2012/8

A distributed architecture for efficient parallelization and computation of knowledge-based temporal abstractions

Asaf Shabtai, Yuval Shahar, Yuval Elovici

Journal of Intelligent Information Systems 39, 249-286, 2012

Today, data storage capabilities as well as computational power are rapidly increasing. On the one hand, this improvement makes it possible to generate and store a great amount of temporal (time-oriented) data for future query, analysis and discovery of new knowledge. On the other hand, systems and experts are encountering new problems in processing this increased amount of data. The rapid growth in stored time-oriented data necessitates the development of new methods for handling, processing, and interpreting large amounts of temporal data. One approach is to use an automatic summarization process based on predefined knowledge, such the Knowledge-Based Temporal-Abstraction (KBTA) method. This method enables one to summarize and reduce the amount of raw data by creating higher level interpretations based on predefined domain knowledge. Unfortunately, the task of temporal …