The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an administrator. Often administrators must then manually investigate events to figure out the source of a problem. Stream processing engines (SPEs) are general purpose data management systems for monitoring applications. They provide...
Automatic indexing of music by instruments and their types is a challenging problem, especially when multiple instruments are playing at the same time. We have built a database containing more than one million of music instrument sounds, each described by a large number o features including standard MPEG7 audio descriptors, features for speech recognition, and many new audio features developed by...
In this paper a new algorithm, called CStar, for document clustering is presented. This algorithm improves recently developed algorithms like generalized star (GStar) and ACONS algorithms, originally proposed for reducing some drawbacks presented in previous Star-like algorithms.The CStar algorithm uses the condensed star-shaped sub-graph concept defined by ACONS, but defines a new heuristic that...
Several marketing problems involve prediction of customer purchase behavior and forecasting future preferences. We consider predictive modeling of large scale, bi-modal or multimodal temporal marketing data, for instance, datasets consisting of customer spending behavior over time. Such datasets are characterized by variability in purchase patterns across different customer subgroups and shifting...
The theoretical relationship between association rules and machine learning techniques needs to be studied in more depth. This article studies the use of clustering as a model for association rule mining. The clustering model is exploited to bound and estimate association rule support and confidence. We first study the efficient computation of the clustering model with K-means; we show the sufficient...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.