Integrating aspect analysis and local outlier factor for intelligent review spam detection

2020 ◽  
Vol 102 ◽  
pp. 163-172 ◽  
Author(s):  
Lan You ◽  
Qingxi Peng ◽  
Zenggang Xiong ◽  
Du He ◽  
Meikang Qiu ◽  
...  
Keyword(s):  
Spam Detection ◽  
Local Outlier Factor ◽  
Review Spam ◽  
Local Outlier

scholarly journals Out-of-Distribution Detection for Deep Neural Networks With Isolation Forest and Local Outlier Factor

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 132980-132989
Author(s):  
Siyu Luan ◽  
Zonghua Gu ◽  
Leonid B. Freidovich ◽  
Lili Jiang ◽  
Qingling Zhao
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Local Outlier Factor ◽  
Local Outlier ◽  
Isolation Forest

Bimodal Distribution and Co-Bursting in Review Spam Detection

2017 ◽  
Author(s):  
Huayi Li ◽  
Geli Fei ◽  
Shuai Wang ◽  
Bing Liu ◽  
Weixiang Shao ◽  
...  
Keyword(s):  
Bimodal Distribution ◽  
Spam Detection ◽  
Review Spam

scholarly journals Credit Card Fraud Detection System

2020 ◽  
Vol 6 (12) ◽  
pp. 24-27
Author(s):  
Shashank Singh and Meenu Garg
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Data Science ◽  
Detection System ◽  
Fraud Detection ◽  
Detection Problem ◽  
Credit Card Fraud ◽  
Local Outlier Factor ◽  
Local Outlier ◽  
Isolation Forest

It is essential that Visa organizations can distinguish false Mastercard exchanges so clients are not charged for things that they didn't buy. Such issues can be handled with Data Science and its significance, alongside Machine Learning, couldn't be more important. This undertaking expects to outline the demonstrating of an informational collection utilizing AI with Credit Card Fraud Detection. The Credit Card Fraud Detection Problem incorporates demonstrating past Visa exchanges with the information of the ones that ended up being extortion. This model is then used to perceive if another exchange is fake. Our target here is to identify 100% of the fake exchanges while limiting the off base misrepresentation arrangements. Charge card Fraud Detection is an average example of arrangement. In this cycle, we have zeroed in on examining and pre- preparing informational indexes just as the sending of numerous irregularity discovery calculations, for example, Local Outlier Factor and Isolation Forest calculation on the PCA changed Credit Card Transaction

Review Spam Detection Using Opinion Mining

2017 ◽  
pp. 273-279 ◽  
Author(s):  
Rohit Narayan ◽  
Jitendra Kumar Rout ◽  
Sanjay Kumar Jena
Keyword(s):  
Opinion Mining ◽  
Spam Detection ◽  
Review Spam

An efficient local outlier detection optimized by rough clustering

2021 ◽  
pp. 1-12
Author(s):  
Chunyan She ◽  
Shaohua Zeng
Keyword(s):  
Outlier Detection ◽  
False Positive Rate ◽  
Time Cost ◽  
Local Distribution ◽  
Running Speed ◽  
Local Outlier Factor ◽  
Real World Applications ◽  
Positive Rate ◽  
Nearest Neighborhood ◽  
Local Outlier

Outlier detection is a hot issue in data mining, which has plenty of real-world applications. LOF (Local Outlier Factor) can capture the abnormal degree of objects in the dataset with different density levels, and many extended algorithms have been proposed in recent years. However, the LOF needs to search the nearest neighborhood of each object on the whole dataset, which greatly increases the time cost. Most of these extended algorithms only consider the distance between an object and its neighborhood, but ignore the local distribution of an object within its neighborhood, resulting in a high false-positive rate. To improve the running speed, a rough clustering based on triple fusion is proposed, which divides a dataset into several subsets and outlier detection is performed only on each subset. Then, considering the local distribution of an object within its neighborhood, a new local outlier factor is constructed to estimate the abnormal degree of each object. Finally, the experimental results indicate that the proposed algorithm has better performance and lower running time than the others.

Detection of High-level PM2.5 Occurrences Applying Local Outlier Factor (LOF) Algorithm

2021 ◽  
Vol 37 (1) ◽  
pp. 125-143
Author(s):  
Yongchan Lee ◽  
Yongbum Kwon ◽  
Heekwan Lee
Keyword(s):  
Local Outlier Factor ◽  
High Level ◽  
Local Outlier

A Grid Partition-Based Local Outlier Factor for Data Stream Processing

2021 ◽  
pp. 1047-1060
Author(s):  
Raed Alsini ◽  
Omar Alghushairy ◽  
Xiaogang Ma ◽  
Terrance Soule
Keyword(s):  
Data Stream ◽  
Stream Processing ◽  
Data Stream Processing ◽  
Local Outlier Factor ◽  
Grid Partition ◽  
Local Outlier

Wavelet Denoising of Near-Earth All-Day Star Map Based on Local Outlier Factor

2020 ◽  
Vol 40 (8) ◽  
pp. 0810001
Author(s):  
吴强 Wu Qiang ◽  
张锐 Zhang Rui
Keyword(s):  
Wavelet Denoising ◽  
Local Outlier Factor ◽  
Local Outlier

scholarly journals Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor

2020 ◽  
Vol 14 (4) ◽  
pp. 551-559 ◽  
Author(s):  
Kun Ding ◽  
Jingwei Zhang ◽  
Hanxiang Ding ◽  
Yongjie Liu ◽  
Fudong Chen ◽  
...  
Keyword(s):  
Fault Detection ◽  
Local Outlier Factor ◽  
Photovoltaic Array ◽  
Local Outlier
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