Creating precise soft computing techniques for estimating groundwater levels (GWL) to improve water resource scheduling and administration is crucial. Machine Learning (ML) algorithms have significantly improved GWL p...
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this paper presents a neural approach for modeling lexical vagueness. A three layers self-organizing feature maps is used to modelingthe lexical vagueness with semantic context. the experimental results show that our...
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ISBN:
(纸本)9781467308946;9788994364261
this paper presents a neural approach for modeling lexical vagueness. A three layers self-organizing feature maps is used to modelingthe lexical vagueness with semantic context. the experimental results show that our approach is more appropriate than traditional vagueness modeling approaches.
In pervasive environments, presence-based application development via Presence Management Systems (PMSs) is a key factor to optimise the management of communication channels, driving productivity increase. Solutions f...
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ISBN:
(纸本)9783642242786
In pervasive environments, presence-based application development via Presence Management Systems (PMSs) is a key factor to optimise the management of communication channels, driving productivity increase. Solutions for presence management should satisfy the interoperability requirements, in turn providing context-centric presence analysis and privacy management. In order to push PMSs towards flexible, open and context-aware presence management, we propose some adaptation of two extensions to standard XML-based XMPP for message exchange in online communication systems. the contribution allows for more complex specification and management of nested group and privacy lists, where semantic technologies are used to map all messages into RDF vocabularies and pave the way for a broader semantic integration of heterogeneous and distributed presence information sources in the standard PMSs framework.
Web search behavior is being diversified. And the diversification of web search behavior makes query both sporadic and non-sequential. In this case, it is difficult to understand why and how users search any informati...
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ISBN:
(纸本)9783642242786
Web search behavior is being diversified. And the diversification of web search behavior makes query both sporadic and non-sequential. In this case, it is difficult to understand why and how users search any information. context of web search makes it possible to classify sporadic and non-sequential queries according to each interest. However, only the user him/herself can identify the context of web search behavior exactly. Hence, it is necessary to conduct a client-side research in which users are deeply engaged. the purpose of this research is to develop and apply the methodology that systematically examines the web search behavior and its context. To achieve this, (1) client-side log data is collected, then participants (2) clustered the queries based on context and (3) filled in a questionnaire as to each clustered queries. Also, interviews were conducted in each person. the finding of this study is that the features of UCQS are different from previous studies. Furthermore, we identified the flow of users' web search behavior.
this paper presents an approach for contextualizing an event-based decision support system for scheduling patient assessments in a hospital. To cope with unexpected delays, patient coordinators often pursue a worst ca...
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ISBN:
(纸本)9783642242786
this paper presents an approach for contextualizing an event-based decision support system for scheduling patient assessments in a hospital. To cope with unexpected delays, patient coordinators often pursue a worst case scenario when scheduling patient assessments, leading to an underutilization of human resources and equipment when the procedure went without complications. We present a context-based decision support system for patient planning that helps the patient coordinator with taking well-informed rescheduling decisions and anticipating changes in other patients' schedules. the system uses information and events produced by medical equipment. As these events can be non-deterministic, we demonstrate how our domain specific context model can be used to contextualize events to enhance their quality and ascertain their meaning.
the state forecasting of complex systems requires increasing the reliability of modeling results. the creation of a hybrid predictive model is needed to solve this task. the contextual information extracted from the s...
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this bird-of-a-feather session attempts to break interdisciplinary ground in the context of work content, workflow, and work context analysis in Digital Government. the authors argue that using and connecting multiple...
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this bird-of-a-feather session attempts to break interdisciplinary ground in the context of work content, workflow, and work context analysis in Digital Government. the authors argue that using and connecting multiple theories and disciplines might yield more robust results and deeper understanding of the Digital Government evolution than strictly disciplinary research.
Location-aware systems are mobile or spatially distributed computing systems, such as smart phones or sensor nodes in wireless sensor networks, enabled to react flexibly to changing environments. Due to severe restric...
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ISBN:
(纸本)9783642242786
Location-aware systems are mobile or spatially distributed computing systems, such as smart phones or sensor nodes in wireless sensor networks, enabled to react flexibly to changing environments. Due to severe restrictions of computational power on these platforms and real-time demands, most current solutions do not support advanced spatial reasoning. Qualitative Spatial Reasoning (QSR) and granularity are two mechanisms that have been suggested in order to make reasoning about spatial environments tractable. We propose an approach for combining these two techniques, so as to obtain a light-weight QSR mechanism, called partial order QSR (for brevity: PQSR), that is fast enough to allow application on small, low-cost computing devices. the key idea of PQSR, is to use a core fragment of typical QSR relations, which can be expressed with partial orders and their linearizations, and to additionally delimit reasoning about these relations with a size-based granularity mechanism.
the following paper is a proof-of-concept demonstration of a novel Bayesian framework for making inferences about individual students and the context in which they are learning. It has implications for both efforts to...
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ISBN:
(纸本)9781450348706
the following paper is a proof-of-concept demonstration of a novel Bayesian framework for making inferences about individual students and the context in which they are learning. It has implications for both efforts to automate personalized instruction and to probabilistically model educational context. By modelling students as Bayesian learners, individuals who weigh their prior belief against current circumstantial data to reach conclusions, it becomes possible to both generate estimates of performance and the impact of the educational environment in probabilistic terms. this framework is tested through a Bayesian algorithm that can be used to characterize student prior knowledge in course material and predict student performance. this is demonstrated using both simulated data. the algorithm generates estimates that behave qualitatively as expected on simulated data and predict student performance substantially better than chance. A discussion of the results and the conceptual benefits of the framework follow.
this position paper describes the role ontologies can play in Mobile context-Aware recommender systems. In a Semantic Web vision of recommender systems, the adoption of ontologies for modelingthe domain, the context ...
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