Memetic Spider Monkey Optimization for Spam Review Detection Problem
- Title
- Memetic Spider Monkey Optimization for Spam Review Detection Problem
- Creator
- Shekhawat S.S.; Sharma H.; Kumar S.
- Description
- Spider monkey optimization (SMO) algorithm imitates the spider monkey's fission-fusion social behavior. It is evident through literature that the SMO is a competitive swarm-based algorithm that is used to solve difficult real-life problems. The SMO's search process is a little bit biased by the random component that drives it with high explorative searching steps. A hybridized SMO with a memetic search to improve the local search ability of SMO is proposed here. The newly developed strategy is titled Memetic SMO (MeSMO). Further, the proposed MeSMO-based clustering approach is applied to solve a big data problem, namely, the spam review detection problem. A customer usually makes decisions to purchase something or make an image of someone based on online reviews. Therefore, there is a good chance that the individuals or companies may write spam reviews to upgrade or degrade the stature or value of a trader/product/company. Therefore, an efficient spam detection algorithm, MeSMO, is proposed and tested over four complex spam datasets. The reported results of MeSMO are compared with the outcomes obtained from the six state-of-art strategies. A comparative analysis of the results proved that MeSMO is a good technique to solve the spam review detection problem and improved precision by 3.68%. 2023 Mary Ann Liebert, Inc., publishers.
- Source
- Big Data, Vol-11, No. 2, pp. 137-149.
- Date
- 2023-01-01
- Publisher
- Mary Ann Liebert Inc.
- Subject
- big data; golden section search; memetic search; optimization; spam review; swarm intelligence
- Coverage
- Shekhawat S.S., Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India; Sharma H., Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India
- Rights
- Restricted Access
- Relation
- ISSN: 21676461; PubMed ID: 34152859
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Shekhawat S.S.; Sharma H.; Kumar S., “Memetic Spider Monkey Optimization for Spam Review Detection Problem,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/14308.