By Peter P. Chen, Leah Y. Wong
This quantity encompasses a choice of the papers offered through the First overseas ACM-L Workshop, which was once held in Tucson, Arizona, throughout the twenty fifth overseas convention on Conceptual Modeling, ER 2006.
Included during this state of the art survey are eleven revised complete papers, rigorously reviewed and chosen from the workshop shows. those are crowned off with four invited lectures and an introductory and motivational overview.
Taken as a complete, those papers hide almost the entire present considering in conceptual modeling research.
The workshop in query interested in bettering the basic knowing of the way to version continuous studying from previous reports and the way to seize wisdom from transitions among process states.
Active conceptual modeling is a continuing means of describing all elements of a site, its actions, and alterations from diverse views in accordance with our wisdom and understanding.
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Additional resources for Active Conceptual Modeling of Learning: Next Generation Learning-Base System Development
Different from the goals an agent intends to fulfill through an action, beliefs refer to what an agent believes prior to the action, and they form the background upon which an agent can choose to act in a particular way . We further classify beliefs into assumptions and hypotheses (see Fig. 8). A s s u m p tio n S R e a s o n S H y p o th e s is B e lie f G o a l Is [0 :m ] [0 :m ] re d u c e d to Fig. 8. Semantics of “Why” 3 Active Conceptual Modeling with Provenance Annotations As discussed in , a serious problem in today’s data modeling practices is that database design approaches have viewed data models as representing only a snapshot of the world and recommend ignoring variations of information as well as the causes and other details of those variations during data modeling.
In: Intl. Joint Conference on Work Activities Coordination and Collaboration (WACC) (1999) 16. : A meta-service for event notiﬁcation. In: CoopIS/DOA/ODBASE (1) (2004) 17. : Continual queries for internet scale event-driven information delivery. IEEE-TKDE 11(4) (1999) 18. : Continuously adaptive continuous queries over streams. In: ACM SIGMOD Conference (2002) 19. : Adaptive ﬁlters for continuous queries over distributed data streams. In: ACM SIGMOD (2003) 20. Paton, N. ): Active Rules in Database Systems.
Firstly, observe that in the events, conditions and actions we allow variables to be used. For example, Ep (EVp ) denotes that the event of the parent-trigger Ep has the (vector of) variable(s) EVp in its speciﬁcation; similarly, Cp1 (V Cp 1) denotes the query and the variables used in the ﬁrst condition of the parent trigger. We assume that the usual rules for safety  of the variables apply, in the sense that each variable that appears in a negative literal, must also appear in a positive literal, or have a ground value at the time of the invocation/evaluation of the corresponding (negated) predicate.
Active Conceptual Modeling of Learning: Next Generation Learning-Base System Development by Peter P. Chen, Leah Y. Wong