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.
Multi-tenant storage management environments typically manage multiple enterprise accounts with heterogeneous storage footprints. Identifying and grouping accounts with similar storage footprints into clusters reduces account management overhead, and provides a framework for data-driven storage recommendation services. This paper describes a method for the clustering of accounts in multi-tenant storage...
Human action recognition is very important in human computer interaction. In this article, we present a new method of recognizing human actions by using Microsoft Kinect sensor, k-means clustering and Hidden Markov Models (HMMs). Kinect is able to generate human skeleton information from depth images, in addition, features representing specific body parts are generated from the skeleton information...
Text clustering is the major route for topic detection. The major shortcoming which the current algorithms always suffers is the high computing complexity and great time cost when the number of instance is too large. We introduce a new algorithm which cluster the text copra is two steps: in the C-process we divide the copra into some overlapping subsets using Canopy clustering; in the K-process we...
This paper proposes a hybrid algorithm based on improved LLE and adaptive k-means for visual codebook generation in tourism scene classification. Firstly, we construct the improved LLE algorithm to get lower dimensional and compressed image feature representations. Then we form the adaptive k-means clustering algorithm to generate the visual codebook. Finally, we use the visual codebook histogram...
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applied to address these two issues, including feature selection, instance selection, and clustering. Most existing methods either compromise computational complexity or prediction precision. Two novel, scalable memory-based CF...
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.