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Semantic Networks and the Generation of Context
1975
International Joint Conference on Artificial Intelligence
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This paper outlines a representation of knowledge based on semantic networks and organized in terms of semantic axes and "scenarios". ...
Finally, an example is given to illustrate the representation and the context mechanism. 0. ...
The research described in this paper was partially supported by the Department of Communications of Canada and by the National Research Council of Canada. ...
dblp:conf/ijcai/MylopoulosCBS75
fatcat:6ptsvmhbjjdxveaxbnz4c57a34
Integrating visual and semantic contexts for topic network generation and word sense disambiguation
2009
Proceeding of the ACM International Conference on Image and Video Retrieval - CIVR '09
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First, a topic network is generated to characterize both the semantic similarity contexts and the visual similarity contexts between the image topics more sufficiently. ...
similarity contexts between their tags for topic network generation and word sense disambiguation. ...
Thus it is necessary to exploit both the inter-topic semantic contexts and the inter-topic visual contexts for generating a more precise topic network. ...
doi:10.1145/1646396.1646440
dblp:conf/civr/FanLSY09
fatcat:dvczr67ddnenjhp3w3reurc25u
SSN-NLP at SemEval-2020 Task 4: Text Classification and Generation on Common Sense Context Using Neural Networks
2020
Proceedings of the Fourteenth Workshop on Semantic Evaluation
unpublished
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For common sense validation with multi choice, we propose a stacking based approach to classify sentences that are more favourable in terms of common sense to the particular statement. ...
This paper describes the our approach to solve this challenge. ...
Conclusion We have implemented both traditional machine learning and deep learning approach for the task of classifying and generating sentences based on the context of common sense. ...
doi:10.18653/v1/2020.semeval-1.73
fatcat:forqpyw7o5btfdesygeq3bm55q
Using Graph Neural Networks for Program Termination
[article]
2022
arXiv
pre-print
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Overall, we designed and implemented classifiers for program termination based on Graph Convolutional Networks and Graph Attention Networks, as well as a semantic segmentation Graph Neural Network that ...
To further assist programmers in understanding and debugging nontermination bugs, we adapt the notions of attention and semantic segmentation, previously used for other application domains, to programs ...
semantic segmentation of termination using different network architectures and datasets. ...
arXiv:2207.14648v1
fatcat:nqnggy5rhjcqzngggguqwmqfsy
A two-tier semantic overlay network for P2P search
2007
2007 International Conference on Parallel and Distributed Systems
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Context data with the same semantics are grouped together into a one-dimensional semantic ring space in the upper-tier network. ...
Thus, all the nodes in the same semantic cluster know which node is responsible for storing context data triples they are looking for, and context queries can be efficiently routed to those nodes. ...
With this scheme, a peer can extract the semantics of its data triples more precisely without losing generality for context queries. ...
doi:10.1109/icpads.2007.4447754
dblp:conf/icpads/GuZP07
fatcat:r5llk4ajzjfyhnnxb4uohptop4
Image Caption Generation Using Multi-Level Semantic Context Information
2021
Symmetry
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Then a context information extraction network is used to extract the context information between the three different semantic layers, and an attention mechanism is introduced to improve the accuracy of ...
Experiments on the VRD and COCO datasets demonstrate that our proposed model can leverage the context information between semantic layers to improve the accuracy of those visual tasks generation. ...
Acknowledgments: The authors are grateful for the editor and reviewers for their constructive advice on the revision of the manuscript. ...
doi:10.3390/sym13071184
fatcat:xdxpibaf7rhyfjvfymt5jgl2fa
Context aware saliency map generation using semantic segmentation
[article]
2018
arXiv
pre-print
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Saliency map from semantic information is fused with color and contrast based saliency maps. The final saliency map is then generated. ...
Saliency map detection, as a method for detecting important regions of an image, is used in many applications such as image classification and recognition. ...
CNN produces both the semantic segmentation and the image context. Two other saliency maps are also generated based on color and contrast. ...
arXiv:1801.00256v2
fatcat:35xwt5ewmrcwfgvqmtdsljbhcy
An Ontology-Based P2P Network for Semantic Search
2009
International Journal of Grid and High Performance Computing
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Thus, all the nodes in the same semantic cluster know which node is responsible for storing context data triples they are looking for, and context queries can be efficiently routed to those nodes. ...
This is achieved by applying an ontology-based semantic clustering technique and dedicating part of node identifiers to correspond to their data semantics. ...
With this scheme, a peer can extract the semantics of its data triples more precisely without losing generality for context queries. ...
doi:10.4018/jghpc.2009070803
fatcat:awv5r2t66ba4dpkycjpv47646m
Semantic Context-Aware Image Style Transfer
2022
IEEE Transactions on Image Processing
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To achieve semantic context-aware style transfer, a hierarchical local-to-global network architecture, which contains two sub-networks including the local context network and the global context network ...
The former focuses on style transfer for each semantic context pair from the style image to the content image, and generates a local style transfer image storing the detailed style feature representations ...
Second, a novel hierarchical local-to-global network architecture is developed to enhance the stokes of local semantic context pairs and generate a globally consistent stylized result. ...
doi:10.1109/tip.2022.3149237
pmid:35143399
fatcat:3od3iqpyizfk5c6ssa6rsler5i
Bidirectional Temporal Context Fusion with Bi-Modal Semantic Features using a gating mechanism for Dense Video Captioning
2021
International Journal of Intelligent Computing and Information Sciences
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Secondly, we propose to explicitly extract bi-modal semantic concepts (nouns and verbs) from a detected event segment and equilibrate the contributions from the proposed event representation and the semantic ...
Most recent works attempted to make use of an encoder-decoder neural network framework which employs a 3D-CNN as an encoder for representing a detected event frames, and an RNN as a decoder for caption ...
Also learning bi-modal semantic features via attending on relevant verbs and nouns that describes the event content effectively, improves the captioning performance and is done while decoding each event ...
doi:10.21608/ijicis.2021.60216.1055
fatcat:o6is54gsjjcizohvh2jurn6xbm
Dynamic Context Correspondence Network for Semantic Alignment
[article]
2019
arXiv
pre-print
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We then develop a novel dynamic fusion strategy based on attention mechanism to weave the advantages of both local and context features by integrating semantic cues from multiple scales. ...
In this paper, we aim to incorporate global semantic context in a flexible manner to overcome the limitations of prior work that relies on local semantic representations. ...
Acknowledgments This work was supported in part by the NSFC Grant No.61703195 and the Shanghai NSF Grant No.18ZR1425100. ...
arXiv:1909.03444v1
fatcat:oxewn5s3a5ekbadmmd2f5pk464
Context Generation and Structuralization for Ambient Networks
2007
Proceedings of the 1st International ICST Conference on Autonomic Computing and Communication Systems
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The outcome of the system consists of a Web Service which exposes data and semantics of context information. ...
The input data of this system consists of information about sensors and an ontology describing their semantics. ...
The proposed solution bases on annotation of the context data with semantic information generated by the context source and is much more flexible. ...
doi:10.4108/icst.autonomics2007.2233
dblp:conf/autonomics/SzydloSZ07
fatcat:yvpuflr4hnbendm5xhg6sr6o3q
Deep Mask Memory Network with Semantic Dependency and Context Moment for Aspect Level Sentiment Classification
2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
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Deep memory networks often use location information between context word and aspect to generate the memory. ...
information of the aspect and the inter-aspect relation information into deep memory network. ...
Acknowledgments This work is partially supported by the National Natural Science Foundation of China (Grant no.61772568), the Key Areas Research and Development Program of Guangdong (Grant no.2018B010109007 ...
doi:10.24963/ijcai.2019/707
dblp:conf/ijcai/LinYL19
fatcat:zqxindc3hjeklhvaw7obuhnqh4
Automated context dissemination for autonomic collaborative networks through semantic subscription filter generation
2013
Journal of Network and Computer Applications
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We propose a context dissemination approach that automates the context exchange between elements. The approach enables the automated generation of semantic subscription filters. ...
The current manual management of services and applications in today's telecommunication networks is becoming increasingly complicated. ...
Related work In this section, we describe related work in the area of context retrieval and dissemination, its use of semantics and its application to network management challenges. ...
doi:10.1016/j.jnca.2013.01.011
fatcat:yxgc7iafgfgr3fjoehzsw3c4fu
CAGE: Context-Aware Grasping Engine
[article]
2020
arXiv
pre-print
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Our approach outperformed all baselines by statistically significant margins, producing new insights into the importance of balancing memorization and generalization of contexts for semantic grasping. ...
We introduce the Context-Aware Grasping Engine, which combines a novel semantic representation of grasp contexts with a neural network structure based on the Wide & Deep model, capable of capturing complex ...
ACKNOWLEDGMENTS This work is supported in part by NSF IIS 1564080, NSF GRFP DGE-1650044, and ONR N000141612835. ...
arXiv:1909.11142v3
fatcat:7rzvegkvqjha5pht5usvmqerri
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