Association analysis and prediction are two major tasks in data mining, and they represent two foremost objectives: data exploration for understanding and model construction for prediction. Data mining is known as a process to convert raw data to useful information --knowledge. However, what do we do with the knowledge discovered from data? We will need knowledge to enable actions, such as prev...

1 Motivation Computer vision research has always been an active area of artificial intelligence. One of the basic goals of AI is to build agents that act intelligently or human-like. Reasoning, learning and language processing have contributed in reaching the goal of Turing test. Yet they provide only a partial solution as they lack the basic perceptual capabilities required to perceive and int...

due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. association rules mining is one of the data mining techniques to extract useful patterns in the form of association rules. one of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. hiding the as...

In this paper, we present a spatiotemporal co-location video pattern mining approach with application to robust action retrieval in YouTube videos. First, we introduce an attention shift scheme to detect and partition the focused human actions from YouTube videos, which is based upon the visual saliency [13] modeling together with both the face [35] and body [32] detectors. From the segmented s...

This paper describes the application of Latent Semantic Analysis to the term-document matrices that result from modeling an action game. Innovative solutions to address challenges like the definition of “words” and “documents” in the dynamic and complex domain of action games are proposed, and interesting, previously unknown semantic information is extracted.

Path recommendation plays an important role for learners to obtaining good action in e-learning environment. Without appropriate guiding service, learners might miss some resource and waste time. Therefore, how to provide visitors customized path becomes an important task for learners. To bridge the gap, this research uses sequential pattern mining for intelligent touring system to generate per...

Continuously improved business processes are a central success factor for companies. Yet, existing data analytics do not fully exploit the data generated during process execution. Particularly, they miss prescriptive techniques to transform analysis results into improvement actions. In this paper, we present the data-mining-driven concept of recommendation-based business process optimization on...

Data mining is one amid the core research areas in the field of computer science. Yet there is a knowledge data detection process helps the data mining to extract hidden information from the dataset there is a big scope of machine learning algorithms. Especially supervised machine learning algorithms gain extensive importance in data mining research. Boosting action is regularly helps the super...

This Paper presents a platform to mine epileptiform activity from Electroencephalograms (EEG) by combining the methodologies of Deterministic Finite Automata (DFA) and Knowledge Discovery in Data Mining (KDD) TV-Tree. Mining EEG patterns in human brain dynamics is complex yet necessary for identifying and predicting the transient events that occur before and during epileptic seizures. We believ...