Search results for "Mining"
showing 10 items of 1730 documents
The CogALex-IV Shared Task on the Lexical Access Problem
2014
The shared task of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALexIV) was devoted to a subtask of the lexical access problem, namely multi-stimulus association. In this task, participants were supposed to determine automatically an expected response based on a number of received stimulus words. We describe here the task definition, the theoretical background, the training and test data sets, and the evaluation procedure used for ranking the participating systems. We also summarize the approaches used and present the results of the evaluation. In conclusion, the outcome of the competition are a number of systems which provide very good solutions to the problem.
Using proximity and spatial homogeneity in neighbourhood-based classifiers
1997
In this paper, a set of neighbourhood-based classifiers are jointly used in order to select a more reliable neighbourhood of a given sample and take an appropriate decision about its class membership. The approaches introduced here make use of two concepts: proximity and symmetric placement of the samples.
A novel Bayesian framework for relevance feedback in image content-based retrieval systems
2006
This paper presents a new algorithm for image retrieval in content-based image retrieval systems. The objective of these systems is to get the images which are as similar as possible to a user query from those contained in the global image database without using textual annotations attached to the images. The main problem in obtaining a robust and effective retrieval is the gap between the low level descriptors that can be automatically extracted from the images and the user intention. The algorithm proposed here to address this problem is based on the modeling of user preferences as a probability distribution on the image space. Following a Bayesian methodology, this distribution is the pr…
Network attack detection and classification by the F-transform
2015
We solve the problem of network attack detection and classification. We discuss the way of generation and simulation of an artificial network traffic data. We propose an efficient algorithm for data classification that is based on the F-transform technique. The algorithm successfully passed all tests and moreover, it showed ability to perform classification in an on-line regime.
Analysis of ventricular fibrillation signals using feature selection methods
2012
Feature selection methods in machine learning models are a powerful tool to knowledge extraction. In this work they are used to analyse the intrinsic modifications of cardiac response during ventricular fibrillation due to physical exercise. The data used are two sets of registers from isolated rabbit hearts: control (G1: without physical training), and trained (G2). Four parameters were extracted (dominant frequency, normalized energy, regularity index and number of occurrences). From them, 18 features were extracted. This work analyses the relevance of each feature to classify the records in G1 and G2 using Logistic Regression, Multilayer Perceptron and Extreme Learning Machine. Three fea…
Interactive Image Retrieval Using Smoothed Nearest Neighbor Estimates
2010
Relevance feedback has been adopted by most recent Content Based Image Retrieval systems to reduce the semantic gap that exists between the subjective similarity among images and the similarity measures computed in a given feature space. Distance-based relevance feedback using nearest neighbors has been recently presented as a good tradeoff between simplicity and performance. In this paper, we analyse some shortages of this technique and propose alternatives that help improving the efficiency of the method in terms of the retrieval precision achieved. The resulting method has been evaluated on several repositories which use different feature sets. The results have been compared to those obt…
Enforcing Conceptual Modeling to improve the understanding of human genome
2010
It is widely accepted that the use of Conceptual Modeling techniques in modern Software Engineering leads to a more accurate description of the problem domain. The application of these techniques in the context of challenging domains as the human genome is a fascinating task. The relevant biological concepts should be properly addressed through the creation of the corresponding conceptual schema. This schema will improve the description of the global process followed from a DNA sequence to a fully functional protein. Once the conceptual model is established, the corresponding database is created. The database is intended to act as a unified repository of integrated information that will all…
Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data
2013
Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…
Zur Identifikation von Strukturanalogien in Datenmodellen
2005
On the one hand, data models decrease the complexity of information system development. On the other hand, data models causes additional complexity. Recently structural analogies are discussed as instruments reducing the complexity of data models. This piece of research presents a procedure to identify structural analogies in data models and demonstrates its performance by analyzing Scheer’s reference model for industrial enterprises (Y-CIM-model). The proposed procedure is based on formalizing data models within set theory and uses a quantitative similarity measure. The obtained results show both identical and very similar information structures within the Y-CIM-model. Furthermore, ways of…
Towards MKDA: A Knowledge Discovery Assistant for Researches in Medicine
2007
Nowadays doctors are generating a huge amount of raw data. These data, analyzed with data mining techniques, could be sources of new knowledge. Unluckily such tasks need skilled data analysts, and not so much researchers in Medicine are also data mining experts. In this paper we present a web based system for knowledge discovery assistance in Medicine able to advice a medical researcher in this kind of tasks. The user must define only the experiment specifications in a formal language we have defined. The system GUI helps users in their composition. Then the system plans a Knowledge Discovery Process (KDP) on the basis of rules in a knowledge base. Finally the system executes the KDP and pr…