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3,048
Events, Causality and Symmetry
, 2008
"... The article discusses causal models, such as Petri nets and event structures, how they have been rediscovered in a wide variety of recent applications, and why they are fundamental to computer science. A discussion of their present limitations leads to their extension with symmetry. The consequences ..."
Abstract
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Cited by 6 (2 self)
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The article discusses causal models, such as Petri nets and event structures, how they have been rediscovered in a wide variety of recent applications, and why they are fundamental to computer science. A discussion of their present limitations leads to their extension with symmetry
Minimally Supervised Event Causality Identification
"... This paper develops a minimally supervised approach, based on focused distributional similarity methods and discourse connectives, for identifying of causality relations between events in context. While it has been shown that distributional similarity can help identifying causality, we observe that ..."
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This paper develops a minimally supervised approach, based on focused distributional similarity methods and discourse connectives, for identifying of causality relations between events in context. While it has been shown that distributional similarity can help identifying causality, we observe
EMNLP’11 Minimally Supervised Event Causality Identification
"... This paper develops a minimally supervised approach, based on focused distributional sim-ilarity methods and discourse connectives, for identifying of causality relations between events in context. While it has been shown that distributional similarity can help identify-ing causality, we observe tha ..."
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This paper develops a minimally supervised approach, based on focused distributional sim-ilarity methods and discourse connectives, for identifying of causality relations between events in context. While it has been shown that distributional similarity can help identify-ing causality, we observe
Virtual time and global states of distributed systems.
- Proc. Workshop on Parallel and Distributed Algorithms,
, 1989
"... Abstract A distributed system can be characterized by the fact that the global state is distributed and that a common time base does not exist. However, the notion of time is an important concept in every day life of our decentralized \ r eal world" and helps to solve problems like getting a c ..."
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Cited by 744 (5 self)
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consistent population census or determining the potential causality between events. We argue that a linearly ordered structure of time is not (always) adequate for distributed systems and propose a generalized non-standard m o del of time which consists of vectors of clocks. These clock-vectors are p
Reliable Communication in the Presence of Failures
- ACM Transactions on Computer Systems
, 1987
"... The design and correctness of a communication facility for a distributed computer system are reported on. The facility provides support for fault-tolerant process groups in the form of a family of reliable multicast protocols that can be used in both local- and wide-area networks. These protocols at ..."
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Cited by 546 (18 self)
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attain high levels of concurrency, while respecting application-specific delivery ordering constraints, and have varying cost and performance that depend on the degree of ordering desired. In particular, a protocol that enforces causal delivery orderings is introduced and shown to be a valuable
Core affect and the psychological construction of emotion
- Psychological Review
"... At the heart of emotion, mood, and any other emotionally charged event are states experienced as simply feeling good or bad, energized or enervated. These states—called core affect—influence reflexes, perception, cognition, and behavior and are influenced by many causes internal and external, but pe ..."
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Cited by 448 (0 self)
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At the heart of emotion, mood, and any other emotionally charged event are states experienced as simply feeling good or bad, energized or enervated. These states—called core affect—influence reflexes, perception, cognition, and behavior and are influenced by many causes internal and external
doi:10.1093/comjnl/bxh000 Events, Causality and Symmetry
"... The article discusses causal models, such as Petri nets and event structures, how they have been rediscovered in a wide variety of recent applications, and why they are fundamental to computer science. A discussion of their present limitations leads to their extension with symmetry. The consequences ..."
Abstract
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The article discusses causal models, such as Petri nets and event structures, how they have been rediscovered in a wide variety of recent applications, and why they are fundamental to computer science. A discussion of their present limitations leads to their extension with symmetry
Domino: Understanding Wide-Area, Asynchronous Event Causality in Web Applications
"... Abstract In a modern web application, a single high-level action like a mouse click triggers a flurry of asynchronous events on the client browser and remote web servers. We introduce Domino, a new tool which automatically captures and analyzes end-to-end, asynchronous causal relationship of events ..."
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Abstract In a modern web application, a single high-level action like a mouse click triggers a flurry of asynchronous events on the client browser and remote web servers. We introduce Domino, a new tool which automatically captures and analyzes end-to-end, asynchronous causal relationship
Toward future scenario generation: extracting event causality exploiting semantic relation, context, and association features. In:
, 2014
"... Abstract We propose a supervised method of extracting event causalities like conduct slash-and-burn agriculture→exacerbate desertification from the web using semantic relation (between nouns), context, and association features. Experiments show that our method outperforms baselines that are based o ..."
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Cited by 2 (1 self)
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Abstract We propose a supervised method of extracting event causalities like conduct slash-and-burn agriculture→exacerbate desertification from the web using semantic relation (between nouns), context, and association features. Experiments show that our method outperforms baselines that are based
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