A Cross-domain Deceptive Opinion Detection by Genetic Algorithm
Qiao-jing Tang, Wei-hua Li, Jing Zhao
Available Online March 2016.
- https://doi.org/10.2991/icmmct-16.2016.123How to use a DOI?
- Deceptive reviews, Cross-domain, Genetic algorithm, Spectral clustering
- With the maturing of the electronic commerce,many people will choose to shop online.At the same time the goods's reviews will influence the decision of people to buy goods,which has led businesses to deliberately write deceptive opinion to improve the sales of goods or undercut rivals .Aiming at the problem of the deceptive reviews,this paper proposes a deceptive reviews detection based on cross-domain and genetic algorithm.To define the data of feature in the source domain ,using genetic algorithm for feature to get the optimal feature set and constructing the feature incidence matrix M y the similarity of documents.it reducing the dimensionality of M , by using spectral clustering algorithm,to obtain a corresponding space mapping.then, with the help of sentiment classifiers,training and being classified in the target domain.Experimental results points that the feasibility and advantages of the method in recognizing the problem of deceptive reviews.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Qiao-jing Tang AU - Wei-hua Li AU - Jing Zhao PY - 2016/03 DA - 2016/03 TI - A Cross-domain Deceptive Opinion Detection by Genetic Algorithm BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology PB - Atlantis Press SP - 621 EP - 625 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-16.2016.123 DO - https://doi.org/10.2991/icmmct-16.2016.123 ID - Tang2016/03 ER -