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Behavioral clustering

Behavioral clustering is a statistical analysis method used in retailing to identify consumer purchase trends and group stores based on consumer… 
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Related topics

Related topics

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Geomarketing

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2020
2020
Behavioral Clustering: A New Approach for Traffic Congestion Evaluation
Nowadays, the analysis of vehicular ad hoc networks for the evaluation of traffic conditions is a hot research field. One of the… 
2018
2018
Automatic Payload Signature Generation for Accurate Identification of Internet Applications and Application Services
The diversity and fast growth of Internet traffic volume are highly influenced by mobile and computer applications being… 
2016
2016
Fractal Clustering and similarity measure: Two new approaches for reducing energy consumption in Wireless Sensor Networks
Sensor clustering is an efficient strategy to reduce the number of messages flowing in a Wireless Sensor Network (WSN… 
2014
2014
Distinguishing between Web Attacks and Vulnerability Scans Based on Behavioral Characteristics
The number of vulnerabilities and reported attacks on Web systems are showing increasing trends, which clearly illustrate the… 
2013
2013
Behavioral Clustering for Point Processes
Groups of parallel point processes may be analyzed with a variety of different goals. Here we consider the case in which one has… 
2013
2013
A Scalable Implementation of Malware Detection Based on Network Connection Behaviors
When hundreds of thousands of applications need to be analyzed within a short period of time, existing static and dynamic malware… 
2012
2012
NetGator: Malware Detection Using Program Interactive Challenges
Internet-borne threats have evolved from easy to detect denial of service attacks to zero-day exploits used for targeted… 
2011
2011
Hypergraph Clustering for Better Network Traffic Inspection
Networked computing environments are subject to configuration errors, unauthorized users, undesired activities and attacks by… 
2011
2011
Defining malware families based on analyst insights
Determining whether arbitrary files are related to known malicious files is often useful in network and host-based defense. Doing… 
Review
2001
Review
2001
Latent groups and cross-level inferences
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