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.
Frequent pattern mining discovers associations among different items in large sets of data. In many real-world applications, the presence of an object or a characteristic cannot be given exactly all the time. Instead, they can be better expressed in terms of probability and such data is called uncertain data. Mining frequent patterns from uncertain data is challenging due to presence of existential...
Clustering analysis is one of the most commonly used data processing algorithm. In this era of data explosion, clustering large volume of data is very challenging. If the data is heterogeneous, it brings more challenges. K-Prototype is an algorithm which aims at clustering mixed dataset which contains numerical as well as categorical data. This algorithm does not distinguish between nominal data and...
Organization of transactional data is one of the important steps in Knowledge Discovery. Compact Pattern Tree (CPTree) organization of the data is apt for the FP-Tree, CAN-Tree, CATS-Tree etc., Construction of CPTree has been dealt within two phase method. This paper exploits the transactional data representation in a structured form using one of the data structures for subsequent representation of...
Most of the real-world data is gathered locally, organized regionally leading to distributed environment. The analysis of such data will assist decision makers for promoting their business. Most of the data mining strategies are multi-pass techniques employed for mining and discovering the knowledge. Hence, the paper focuses on developing two pass data mining constructs to handle uncertain data. One...
Temporal association rules are largely different from traditional association rules by the fact that temporal association rules attempt to model temporal relationships in the data. Effective gain in any business is possible to achieve due to the adaptive knowledge which demands customized rules for specific conditions. Several parallel algorithms are useful to extract frequent patterns from large...
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.