@inproceedings{10e1be842cb8482ba0bc20a766486bc1,
title = "Quantifying customer review by integrating multiple source of knowledge",
abstract = "The recent emergence of a large volume of customer reviews on e–commerce web sites has raised concerns on the provision of intuitive and comprehensive reputation comparisons of feature dimensions. In this paper, we propose and implement a product reputation mining prototype system. A multiple-knowledge based F–O pair extraction model, which is the center piece of our work, is presented for conducting analyses toward deeper sentence-level comprehension of sentiments in customer reviews. Experimental results demonstrate the effectiveness of the proposed method.",
keywords = "Feature-opinion extraction, Machine learning, Reputation mining, Sentiment quantification",
author = "Yuanchao Liu and Xinping Li and Mingjiang Wang",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 11th International Conference on Machine Learning and Computing, ICMLC 2019 ; Conference date: 22-02-2019 Through 24-02-2019",
year = "2019",
doi = "10.1145/3318299.3318309",
language = "英语",
isbn = "9781450366007",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "6--11",
booktitle = "ACM International Conference Proceeding Series",
address = "美国",
}