Traffic classifications based on Statistics methods and Machine learning techniques have attracted a great deal of interest. One challenging issue is that most of supervised algorithms need traffic application informa...
详细信息
the goal of this paper is to investigate which requirements engineering techniques have been applied in the development of Multi-Agent Systems (MAS) and how they were applied. We performed a systematic review of 58 of...
详细信息
ISBN:
(纸本)9783642043932
the goal of this paper is to investigate which requirements engineering techniques have been applied in the development of Multi-Agent Systems (MAS) and how they were applied. We performed a systematic review of 58 of a total of 835 papers found in scientific digital libraries. the results show that most of the proposals for dealing with requirements (79%) use already defined methods or techniques from other software development paradigms and that 69% of these techniques are based on the goal-oriented paradigm. A total of 95% of the reviewed papers focus on techniques for analyzing requirements, and only 45% of them explicitly consider some type of elicitation technique. Finally, only 5% of the papers give some empirical evidence about the effectiveness of their approaches by conducting empirical studies. the results of our study are particularly important in the determination of current research activities in Requirements engineering for MAS and in the identification of research gaps for further investigation.
the proceedings contain 125 papers. the special focus in this conference is on Bioinformatics, data Mining and Knowledge engineering. the topics include: Modelling and clustering of gene expressions using RBFs and a s...
ISBN:
(纸本)3540228810
the proceedings contain 125 papers. the special focus in this conference is on Bioinformatics, data Mining and Knowledge engineering. the topics include: Modelling and clustering of gene expressions using RBFs and a shape similarity metric;a novel hybrid GA/SVM system for protein sequences classification;building genetic networks for gene expression patterns;SVM-based classification of distant proteins using hierarchical motifs;knowledge discovery in lymphoma cancer from gene-expression;a method of filtering protein surface motifs based on similarity among local surfaces;qualified predictions for proteomics pattern diagnostics with confidence machines;an assessment of feature relevance in predicting protein function from sequence;a new artificial immune system algorithm for clustering;the categorisation of similar non-rigid biological objects by clustering local appearance patches;unsupervised dense regions discovery in DNA microarray data;visualisation of distributions and clusters using ViSOMs on gene expression data;prediction of implicit protein-protein interaction by optimal associative feature mining;exploring dependencies between yeast stress genes and their regulators;prediction of natively disordered regions in proteins using a bio-basis function neural network;the effect of image compression on classification and storage requirements in a high-throughput crystallization system;a hybrid approach to human core-promoter prediction;synergy of logistic regression and support vector machine in multiple-class classification;deterministic propagation of blood pressure waveform from human wrists to fingertips;pre-pruning decision trees by local association rules and a new approach for selecting attributes based on rough set theory.
Synchronous finite state machines are very important for digital sequential systems. Among other important aspects, they represent a powerful way for synchronising hardware components so that these components may coop...
详细信息
this paper presents a tool for web usage mining. the aim is centered on providing a tool that facilitates the mining process rather than implement elaborated algorithms and techniques. the tool covers different phases...
详细信息
ISBN:
(纸本)9783540772255
this paper presents a tool for web usage mining. the aim is centered on providing a tool that facilitates the mining process rather than implement elaborated algorithms and techniques. the tool covers different phases of the CRISP-DM methodology as data, preparation, data selection, modeling and evaluation. the algorithms used in the modeling phase are those implemented in the Weka project. the tool has been tested in a web site to find access and navigation patterns.
We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM) [1]. But whereas the GTM i...
详细信息
ISBN:
(纸本)9783540772255
We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM) [1]. But whereas the GTM is an extension of a mixture of experts, this model is an extension of a product of experts [6]. We show visualisation and clustering results on a data set composed of video data of lips uttering 5 Korean vowels and show that the new mapping achieves better results than the standard Self-Organizing Map.
In telecom industry high installation and marketing costs make it between six to ten times more expensive to acquire a new customer than it is to retain the existing one. Prediction and prevention of customer chum is ...
详细信息
ISBN:
(纸本)3540454853
In telecom industry high installation and marketing costs make it between six to ten times more expensive to acquire a new customer than it is to retain the existing one. Prediction and prevention of customer chum is therefore a key priority for industrial research. While all the motives of customer decision to churn are highly uncertain there is lots of related temporal data sequences generated as a result of customer interaction withthe service provider. Existing churn prediction methods like decision tree typically just classify customers into chumers or non-chumers while completely ignoring the timing of chum event. Given histories of other customers and the current customer's data, the presented model proposes a new k nearest sequence (kNS) algorithm along with temporal sequence fusion technique to predict the whole remaining customer data sequence path up to the chum event. It is experimentally demonstrated that the new model better exploits time-ordered customer data sequences and surpasses the existing churn prediction methods in terms of performance and offered capabilities.
In this paper, a new CBR system for Technology Management Centers is presented. the system helps the staff of the centers to solve customer problems by finding solutions successfully applied to similar problems experi...
详细信息
暂无评论