In professional environments which are characterized by a domain (Medicine, Law, etc.), information retrieval systems must be able to process precise queries, mostly because of the...
The usage of descriptive data mining methods for predictive purposes is a recent trend in data mining research. It is well motivated by the understandability of learned models, the...
Abstract. The content of most Web pages is dynamically derived from an underlying relational database. Thus, the success of the Semantic Web hinges on enabling access to relational...
Syed Hamid Tirmizi, Juan Sequeda, Daniel P. Mirank...
The paper presents a novel method for compressing large database workloads for purpose of autonomic, continuous index selection. The compressed workload contains a small subset of ...
We consider the problem of data-stream classification, introducing a stream-classification algorithm, Dynamic Streaming Random Forests, that is able to handle evolving data streams...
Hanady Abdulsalam, David B. Skillicorn, Patrick Ma...
Abstract. We present a method based on clustering techniques to detect concept drift or novelty in a knowledge base expressed in Description Logics. The method exploits an effectiv...
The query performance for tracing tags depends upon the distribution of tag trajectories in the data space. We examine a more efficient representation of tag trajectories by means ...
Multiple target tracking (MTT) is a well-studied technique in the field of radar technology, which associates anonymized measurements with the appropriate object trajectories. This...
Nikolay Vyahhi, Spiridon Bakiras, Panos Kalnis, Ga...
There is an extensive literature on data mining techniques, including several applications of these techniques in the e-commerce setting. However, all previous approaches require t...
In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells' values. The cosine transform is known to have...