Context-based similarity measure on human behavior pattern analysis

2018 ◽  
Vol 23 (14) ◽  
pp. 5455-5467 ◽  
Author(s):  
Aria Ghora Prabono ◽  
Seok-Lyong Lee ◽  
Bernardo Nugroho Yahya
2006 ◽  
Vol 14 (7S_Part_10) ◽  
pp. P548-P548
Author(s):  
Jeonghwan Gwak ◽  
Jong-In Song ◽  
Kiseon Kim ◽  
Moongu Jeon ◽  
Cheolbin Park ◽  
...  

2018 ◽  
Vol 7 (2.12) ◽  
pp. 325
Author(s):  
Jae Gwang Lee ◽  
Jae Pil Lee ◽  
Eun Su Mo ◽  
Jun Hyeon Lee ◽  
Ki Su Yoon ◽  
...  

Background/Objectives: With the development of IT, accidents of industrial secret leakage have occurred more than before. Such acci-dents are mostly caused by insiders. Methods/Statistical analysis: An existing access control system uses RFID and NFC tag. The system saves only the final location in-formation in DB. For the reason, it is hard to track a user’s location data in real time. However, a beacon-based access control system saves a user’s location information in DB in real time. By analyzing the location information of DB, it is possible to track a user. Findings: Beacons are used for determining a user’s location. The determined location information is converted into location data which is saved into DB. The location data is converted into coordinates. The converted coordinate data is analyzed for understanding a user’s behavior pattern. In the pattern analysis, if a user takes an abnormal behavior, policy-based response is performed. The user behavior pattern analysis system proposed in this study is able to respond to an accident in real time. Therefore, it is expected to contribute to reducing the number of industrial secret leakage accidents caused by insiders. Improvements/Applications: This study designs a model that analyzes behavior pattern by using the indoor location data of a user based on beacon. 


Author(s):  
Y. Miao ◽  
X. Tang ◽  
Z. Wang

Abstract. It’s easily to obtain the geometric information of terrain features in a timely manner using advanced surveying and mapping methods, but it is impossible to obtain their semantic information with low latency due to the rapid development of cities. The popularity of GPS-enabled devices and technologies provide us a large number of personal location information. Moreover, it is possible to extract the personal or group behavior pattern due to the regularity of human behavior. Those conditions make it possible to extract and identify human behavior patterns from their trajectory data. In this paper, we present an automatic semantic map generation method that extract semantic patterns and take advantage of them to tagging spatial objects in an unknown region based on known semantic patterns. We study the regularity of trajectory data and build the semantic pattern based on the regularity of human behavior. Most importantly, we use known semantic patterns to identify the semantics of the stay points in the unknown region, and use this method to realize the semantic recognition of the stay points. Results of the experiments show the effectiveness of our proposed method.


2015 ◽  
Vol 239 ◽  
pp. 34-46 ◽  
Author(s):  
M. Casarrubea ◽  
G.K. Jonsson ◽  
F. Faulisi ◽  
F. Sorbera ◽  
G. Di Giovanni ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document