Genetic and Evolutionary Computation Conference 2008
... Dr. Maarten Keijzer to thank for ensuring that everyone stuck with their deadlines. The third, and most important part of GECCO’s success is its attendees. A conference can only be as good as those attending it, and GECCO has been fortunate enough to attract a wonderful mix of innovation, curiosity ...
... Dr. Maarten Keijzer to thank for ensuring that everyone stuck with their deadlines. The third, and most important part of GECCO’s success is its attendees. A conference can only be as good as those attending it, and GECCO has been fortunate enough to attract a wonderful mix of innovation, curiosity ...
Redescription Mining Over non-Binary Data Sets Using Decision
... redescription mining performed meaningful outcomes. And in case if both data sets contain real-valued entries the exhaustive search is inevitable. This, in turn, might put unwanted computational burden. Beside this, redescription mining using decision trees with a modification such that it can work ...
... redescription mining performed meaningful outcomes. And in case if both data sets contain real-valued entries the exhaustive search is inevitable. This, in turn, might put unwanted computational burden. Beside this, redescription mining using decision trees with a modification such that it can work ...
Outlier Detection Techniques
... • Discussion of the basic intuition based on Hawkins – Data is usually multivariate, i.e., multi-dimensional => basic model is univariate, i.e., 1-dimensional – There is usually more than one generating mechanism/statistical process underlying the “normal” data => basic model assumes only one “norma ...
... • Discussion of the basic intuition based on Hawkins – Data is usually multivariate, i.e., multi-dimensional => basic model is univariate, i.e., 1-dimensional – There is usually more than one generating mechanism/statistical process underlying the “normal” data => basic model assumes only one “norma ...
Customer Segmentation and Strategy Definition in Segments: Case
... clustering, grid-based clustering, fuzzy clustering and hierarchical clustering (Cao et al, 2010). ...
... clustering, grid-based clustering, fuzzy clustering and hierarchical clustering (Cao et al, 2010). ...
87 Mining Concept Sequences from Large
... on whether the user can raise queries properly describing the information need to search engines. Writing queries is never easy, partially because queries are typically expressed in a very small number of words (two or three words on average) [Jansen et al. 1998] and many words are ambiguous [Cui et ...
... on whether the user can raise queries properly describing the information need to search engines. Writing queries is never easy, partially because queries are typically expressed in a very small number of words (two or three words on average) [Jansen et al. 1998] and many words are ambiguous [Cui et ...
parallel mining of minimal sample unique itemsets - APT
... communication overheads) causing larger tasks to wait last for processing. In such cases the remaining large tasks may not be able to fully utilize the system and thus result in load imbalance. An optimization method for facilitating load balancing is described and tested with parallel SUDA2. This m ...
... communication overheads) causing larger tasks to wait last for processing. In such cases the remaining large tasks may not be able to fully utilize the system and thus result in load imbalance. An optimization method for facilitating load balancing is described and tested with parallel SUDA2. This m ...
new methods for mining sequential and time series data
... the basis of the requirements of the domain. These techniques include association rules mining, classification, cluster analysis and outlier detection. The availability of applications that produce massive amounts of spatial, spatio-temporal (ST) and time series data (TSD) is the rationale for devel ...
... the basis of the requirements of the domain. These techniques include association rules mining, classification, cluster analysis and outlier detection. The availability of applications that produce massive amounts of spatial, spatio-temporal (ST) and time series data (TSD) is the rationale for devel ...
The Algorithms of Updating Sequential Patterns
... But few researchers study the incremental updating problem of sequence mining. Several efficient algorithms for maintaining sequential patterns have been developed [12,13]. Nevertheless, the problem of maintaining sequential patterns is much more complicated than maintaining associations rules, beca ...
... But few researchers study the incremental updating problem of sequence mining. Several efficient algorithms for maintaining sequential patterns have been developed [12,13]. Nevertheless, the problem of maintaining sequential patterns is much more complicated than maintaining associations rules, beca ...
SCALABLE MINING ON EMERGING ARCHITECTURES
... processors to mine for exact global patterns in terascale distributed data sets. We provide a 10-fold improvement to the existing state of the art in distributed mining. Second, we leverage the improved computational throughput of emerging CMPs to provide nearly-linear scale-ups for shared-memory p ...
... processors to mine for exact global patterns in terascale distributed data sets. We provide a 10-fold improvement to the existing state of the art in distributed mining. Second, we leverage the improved computational throughput of emerging CMPs to provide nearly-linear scale-ups for shared-memory p ...
Role Mining for Engineering and Optimizing Role Based Access
... for the “goodness” of an RBAC system. This is especially important for the setting of optimizing an RBAC system. Such a measure is also critical for evaluating and comparing the effectiveness of different role mining approaches. In [16], the evaluation approach is to first randomly generate a set of ...
... for the “goodness” of an RBAC system. This is especially important for the setting of optimizing an RBAC system. Such a measure is also critical for evaluating and comparing the effectiveness of different role mining approaches. In [16], the evaluation approach is to first randomly generate a set of ...
S2MP: Similarity Measure for Sequential Patterns
... but these measures are not relevant in the case of complex sequences composed of sets of items, as is the case of sequential patterns. In this paper, we propose a new similarity measure taking the characteristics of sequential patterns into account. S 2 M P is an adjustable measure depending on the ...
... but these measures are not relevant in the case of complex sequences composed of sets of items, as is the case of sequential patterns. In this paper, we propose a new similarity measure taking the characteristics of sequential patterns into account. S 2 M P is an adjustable measure depending on the ...
Partition Incremental Discretization
... to localized regions of the instance space. Global methods such as binning are applied before the learning process to the whole dataset. In static methods attributes are discretized independently of each other, while dynamic methods take into account the interdependencies between them. Note that in ...
... to localized regions of the instance space. Global methods such as binning are applied before the learning process to the whole dataset. In static methods attributes are discretized independently of each other, while dynamic methods take into account the interdependencies between them. Note that in ...
DISSERTATION
... reduction methods) are two techniques that aim at solving these problems by reducing the number of features and thus the dimensionality of the data. In the last years, several studies have focused on improving feature selection and dimensionality reduction techniques and substantial progress has bee ...
... reduction methods) are two techniques that aim at solving these problems by reducing the number of features and thus the dimensionality of the data. In the last years, several studies have focused on improving feature selection and dimensionality reduction techniques and substantial progress has bee ...
