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Reasoning with temporal information in natural language text has attracted great attention due to its potential applications in summarization, question answering and other tasks. ... Much of the work done in this direction can be classified as -Annotation schemes for identification of events and time implicit in the text, linking the events using temporal relations and Temporal reasoning ... It supports inferencing with time in solving many NLP applications. ...doi:10.5120/100-209 fatcat:hrlouzt2onc6njhxr6uqydu2ym
Tractable reasoning via approximation Problems in logic are well-known to be hard to solve in the worst case. ... Our main goal is to define a semantically wellfounded logic for approximate reasoning, which is justifiable from the intuitive point of view, and to provide fast algorithms for dealing with it even when ... In this paper we address the problem of scalability in temporal reasoning by providing a collection of new algorithms for efficiently managing large sets of qualitative temporal relations. ...doi:10.1016/0004-3702(95)90010-1 fatcat:afhan6uvwffxzitrp7wnajfchm
We have considered the conceptual relations between different types of intelligence. ... semantic technology), collective intelligence and specific knowledge in the field, which is, according to the approach presented in this paper, the conceptual basis of Intelligent Systems in Economy ( ... Instead, if the agent has to build or to use sophisticated models of problem domain and to solve problems at different levels of abstraction, then it is necessary to use semantic networks. ...doaj:9252a770a574409ab0dd9f59dcb533b7 fatcat:hfff6a4znzbr3mb3oagvzzztue
Lecture Notes in Computer Science
Artificial intelligence is the field of computer science that tries to solve complex problems of realworld applications in a formal language. ... Areas of application are networks, for example computer networks, travel networks, cash flow between international enterprises and political interactions of states. ... Artificial intelligence is the field of computer science that tries to solve complex problems of realworld applications in a formal language. ...doi:10.1007/978-3-540-75666-8_1 fatcat:yuekwapvzfgehnkfazfafouz2i
“Constraint-based reasoning is used to solve a widespread field of problems. Some researchers had a certain task in mind and tried to find a method to solve that task efficiently. ... ISBN 3-540-55510-2 From the introduction: “Much of AI research is about problem solving strategies, for example, developing heuristic search algo- rithms, reasoning on representations of human knowledge ...
approaches of connecting people on the use (automatic) of operational knowledge to solve problems and make decisions based on intellectual cooperation. ... Few technologies have the big potential to review how we live, move, and work. Artificial intelligence (AI) is nowdays equivalent of electricity and the Internet. ... Instead, if the agent has to build or to use sophisticated models of problem domain and to solve problems at different levels of abstraction, then it is necessary to use semantic networks. ...doaj:f2f7f61bd4d14486bf1e85ef3f52706d fatcat:rwuckjbwbjagle7id67ocgtmzy
The next challenge in qualitative spatial and temporal reasoning is to develop calculi that deal with different aspects of space and time. ... In this paper we develop a procedure for reasoning about some of the largest known calculi, the Rectangle Algebra and the Block Algebra with about 10661 relations. ... It is one of the main challenges in the field of qualitative spatial and temporal reasoning to combine different calculi in order to represent more expressive spatial and temporal information. ...doi:10.1609/aaai.v24i1.7594 fatcat:zxmrcmbrurdqdousvsrvf2z6si
Judgements were based more on information about temporal relations, even though no guidance on the use of temporal relation information for causal inference was provided. ... Individual causal relations can always be understood as elements in a chain or network of unfolding causality, from a row of dominoes toppling and interlinked cogs in a machine to weather systems, disease ... It may be that it is more difficult to solve causal reasoning problems with this more indirect verbal mode of presentation. ...doi:10.1080/09541440500264861 fatcat:g7b5e52vtfcerdiuwhx4gzf3ba
Model-Based Reasoning (MBR) is one of the approaches that traditionally have tried to solve this problem thanks to its capacity for modelling and reasoning. ... First this paper proposes a set of basic requirements for the design of Knowledge-Based Systems that will help to solve the problem of temporal diagnosis for environments of high conceptual complexity. ... Acknowledgements We would like to thanks Dr. Palacios from the ICU service at Getafe Hospital (Madrid) for his indispensable collaboration and comments. ...doi:10.1016/j.eswa.2007.08.054 fatcat:imagckkmunbz7phjvb2c52eo34
Many applications -- from planning and scheduling to problems in molecular biology -- rely heavily on a temporal reasoning component. ... Taken together, the techniques we develop allow a temporal reasoning component to solve problems that are of practical size. ... Introduction Temporal reasoning is an essential part of many arti cial intelligence tasks. It is desirable, therefore, to develop a temporal reasoning component that is useful across applications. ...arXiv:cs/9601101v1 fatcat:2hst6jhfgbbqnhldpk2favojba
International Journal of Computer Science & Engineering Survey
Documentation of various Business and Human Resource (HR) applications involve Legal documents. Analysis and temporal reasoning of such documents is a demanding area of research. ... The resultant information resolves temporal expressions and deals with issues such as granularity, vagueness, and a reasoning mechanism which models the temporal constraint satisfaction network. ... Data from other sources helps to solve this problem. ...doi:10.5121/ijcses.2011.2103 fatcat:pud7n5nca5clrn7oqm4vtvkady
Specifically, it is demonstrated how the problem of determining path-consistency in a network of binary n-interval relations can be solved. ... A solution to the problem of representing and reasoning about incomplete temporal information of these kinds is forthcoming if a restricted class of non-convex intervals (called n-tntervals) is added to ... It was demonstrated that path consistency techniques can be applied to problem solving involving networks of n-interval relations. ...dblp:conf/ijcai/MorrisSK93 fatcat:crrrr4ivevfjvljij4e35jahye
In simpler domains of application we may not need to consider it a problem but it becomes important in more complex domains, such as ecological modelling. ... Summary: “We propose a symmetric definition of conditional in- dependence between sets of variables in possibility theory, and relate it to the notion of lack of interaction. ...
During the past decades, some subfields of Artificial Intelligence have been devoted to the study of temporal models and techniques to solve generic problems and towards their practical applications in ... This paper provides a non-exhaustive review of some of the efforts made in the field and our particular contributions in the development of temporal reasoning methods to partially solve some of these problems ... ACKNOWLEDGEMENTS We would like to thank Dr. Palacios at the ICU of the Getafe University Hospital (Madrid, Spain) for his fine contribution to this work. ...doi:10.1260/2040-2218.104.22.1685 fatcat:daz3senaqvgwjgo3o3ocfuxlhu
Section 4 shows how the knowledgebased temporal-abstraction method was reused to perform two different subtasks: spatial reasoning and temporal reasoning. ... We first show how we have applied that method to solve both the temporal-and spatial-abstraction tasks in the traffic-control domain. ... Acknowledgments This work has been supported by grants LM05305, LM05708, and LM06245 from the National Library of Medicine, and award IRI-9528444 from the National Science Foundation. ...doi:10.1007/bf01237938 fatcat:fnzcvqkgd5ep5d2fr5g555tyii
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