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.
Web Usage Mining is one of the important methods for web recommendations, but most of its studies are limited in using web server log, and its applications are limited in serving a particular web site. In this paper, based on mining the enterprise proxy log, we propose a novel WWW-oriented web recommendation system. Unlike other data sources, the enterprise proxy log is access history of visiting...
There are many clustering tasks which are closely related in the real world, e.g. clustering the Web pages of different universities. However, existing clustering approaches neglect the underlying relation and treat these clustering tasks either individually or simply together. In this paper, we will study a novel clustering paradigm, namely multi-task clustering, which performs multiple related clustering...
Since a large number of clustering algorithms exist, aggregating different clustered partitions into a single consolidated one to obtain better results has become an important problem. We propose a new algorithm for clustering ensemble based on spectral clustering. We also propose a criteria along with this algorithm, for the detection of cluster numbers. Our algorithm can determine the number of...
Presents an improved segmentation algorithm for flame image of rotary kiln burning zone, based on Gabor wavelet based texture coarseness and Fuzzy C-MEANS (FCM) cluster algorithm. At first, analyses the flame image in detail, divides it into four areas (flame area, material area, illuminated area, background area) by expert experiences and applies threshold segmentation in order to get rid of background...
Mining data streams has attracted much attention recently. Labeled samples needed by most current stream classification methods are more difficult and expensive to obtain than unlabeled ones. This paper proposed a semi-supervised learning algorithm - clustering-training to utilize the unlabeled samples. It uses clustering to select confidently unlabeled samples, and uses them to re-train the classifier...
Recently, the continuously arriving and evolving data stream has become a common phenomenon in many fields, such as sensor networks, Web click stream and Internet traffic flow. One of the most important mining tasks is clustering. Clustering has attracted extensive research by both the community of machine learning and data mining. Many stream clustering methods have been proposed. These methods have...
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.