Search results for " mining"
showing 10 items of 1548 documents
Practical Volcano-Independent Recognition of Seismic Events: VULCAN.ears Project
2021
Recognizing the mechanisms underlying seismic activity and tracking temporal and spatial patterns of earthquakes represent primary inputs to monitor active volcanoes and forecast eruptions. To quantify this seismicity, catalogs are established to summarize the history of the observed types and number of volcano-seismic events. In volcano observatories the detection and posterior classification or labeling of the events is manually performed by technicians, often suffering a lack of unified criteria and eventually resulting in poorly reliable labeled databases. State-of-the-art automatic Volcano-Seismic Recognition (VSR) systems allow real-time monitoring and consistent catalogs. VSR systems…
WWOX-related encephalopathies: delineation of the phenotypical spectrum and emerging genotype-phenotype correlation
2014
International audience; BACKGROUND:Homozygous mutations in WWOX were reported in eight individuals of two families with autosomal recessive spinocerebellar ataxia type 12 and in two siblings with infantile epileptic encephalopathy (IEE), including one who deceased prior to DNA sampling.METHODS:By combining array comparative genomic hybridisation, targeted Sanger sequencing and next generation sequencing, we identified five further patients from four families with IEE due to biallelic alterations of WWOX.RESULTS:We identified eight deleterious WWOX alleles consisting in four deletions, a four base-pair frameshifting deletion, one missense and two nonsense mutations. Genotype-phenotype correl…
Field-portable X-ray fluorescence spectrometry as rapid measurement tool for landfill mining operations: comparison of field data vs. laboratory anal…
2015
Landfill mining applied in reclamation at the territories of old dump sites and landfills is a known approach tended to global economic and environmental benefits as recovery of metals and energy i...
An Evaluation Matrix to Compare Computer Hydrological Models for Flood Predictions
2020
In order to predict and control the impacts of floods in torrents, it is important to verify the simulation accuracy of the most used hydrological models. The performance verification is particularly needed for applications in watersheds with peculiar climatic and geomorphological characteristics, such as the Mediterranean torrents. Moreover, in addition to the accuracy, other factors affect the choice of software by stakeholders (users, modellers, researchers, etc.). This study introduces a &ldquo
Web, Artificial Intelligence and Network Applications. Proceedings of the Workshops of the 34th International Conference on Advanced Information Netw…
2020
This proceedings book presents the latest research findings, and theoretical and practical perspectives on innovative methods and development techniques related to the emerging areas of Web computing, intelligent systems and Internet computing. The Web has become an important source of information, and techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play a key role in many of today’s major Web applications, such as e-commerce and computer security. Moreover, Web services provide a new platform for enabling service-oriented systems. The emergence of large-scale distributed co…
Detection of Internet robots using a Bayesian approach
2015
A large part of Web traffic on e-commerce sites is generated not by human users but by Internet robots: search engine crawlers, shopping bots, hacking bots, etc. In practice, not all robots, especially the malicious ones, disclose their identities to a Web server and thus there is a need to develop methods for their detection and identification. This paper proposes the application of a Bayesian approach to robot detection based on characteristics of user sessions. The method is applied to the Web traffic from a real e-commerce site. Results show that the classification model based on the cluster analysis with the Ward's method and the weighted Euclidean metric is very effective in robot det…
Anomaly Detection from Network Logs Using Diffusion Maps
2011
The goal of this study is to detect anomalous queries from network logs using a dimensionality reduction framework. The fequencies of 2-grams in queries are extracted to a feature matrix. Dimensionality reduction is done by applying diffusion maps. The method is adaptive and thus does not need training before analysis. We tested the method with data that includes normal and intrusive traffic to a web server. This approach finds all intrusions in the dataset. peerReviewed
Modeling a non-stationary bots’ arrival process at an e-commerce Web site
2017
Abstract The paper concerns the issue of modeling and generating a representative Web workload for Web server performance evaluation through simulation experiments. Web traffic analysis has been done from two decades, usually based on Web server log data. However, while the character of the overall Web traffic has been extensively studied and modeled, relatively few studies have been devoted to the analysis of Web traffic generated by Internet robots (Web bots). Moreover, the overwhelming majority of studies concern the traffic on non e-commerce websites. In this paper we address the problem of modeling a realistic arrival process of bots’ requests on an e-commerce Web server. Based on real…
Feature selection: A multi-objective stochastic optimization approach
2020
The feature subset task can be cast as a multiobjective discrete optimization problem. In this work, we study the search algorithm component of a feature subset selection method. We propose an algorithm based on the threshold accepting method, extended to the multi-objective framework by an appropriate definition of the acceptance rule. The method is used in the task of identifying relevant subsets of features in a Web bot recognition problem, where automated software agents on the Web are identified by analyzing the stream of HTTP requests to a Web server.
Application of neural network to predict purchases in online store
2016
A key ability of competitive online stores is effective prediction of customers’ purchase intentions as it makes it possible to apply personalized service strategy to convert visitors into buyers and increase sales conversion rates. Data mining and artificial intelligence techniques have proven to be successful in classification and prediction tasks in complex real-time systems, like e-commerce sites. In this paper we proposed a back-propagation neural network model aiming at predicting purchases in active user sessions in a Web store. The neural network training and evaluation was performed using a set of user sessions reconstructed from server log data. The proposed neural network was abl…