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Displaying 1-11 out of 11 total
Contextual Sequential Pattern Mining
Found in: Data Mining Workshops, International Conference on
By Julien Rabatel, Sandra Bringay, Pascal Poncelet
Issue Date:December 2010
pp. 981-988
Traditional sequential patterns do not take into account additional contextual information since patterns extracted from data are usually general. By considering the fact that a pattern is associated with one specific context the decision expert can then a...
 
A Hierarchy-Based Method for Synthesizing Frequent Itemsets Extracted from Temporal Windows
Found in: Soft Computing and Pattern Recognition, International Conference of
By Yoann Pitarch, Anne Laurent, Pascal Poncelet
Issue Date:December 2009
pp. 136-142
With the rapid development of information technology, many applications have to deal with potentially infinite data streams. In such a dynamic context, storing the whole data stream history is unfeasible and providing a high-quality summary is required for...
 
SS-IDS: Statistical Signature Based IDS
Found in: Internet and Web Applications and Services, International Conference on
By Payas Gupta, Chedy Raïssi, Gerard Dray, Pascal Poncelet, Johan Brissaud
Issue Date:May 2009
pp. 407-412
Security of web servers has become a sensitive subject today. Prediction of normal and abnormal request is problematic due to large number of false alarms in many anomaly based Intrusion Detection Systems (IDS). SS-IDS derives automatically the parameter p...
 
Multidimensional Data Stream Summarization Using Extended Tilted-Time Windows
Found in: Advanced Information Networking and Applications Workshops, International Conference on
By Yoann Pitarch, Anne Laurent, Marc Plantevit, Pascal Poncelet
Issue Date:May 2009
pp. 250-254
Nowadays, servers register more and more log entries. Monitoring, analyzing and exctracting knowledge from networks and web servers is crucial for a lot of applications. Indeed, logs can be useful for describing the activity by means of several dimensions....
 
Peer-to-Peer Usage Analysis: a Distributed Mining Approach
Found in: Advanced Information Networking and Applications, International Conference on
By Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
Issue Date:April 2006
pp. 993-998
With the huge number of information sources available on the Internet, Peer-to-Peer (P2P) systems offer a novel kind of system architecture providing the large-scale community with applications for file sharing, distributed file systems, distributed comput...
 
Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential Patterns
Found in: Temporal Representation and Reasoning, International Syposium on
By Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire
Issue Date:July 2004
pp. 87-95
In this paper we consider the problem of discovering sequential patterns by handling time constraints. While sequential patterns could be seen as temporal relationships between facts embedded in the database, generalized sequential patterns aim at providin...
 
A Graph-based Method to Detect Rare Events: An Application to Identify Pathologic Cells
Found in: IEEE Computer Graphics and Applications
By Eniko Szekely,Arnaud Sallaberry,Faraz Zaidi,Pascal Poncelet
Issue Date:August 2014
pp. 1
Detection of outliers and anomalous behavior is a well-known problem in the data mining and statistics fields. Although the problem of identifying single outliers has been extensively studied in the literature, little or some effort has been devoted to the...
 
Sampling for Sequential Pattern Mining: From Static Databases to Data Streams
Found in: Data Mining, IEEE International Conference on
By Chedy Raissi, Pascal Poncelet
Issue Date:October 2007
pp. 631-636
Sequential pattern mining is an active field in the domain of knowledge discovery. Recently, with the constant progress in hardware technologies, real-world databases tend to grow larger and the hypothesis that a database can be loaded into main-memory for...
 
Mining time relaxed gradual moving object clusters
Found in: Proceedings of the 20th International Conference on Advances in Geographic Information Systems (SIGSPATIAL '12)
By Dino Ienco, Maguelonne Teisseire, Pascal Poncelet, Phan Nhat Hai
Issue Date:November 2012
pp. 478-481
One of the objectives of spatio-temporal data mining is to analyze moving object datasets to exploit interesting patterns. Traditionally, existing methods only focus on an unchanged group of moving objects during a time period. Thus, they cannot capture ob...
     
French presidential elections: what are the most efficient measures for tweets?
Found in: Proceedings of the first edition workshop on Politics, elections and data (PLEAD '12)
By Dino Ienco, Elnaz Bigdeli, Flavien Bouillot, Mathieu Roche, Pascal Poncelet, Stan Matwin
Issue Date:November 2012
pp. 23-30
Tweets exchanged over the Internet are an important source of information even if their characteristics make them difficult to analyze (e.g., a maximum of 140 characters; noisy data). In this paper, we address the problem of extracting relevant topics thro...
     
A novel approach for privacy mining of generic basic association rules
Found in: Proceeding of the ACM first international workshop on Privacy and anonymity for very large databases (PAVLAD '09)
By Moez Waddey, Pascal Poncelet, Sadok Ben Yahia
Issue Date:November 2009
pp. 45-52
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties from directly sharing the data. The irony is that data mining results rarely...
     
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