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The “big elephant in the room” in the ongoing CEP dialog is that most of the current (CEP) software on the market is not capable of machine learning and statistical analysis of dynamic real-time situations. Software vendors have been promoting and selling business process automation solutions and calling this approach “CEP” when, in fact, nothing is new. There is certainly no “technology leap” in these systems, as sold today.
- First, event management is primarily about the identification and generation of business events from the ambient events. Similar to what Carole-Ann and I had written in previous posts.- Second, IBM wants to introduce high level EPLs to express the logic for that processing that are business-centric, something very similar to what Business Rules Languages and approaches are in the business rules management area.
- leave anything related to transport, communication to other layers- use this revised CEP to express and execute event-relevant logic, the purpose of which is to translate the ambient events into relevant business events- have these business events trigger business processes (however lightweight you want to make them)- have these business processes invoke decision services implemented through decision management to decide what they should be doing at every step- have the business processes invoke action services to execute the actions decided by the decision services- all the while generating business events or ambient events- etc.
Discovering patterns with great significance is an important problem in data mining discipline. An episode is defined to be a partially ordered set of events for consecutive and fixed-time intervals in a sequence. Most of previous studies on episodes consider only frequent episodes in a sequence of events (called simple sequence). In real world, we may find a set of events at each time slot in terms of various intervals (hours, days, weeks, etc.). We refer to such sequences as complex sequences. Mining frequent episodes in complex sequences has more extensive applications than that in simple sequences. In this paper, we discuss the problem on mining frequent episodes in a complex sequence. We extend previous algorithm MINEPI to MINEPI+ for episode mining from complex sequences. Furthermore, a memory-anchored algorithm called EMMA is introduced for the mining task. Experimental evaluation on both real-world and synthetic data sets shows that EMMA is more efficient than MINEPI+.
Jeffrey Sachs 15.1.2024
Only an exceptional president could resist the endless war-profiteering of this mammoth war machine; alas, Biden doesn’t even try.
Led by Minister Robert Habeck (the Greens) the German Federal Ministry for Economic Affairs and Climate Action is putting the parliament’s right to have a say in major military procurements into question, according to an expertise presented by Habeck’s advisors on Tuesday. The Green-led ministry is hoping to save time in the arms-buildup, by curtailing democratic processes. Last April, Defense Minister Boris Pistorius (SPD) declared the “time factor” to be the essential criterion in his reform of military procurement. In the current procurement reform, transatlantic voices are gaining the upper hand, favoring a rapid upgrading in the Bundeswehr’s capabilities, at the expense of the promotion of an independent European arms industry. This is provoking new tensions with France. Germany is conducting its arms buildup largely within the NATO framework. The military alliance has recently confirmed its armament policy at its Vilnius summit. The NATO members agreed on further measures allowing them “to respond faster and at a greater scale.”
Y. Ahn, S. Han, H. Kwak, S. Moon, and H. Jeong. Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, Genova, Italy, (9-13 July 2007)
V. Alfi, G. Parisi, and L. Pietronero. Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, Genova, Italy, (9-13 July 2007)
V. Alfi, G. Parisi, and L. Pietronero. Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, Genova, Italy, (9-13 July 2007)
V. Alfi, A. Petri, and L. Pietronero. Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, Genova, Italy, (9-13 July 2007)