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A Comparison of Explicit and Implicit Graph Embedding Methods for Pattern Recognition [chapter]

Donatello Conte, Jean-Yves Ramel, Nicolas Sidère, Muhammad Muzzamil Luqman, Benoît Gaüzère, Jaume Gibert, Luc Brun, Mario Vento
<span title="">2013</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper we present a comparison of two implicit and three explicit state of the art graph embedding methodologies.  ...  expensive and efficient state of the art machine learning models of statistical pattern recognition.  ...  In this paper we present a comparison of two implicit and three explicit state of the art graph embedding methodologies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-38221-5_9">doi:10.1007/978-3-642-38221-5_9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pzp6r7hjgjbwrmbykpjapbz6t4">fatcat:pzp6r7hjgjbwrmbykpjapbz6t4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170925094638/https://hal.archives-ouvertes.fr/hal-00829226/document" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c5/ec/c5eca7edd3631e1d7f6ea8e403c60c33924a2f29.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-38221-5_9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Implicit and Explicit Graph Embedding: Comparison of Both Approaches on Chemoinformatics Applications [chapter]

Benoit Gaüzère, Makoto Hasegawa, Luc Brun, Salvatore Tabbone
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The second family is based on comparisons of bags of patterns extracted from graphs to be compared.  ...  Defining similarities or distances between graphs is one of the bases of the structural pattern recognition field.  ...  Acknowledgments The authors thanks Salim Jouili for providing the graph embedding code.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-34166-3_56">doi:10.1007/978-3-642-34166-3_56</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k4vomhhm6bfi7fj7el66pabdi4">fatcat:k4vomhhm6bfi7fj7el66pabdi4</a> </span>
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Improving Fuzzy Multilevel Graph Embedding through Feature Selection Technique [chapter]

Muhammad Muzzamil Luqman, Jean Yves Ramel, Josep Lladós
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper we take forward our work on explicit graph embedding and present an improvement to our earlier proposed method, named "fuzzy multilevel graph embedding -FMGE", through feature selection technique  ...  FMGE achieves the embedding of attributed graphs into low dimensional vector spaces by performing a multilevel analysis of graphs and extracting a set of global, structural and elementary level features  ...  Graph embedding is a natural outcome of parallel advancements in structural and statistical pattern recognition.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-34166-3_27">doi:10.1007/978-3-642-34166-3_27</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zxl3fcf775c2hm23vurc3yfqd4">fatcat:zxl3fcf775c2hm23vurc3yfqd4</a> </span>
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DeepEmo: Learning and Enriching Pattern-Based Emotion Representations [article]

Elvis Saravia, Hsien-Chi Toby Liu, Yi-Shin Chen
<span title="2018-04-24">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The patterns are then enriched with word embeddings and evaluated through several emotion recognition tasks.  ...  We propose a graph-based mechanism to extract rich-emotion bearing patterns, which fosters a deeper analysis of online emotional expressions, from a corpus.  ...  ., captures implicit and explicit emotional expressions).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1804.08847v1">arXiv:1804.08847v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rzdlxamvjnbyjhnnziw75ybs7u">fatcat:rzdlxamvjnbyjhnnziw75ybs7u</a> </span>
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Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering [article]

JianJian Cao and Xiameng Qin and Sanyuan Zhao and Jianbing Shen
<span title="2021-12-14">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Firstly, it not only builds graph for the image, but also constructs graph for the question in terms of both syntactic and embedding information.  ...  Next, we explore the intra-modality relationships by a dual-stage graph encoder and then present a bilateral cross-modality graph matching attention to infer the relationships between the image and the  ...  infer the explicit and implicit relations inside each graph.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.07270v1">arXiv:2112.07270v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oco2bjv4rrfpjfylwcmxa2pfky">fatcat:oco2bjv4rrfpjfylwcmxa2pfky</a> </span>
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Describing Unseen Classes by Exemplars: Zero-Shot Learning Using Grouped Simile Ensemble

Yang Long, Ling Shao
<span title="">2017</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wsjivbkuezdvxdnrhihbwjrxlu" style="color: black;">2017 IEEE Winter Conference on Applications of Computer Vision (WACV)</a> </i> &nbsp;
We provide an efficient scenario to annotate similes for two benchmark datasets, AwA and aPY. 2) We propose a graph-cut-based class clustering algorithm to effectively discover implicit attributes from  ...  However, existing methods are restricted to learning explicitly nameable attributes and cannot tell which attributes are more important to the recognition task.  ...  In comparison to existing methods, our method adopts the advantages of using embedding approaches that can effectively map visual features to the semantic spaces.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/wacv.2017.106">doi:10.1109/wacv.2017.106</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/wacv/LongS17.html">dblp:conf/wacv/LongS17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ssttl2prmzaiji7l4xd6ld7xk4">fatcat:ssttl2prmzaiji7l4xd6ld7xk4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719195937/https://ueaeprints.uea.ac.uk/62138/1/egpaper_final_2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a4/fc/a4fcb57554c84572d900659d84df8e6de151a264.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/wacv.2017.106"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Stochastic Graphlet Embedding [article]

Anjan Dutta, Hichem Sahbi
<span title="2017-02-17">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
However, these non-vectorial graph data cannot be straightforwardly plugged into off-the-shelf machine learning algorithms without a preliminary step of -- explicit/implicit -- graph vectorization and  ...  Graph-based methods are known to be successful in many machine learning and pattern classification tasks.  ...  ACKNOWLEDGMENTS Anjan Dutta was a postdoctoral researcher at the Télécom ParisTech in Paris when some of the works described in this paper were done. He would like to thank Prof.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1702.00156v2">arXiv:1702.00156v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xcxlbxcm2nb33fptt4jbbvv2na">fatcat:xcxlbxcm2nb33fptt4jbbvv2na</a> </span>
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AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba [article]

Ningyu Zhang, Qianghuai Jia, Shumin Deng, Xiang Chen, Hongbin Ye, Hui Chen, Huaixiao Tou, Gang Huang, Zhao Wang, Nengwei Hua, Huajun Chen
<span title="2021-12-07">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
novel low-resource phrase mining approach, c) updating the graph dynamically via a concept distribution estimation method based on implicit and explicit user behaviors.  ...  Conceptual graphs, which is a particular type of Knowledge Graphs, play an essential role in semantic search.  ...  Finally, we propose a novel concept distribution estimation method based on implicit and explicit user behaviors to tackle the taxonomy evolution challenges.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2106.01686v2">arXiv:2106.01686v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ahae7tr745bargo5c2ipxohorq">fatcat:ahae7tr745bargo5c2ipxohorq</a> </span>
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Contrastive Object Detection Using Knowledge Graph Embeddings [article]

Christopher Lang, Alexander Braun, Abhinav Valada
<span title="2021-12-21">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Object recognition for the most part has been approached as a one-hot problem that treats classes to be discrete and unrelated.  ...  In this work, we compare the error statistics of the class embeddings learned from a one-hot approach with semantically structured embeddings from natural language processing or knowledge graphs that are  ...  Explicit vs Implicit background representation the inherent semantic structure of the embeddings.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.11366v1">arXiv:2112.11366v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rimn6wnkl5f7jegx767akkbef4">fatcat:rimn6wnkl5f7jegx767akkbef4</a> </span>
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Hybrid Knowledge Routed Modules for Large-scale Object Detection [article]

Chenhan Jiang, Hang Xu, Xiangdan Liang, Liang Lin
<span title="2018-10-30">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
By functioning over a region-to-region graph, both modules can be individualized and adapted to coordinate with visual patterns in each image, guided by specific knowledge forms.  ...  The dominant object detection approaches treat the recognition of each region separately and overlook crucial semantic correlations between objects in one scene.  ...  In these works, a fixed graph is usually considered, while our module's graph has adaptive region-to-region edges which can be embedded with any kinds of external knowledge. Few-shot Recognition.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1810.12681v1">arXiv:1810.12681v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kgt4fdox35b5tew22mf6szyppy">fatcat:kgt4fdox35b5tew22mf6szyppy</a> </span>
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A Survey of Implicit Discourse Relation Recognition [article]

Wei Xiang, Bang Wang
<span title="2022-03-06">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The task of implicit discourse relation recognition (IDRR) is to detect implicit relation and classify its sense between two text segments without a connective.  ...  We also present performance comparisons for those solutions experimented on a public corpus with standard data processing procedures.  ...  ACKNOWLEDGMENTS This work is supported in part by National Natural Science Foundation of China (Grant No: 62172167). The corresponding author is Bang Wang.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2203.02982v1">arXiv:2203.02982v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ubublxw2fnfdpexgw4jslj76tm">fatcat:ubublxw2fnfdpexgw4jslj76tm</a> </span>
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Graph Kernels based on High Order Graphlet Parsing and Hashing [article]

Anjan Dutta, Hichem Sahbi
<span title="2018-02-28">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
However, these non-vectorial graph data cannot be straightforwardly plugged into off-the-shelf machine learning algorithms without a preliminary step of -- explicit/implicit -- graph vectorization and  ...  Graph-based methods are known to be successful in many machine learning and pattern classification tasks.  ...  Anjan Dutta was with Télécom ParisTech when most of the work was done (under the MLVIS project) and part of the paper was written.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1803.00425v1">arXiv:1803.00425v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/b7i5aubyivcanmt7bdxcrclumu">fatcat:b7i5aubyivcanmt7bdxcrclumu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200902100257/https://arxiv.org/pdf/1803.00425v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/61/23/6123053386265c6c13067623430225fa2e6449f3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1803.00425v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Survey [article]

Yuecai Zhu, Fuyuan Lyu, Chengming Hu, Xi Chen, Xue Liu
<span title="2022-03-27">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
However, the temporal information embedded in the dynamic graphs brings new challenges in analyzing and deploying them.  ...  Events staleness, temporal information learning and explicit time dimension usage are some example challenges in dynamic graph learning.  ...  Explicit Time Learning Model is capable of periodicity recognition and vector clock recognition, for which Implicit Time Learning Model is incapable.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2203.10480v2">arXiv:2203.10480v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tf7n73rhtbbcpptbn6lyvhcew4">fatcat:tf7n73rhtbbcpptbn6lyvhcew4</a> </span>
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CARER: Contextualized Affect Representations for Emotion Recognition

Elvis Saravia, Hsien-Chi Toby Liu, Yen-Hao Huang, Junlin Wu, Yi-Shin Chen
<span title="">2018</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/u3ideoxy4fghvbsstiknuweth4" style="color: black;">Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</a> </i> &nbsp;
The pattern-based representations are further enriched with word embeddings and evaluated through several emotion recognition tasks.  ...  Our experimental results demonstrate that the proposed method outperforms state-of-the-art techniques on emotion recognition tasks.  ...  Acknowledgements This research was supported by the Ministry of Science and Technology (#106-2221-E-007-115-MY2 and #106-3114-E-007-013).  ... 
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User identification approach based on simple gestures

Jože Guna, Emilija Stojmenova, Artur Lugmayr, Iztok Humar, Matevž Pogačnik
<span title="2013-08-16">2013</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7inqmh346zfjjizjyieh7ijtma" style="color: black;">Multimedia tools and applications</a> </i> &nbsp;
For reference with other related systems, explicit and well defined identification gestures were used.  ...  User evaluation study results show that our algorithm ensures nearly 100% recognition accuracy when using explicit identification signature gestures and between 88% and 77% recognition accuracy when the  ...  Acknowledgements The operation that led to this paper is partially financed by the European Union, European Social Fund and the Slovenian research Agency, grant No. P2-0246.  ... 
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20120722060722/http://www.ht.sfc.keio.ac.jp:80/~hxt/pub/pervasive2012/Pervasive/workshops/same-5-guna.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/10/05/1005542c1823838b8b563d8e47e354bd3f9950a2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11042-013-1635-1"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>
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