic patterns and some linguistic rules.
引用
收藏
页码:132 / 135
页数:4
相关论文
共 50 条
  • [31] Aspect identification and ratings inference for hotel reviews
    Xue, Wei
    Li, Tao
    Rishe, Naphtali
    WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2017, 20 (01): : 23 - 37
  • [32] Ontology-based Feature Level Opinion Mining for Portuguese Reviews
    Freitas, Larissa A.
    Vieira, Renata
    PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'13 COMPANION), 2013, : 367 - 370
  • [33] Aspect identification and ratings inference for hotel reviews
    Wei Xue
    Tao Li
    Naphtali Rishe
    World Wide Web, 2017, 20 : 23 - 37
  • [34] Leveraging Foreign Language Labeled Data for Aspect-Based Opinion Mining
    Nguyen Thi Thanh Thuy
    Ngo Xuan Bach
    Tu Minh Phuong
    2020 RIVF INTERNATIONAL CONFERENCE ON COMPUTING & COMMUNICATION TECHNOLOGIES (RIVF 2020), 2020, : 35 - 40
  • [35] Opinion Mining from User Reviews
    Tripathy, Amiya Kumar
    Sundararajan, Revathy
    Deshpande, Chinmay
    Mishra, Pankaj
    Natarajan, Neha
    2015 INTERNATIONAL CONFERENCE ON TECHNOLOGY FOR SUSTAINABLE DEVELOPMENT (ICTSD-2015), 2015,
  • [36] An opinion mining framework for Cantonese reviews
    Jian Chen
    Dong Ping Huang
    Shuyue Hu
    Yu Liu
    Yi Cai
    Huaqing Min
    Journal of Ambient Intelligence and Humanized Computing, 2015, 6 : 541 - 547
  • [37] Mining opinion features in customer reviews
    Hu, MQ
    Liu, B
    PROCEEDING OF THE NINETEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE SIXTEENTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2004, : 755 - 760
  • [38] An opinion mining framework for Cantonese reviews
    Chen, Jian
    Huang, Dong Ping
    Hu, Shuyue
    Liu, Yu
    Cai, Yi
    Min, Huaqing
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2015, 6 (05) : 541 - 547
  • [39] Opinion Mining for Online Customer Reviews
    Nanda, Ashok Kumar
    Jalda, Chaitra Sai
    Kumar, V. Pradeep
    Chakali, Venkata Sai Varun
    Munavath, Krishnaveni
    Marukanti, Srihari Prasad Reddy
    Boreda, Divya
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON DATA SCIENCE, MACHINE LEARNING AND APPLICATIONS, VOL 1, ICDSMLA 2023, 2025, 1273 : 903 - 910
  • [40] MultiBooked: A Corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification
    Barnes, Jeremy
    Lambert, Patrik
    Badia, Toni
    PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2018), 2018, : 656 - 660