Titlebook: New Frontiers in Mining Complex Patterns; 5th International Wo Annalisa Appice,Michelangelo Ceci,Zbigniew W. Ra? Conference proceedings 201

Inflamed

Profiling Human Behavior Through Multidimensional Latent Factor Modelinglar family of techniques addressing this problem is the Latent Factor Modeling which aims at identifying interesting features that determine human behavior. In most cases, latent factors are used to relate atomic features to each other: for example, semantically similar words in documents of a textu

過(guò)分自信

Multi-view Approach to Parkinson’s Disease Quality of Life Data Analysis postural instability are predominant, patients experience also non-motor symptoms, such as decline of cognitive abilities, behavioural problems, sleep disturbances, and other symptoms that greatly affect their quality of life. Careful management of patient’s condition is crucial to ensure the patie

GROSS

Subgraph Mining for Anomalous Pattern Discovery in Event Logsrded by the IT system against a process model (representing the normative behavior). However, most of the existing techniques are only able to identify low-level deviations, which provide a scarce support to investigate what actually happened when a process execution deviates from the specification.

intellect

原來(lái)

Mining Keystroke Timing Pattern for User Authenticationearest neighbor regression based feature ranking algorithm for anomaly detection. Our approach successfully handle drawbacks like outlier detection, scale variation and prevents overfitting. Apart from using existing keystroke timing features from the dataset like dwell time and flight time, other f

鳥(niǎo)籠

Ranking to Learn:ure (e.g., biological data and object recognition, among others), and compared against filter, embedded and wrappers methods. The results are remarkable in terms of accuracy, stability and low execution time.

radiograph

Bayesian Confirmation Measures in Rule-Based Classificationditional analysis comparing results on balanced/imbalanced and binary/multi-class problems highlights also ., ., and . as measures for sorting rules on binary imbalanced datasets. The obtained results can be used to devise new classifiers that optimize confirmation measures during model training.

微粒

Feature Clustering for Extreme Events Analysis, with Application to Extreme Stream-Flow Datailarly to the Apriori algorithm, which reduces drastically the number of subsets to be screened. Results on simulated and real data show that our method allows a fast recovery of a meaningful summary of the dependence structure of extremes.

易碎

Profiling Human Behavior Through Multidimensional Latent Factor Modelingt can be exploited in order to define fine-grain user profiles. These components can be, for instance, “what is being done”, “where”, “when” or “how”. We evaluated our approach in two application scenarios. A first test is performed on real data and it is aimed at semantically validate the model ide

IVORY

Multi-view Approach to Parkinson’s Disease Quality of Life Data Analysisns of medications changes that lead to the improvement or decline of patients’ quality of life. We identify groups of patients ordered in accordance to their quality of life assessment and find examples of therapy modifications which induce positive or negative change of patients’ symptoms. The resu