DocumentCode :
2980989
Title :
Crime detection using Latent Semantic Analysis and hierarchical structure
Author :
Wang, Canyu ; Guo, Xuebi ; Han, Hao
Author_Institution :
Sch. of Sci., South China Univ. of Technol., Guangzhou, China
fYear :
2012
fDate :
22-24 June 2012
Firstpage :
337
Lastpage :
340
Abstract :
We make efforts to help the investigator discover the hidden conspirators. In the criminal cases, the investigators or the police have to make full use of the messages or spoken documents data that they record in files. Thus, mining the latent information from messages is vital to them. In Information Retrieval area, Latent Semantic Analysis (LSA) is an important method for query matching which can discover the underlying semantic relation or similarity between words and topics. We introduce a network hierarchical structure to analyze the original message network, making the analysis conveniently as well as ensuring the connectivity of the inner network connection of all the conspirators. For this purpose, we use LSA to measure the similarities between topics and Crime Prototype Vector, and the similarities will be used as the weights of the paths in the network hierarchies and calculate the suspicious degrees.
Keywords :
computer crime; document handling; information retrieval; natural language processing; LSA; crime detection; crime prototype vector; data mining; hidden conspirators; information retrieval area; inner network connection; latent semantic analysis; network hierarchical structure; query matching; semantic relation; semantic similarity; spoken documents; Educational institutions; Irrigation; Vectors; Crime Detection; Latent Semantic Analysis; Network Hierarchical Structure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2012 IEEE 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2007-8
Type :
conf
DOI :
10.1109/ICSESS.2012.6269474
Filename :
6269474
Link To Document :
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