@inproceedings{e8c0b132df564ac8bfea6bef2fdcbe0c,
title = "Converging human knowledge for opinion mining",
abstract = "Opinion mining focuses on analyzing opinions in documents. Existing most algorithms for mining opinion either are machine-only, leaving plenty of confused puzzles due to lacking human background knowledge, or using opinion dictionary from domain experts. The latter is expensive and hard to scale. In this paper, we propose a novel approach RULING (conveRging hUman knowLedge opInion miNinG) for opinion mining, where human include both the crowd and the experts. Firstly, we propose a method for combining expert knowledge with the machine learning method. Then we use the prediction result to find out the hard item, and classify them using crowdsourcing. This method can scale better than the previous methods and get a better result. Experimental results demonstrate our RULING approach outperforms related proposals in terms of classification performance.",
author = "Jiacheng Liu and Feilong Tang and Long Chen and Liang Qiao and Yanqin Yang and Wenchao Xu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.; 11th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2017 ; Conference date: 10-07-2017 Through 12-07-2017",
year = "2017",
doi = "10.1007/978-3-319-61542-4\_21",
language = "英语",
isbn = "9783319615417",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "219--230",
editor = "Tomoya Enokido and Leonard Barolli",
booktitle = "Innovative Mobile and Internet Services in Ubiquitous Computing - Proceedings of the 11th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2017",
address = "德国",
}