Rules in an Open System: The REACH Rule System

Branding, Holger; Buchmann, Alejandro; Kudrass, Thomas; Zimmermann, Jürgen

doi:10.1007/978-1-4471-3225-7_7

Cited by 53 publications

(21 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The recent context is the context most likely to be used in a real-time environment where sensors are read periodically. In the chronicle context, event As mentioned in Branding et al 1993 there is a trend towards modeling composite events using more complex condition parts. Primitive e v ents are used to trigger rules and the condition part of such a rule queries the event history to determine whether its action is to be executed.…”

Section: Rulesmentioning

confidence: 99%

“…There is a distinction drawn between when a rule is red and when it is executed Branding et al 1993. A rule is red when its corresponding event is triggered.…”

Section: Rulesmentioning

confidence: 99%

“…The detached mode can be further separated into causally independent in which the triggered transaction is executed regardless of whether the triggering transaction commits or aborts, and causally dependent in which the triggering transaction must commit before the triggered transaction can commit or else the triggered transaction is aborted. Branding et al 1993 state that a system which i n teracts with the real world, as real-time systems always do, is likely to have side e ects that are irreversible if the transaction should abort. Therefore two additional coupling modes are presented.…”

Section: Execution Semanticsmentioning

confidence: 99%

See 2 more Smart Citations

Real-Time and Active Databases: A Survey

Eriksson

1998

Active, Real-Time, and Temporal Database Systems

View full text Add to dashboard Cite

Abstract. Active real-time databases have emerged as a research area in which concepts of active databases and real-time databases are combined into a real-time database with reactive behavior. However, this marriage is not free from complications. The main problem is that timeliness, i.e., predictability and e ciency, is of paramount importance in real-time databases, while reactive behavior may add to the unpredictability of the database. This survey addresses reactive behavior and timing constraints from a database perspective. Results of both real-time databases and active databases that have impact on active real-time databases are discussed, as well as projects which h a v e done research o n active real-time databases.

show abstract

Section: Rulesmentioning

confidence: 99%

“…There is a distinction drawn between when a rule is red and when it is executed Branding et al 1993. A rule is red when its corresponding event is triggered.…”

Section: Rulesmentioning

confidence: 99%

Section: Execution Semanticsmentioning

confidence: 99%

See 1 more Smart Citation

Real-Time and Active Databases: A Survey

Eriksson

1998

Active, Real-Time, and Temporal Database Systems

View full text Add to dashboard Cite

show abstract

“…Though the temporal and spatial that support a unified view of both these attributes in the case of real world events. Composite event detection using event templates has also been proposed in several papers [3], [5], [15].…”

Section: Related Workmentioning

confidence: 99%

Representation and processing of information related to real world events

Nagargadde

Sridhar

Ramamritham

2007

Knowledge-Based Systems

View full text Add to dashboard Cite

Event based analysis plays an important role in reducing the latency of information delivery in an event driven world. Also, the perception of an 'event' by a user is at a higher level (a meta event), and would involve the analysis of several less complex or lower order events (basic events) in order to convey meaningful information. This is especially true of real world events and it is often necessary to completely capture the attributes of events and the relationships between them, so that the process of retrieval of event related information is efficient. In this paper, we discuss a formal system for representing and analyzing real world events to address these issues. The event representation discussed in this paper accounts for three important event attributes, namely, time, space, and label. We introduce the notion of sequence templates that appears natural for capturing event related semantics. It can also help in semantically analyzing user queries. To harness this potential, we present a formal structure to represent the queries related to real world events as well as an approach to semantically analyze a user query, and collate event related information to be dispatched to the user. Finally, we discuss the design and implementation of the Query-Event Analysis System (QEAS), which is an integrated system to (a) identify a best-matching sequence template(s) given a user query; (b) derive the meta-events based on the selected sequence templates; and (c) and use the meta-event information to answer the user query.

show abstract

“…This creates an additional constraint on how abnormality detection algorithms may be designed. While event detection and anomaly detection are important problems in the data mining community [4,6,15,17], these models do not address the problem in the context of predicting rare anomalies in the presence of many spurious (but similar) patterns. In order to achieve the specificities in abnormality detection, we will utilize a supervised approach in which the abnormality detection process learns from the data stream.…”

Section: Introductionmentioning

confidence: 99%

On Abnormality Detection in Spuriously Populated Data Streams

Aggarwal¹

2005

Proceedings of the 2005 SIAM International Conference on Data Mining

View full text Add to dashboard Cite

In recent years, advances in hardware technology have made it increasingly easy to collect large amounts of multidimensional data in an automated way. Such databases continuously grow over time, and are referred to as data streams. The behavior of such streams is sensitive to the underlying events which create the stream. In many applications, it is useful to predict abnormal events in the stream in a fast and online fashion. This is often a difficult goal in a fast data stream because of the time criticality of the detection process. Furthermore, the rare events may often be embedded with other spurious abnormalities, which affect the stream in similar ways. Therefore, it is necessary to be able to distinguish between different kinds of events in order to create a credible detection system. This paper discusses a method for supervised abnormality detection from multi-dimensional data streams, so that high specificity of abnormality detection is achieved. We present empirical results illustrating the effectiveness of our method.

show abstract

Rules in an Open System: The REACH Rule System

Cited by 53 publications

References 1 publication

Real-Time and Active Databases: A Survey

Real-Time and Active Databases: A Survey

Representation and processing of information related to real world events

On Abnormality Detection in Spuriously Populated Data Streams

Contact Info

Product

Resources

About