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News Graph: An Enhanced Knowledge Graph for News Recommendation

Danyang Liu, Ting Bai, Jianxun Lian, Xin Zhao, Guangzhong Sun, Ji-Rong Wen, Xing Xie
2019 International Conference on Information and Knowledge Management  
Thus we propose an enhanced knowledge graph called news graph.  ...  Knowledge graph, which contains rich knowledge facts and well structured relations, is an ideal auxiliary data source for alleviating the data sparsity issue and improving the explainability of recommender  ...  ACKNOWLEDGMENTS The authors would like to thank Microsoft News for providing technical support and data in the experiments, and Jiun-Hung Chen (Microsoft News) and Ying Qiao (Microsoft News) for their  ... 
dblp:conf/cikm/LiuBLZSWX19 fatcat:xuhlaan5ybgpjkx27aibssglfe

Semantic Knowledge Graphs for the News: A Review

Andreas L. Opdahl, Tareq Al-Moslmi, Duc-Tien Dang-Nguyen, Marc Gallofré Ocaña, Bjørnar Tessem, Csaba Veres
2022 ACM Computing Surveys  
Semantic knowledge graphs (KGs) is an established technique for integrating such heterogeneous information.  ...  This paper reviews the research on using semantic knowledge graphs for production, distribution, and consumption of news.  ...  ACKNOWLEDGMENTS CONFLICT OF INTEREST The authors are themselves involved in the News Angler project reported in [M46]. MAIN PAPERS  ... 
doi:10.1145/3543508 fatcat:l4lwafoyuncdpmc4qhj3xxekwa

Knowledge Graph Based Waveform Recommendation: A New Communication Waveform Design Paradigm [article]

Wei Huang, Tianfu Qi, Yundi Guan, Qihang Peng, Jun Wang
2022 arXiv   pre-print
In this paper, we investigate the waveform design from a novel perspective and propose a new waveform design paradigm with the knowledge graph (KG)-based intelligent recommendation system.  ...  To achieve this goal, we first build a communication waveform knowledge graph (CWKG) with a first-order neighbor node, for which both structured semantic knowledge and numerical parameters of a waveform  ...  We adopt an improved involution1D operator and multi-head selfattention to perform embedding representation enhancement (ERE) for feature extraction and fusion.  ... 
arXiv:2202.01926v1 fatcat:hjmbvg3sxnaqvomxvbtwlvyhea

The Graph-Based Behavior-Aware Recommendation for Interactive News [article]

Mingyuan Ma, Sen Na, Hongyu Wang, Congzhou Chen, Jin Xu
2021 arXiv   pre-print
First, we build an interaction behavior graph for multi-level and multi-category data.  ...  Further, although heterogeneous graphs have been applied in different areas, a proper way to construct a heterogeneous graph for interactive news data with an appropriate learning mechanism on it is still  ...  [37] used a knowledge graph to extract latent knowledge-level connections among news for having a more precise recommendation.  ... 
arXiv:1812.00002v2 fatcat:kwhugfvc4faapkesblicj5xfhe

Sparklis over PEGASE Knowledge Graph: A New Tool for Pharmacovigilance

Carlos Bobed, Laura Douze, Sébastien Ferré, Romaric Marcilly
2018 Figshare  
the way pharmacovigilance specialists perform search and exploration on their data.First, we have developed a knowledge graph that relies on the OntoADR ontology to semantically enrich the MedDRA terminology  ...  pharmacovigilance specialists experience several difficulties when searching and exploring their patient data despite the existence of standardized terminologies (MedDRA).In this paper, we present our approach to enhance  ...  This inspection method focuses on how easy and intuitive for new users is their interaction with an interactive device.  ... 
doi:10.6084/m9.figshare.7370051 fatcat:cuaufhrnnbeafnf6ebbkrmmw4m

A New Web Usage Mining Approach for Website Recommendations Using Concept Hierarchy and Website Graph

T. Vijaya Kumar, H. S. Guruprasad, Bharath Kumar K. M., Irfan Baig, Kiran Babu S.
2014 International Journal of Computer and Electrical Engineering  
These patterns can be used to provide set of recommendations for the web site which can be deployed by web site administrator for website enhancement.  ...  Along with the server access log file, we incorporate Website knowledge (i.e., Concept hierarchy and Website Graph) into the web usage mining phases. This incorporation can lead to superior patterns.  ...  In [8] , A New Web Usage Mining Approach for Website Recommendations Using Concept Hierarchy and Website Graph T. Vijaya Kumar, H. S. Guruprasad, Bharath Kumar K.  ... 
doi:10.7763/ijcee.2014.v6.796 fatcat:wnqo7evkgbeqdft7ld3pdcjbpi

An Enhanced Neural Graph based Collaborative Filtering with Item Knowledge Graph

Sangeetha M., Meera Devi Thiagarajan
2022 International Journal of Computers Communications & Control  
However, it requires higher processing time for convolutional neural network for performing limited suggestions. Hence, in this paper, an improved neural graph collaborative filtering is proposed.  ...  In recent days, the graph-based filtering techniques are used for the recommendation to improve the suggestions and for easy analysing.  ...  ., in this, an enhanced neural graph collaborative filtering proposed for the recommendation system.  ... 
doi:10.15837/ijccc.2022.4.4568 fatcat:b6dqcrnl3ndkff457vhidar3b4

Relphormer: Relational Graph Transformer for Knowledge Graph Representation [article]

Zhen Bi, Siyuan Cheng, Ningyu Zhang, Xiaozhuan Liang, Feiyu Xiong, Huajun Chen
2022 arXiv   pre-print
To this end, we propose a new variant of Transformer for knowledge graph representation dubbed Relphormer.  ...  Moreover, we propose masked knowledge modeling as a new paradigm for knowledge graph representation learning to unify different link prediction tasks.  ...  Therefore, it is intuitive to design a new technical solution for knowledge graph representation.  ... 
arXiv:2205.10852v2 fatcat:7iw263mzxzehrhx4ogjadzc5mi

GRAD: A New Graph Drawing and Analysis Library

Renata Vaderna, Igor Dejanović, Gordana Milosavljević
2016 Proceedings of the 2016 Federated Conference on Computer Science and Information Systems  
There are many Java libraries which have such capabilities, but they all have certain limitations and room for improvement, some of which are addressed in a new graph drawing and analysis library presented  ...  Doing so in an aesthetically pleasing way requires usage of graph layout algorithms. Since implementing them is not an easy task, most developers have to rely on existing solutions.  ...  There is a great number of graph layout algorithms, with plenty of researchers still working on discovering new and enhancing existing ones.  ... 
doi:10.15439/2016f299 dblp:conf/fedcsis/VadernaDM16 fatcat:mjthpaxzgra4jhs5ipkjocrtwi

Text-Graph Enhanced Knowledge Graph Representation Learning

Linmei Hu, Mengmei Zhang, Shaohua Li, Jinghan Shi, Chuan Shi, Cheng Yang, Zhiyuan Liu
2021 Frontiers in Artificial Intelligence  
In this paper, we propose to model the whole auxiliary text corpus with a graph and present an end-to-end text-graph enhanced KG embedding model, named Teger.  ...  Knowledge Graphs (KGs) such as Freebase and YAGO have been widely adopted in a variety of NLP tasks.  ...  CONCLUSION AND FUTURE WORK In this paper, we propose Teger, a novel end-to-end text-graph enhanced knowledge graph representation method.  ... 
doi:10.3389/frai.2021.697856 pmid:34490421 pmcid:PMC8418144 fatcat:nujckoz5efam3nhe73bqhmhidu

Graph Neural Networks with Continual Learning for Fake News Detection from Social Media [article]

Yi Han, Shanika Karunasekera, Christopher Leckie
2020 arXiv   pre-print
applies GNNs for fake news detection.  ...  Specifically, considering the capability of graph neural networks (GNNs) in dealing with non-Euclidean data, we use GNNs to differentiate between the propagation patterns of fake and real news on social  ...  Then, to verify an item of news, knowledge extracted from its content is compared with the facts in the knowledge graph [5, 37, 54] .  ... 
arXiv:2007.03316v2 fatcat:5onfi65uejfjbabr6fvanqflcy

Answering Who/When, What, How, Why through Constructing Data Graph, Information Graph, Knowledge Graph and Wisdom Graph

Lixu Shao, Yucong Duan, Xiaobing Sun, Honghao Gao, Donghai Zhu, Weikai Miao
2017 Proceedings of the 29th International Conference on Software Engineering and Knowledge Engineering  
Knowledge graphs have been widely adopted, in large part owing to their schema-less nature. It enables knowledge graphs to grow seamlessly and allows for new relationships and entities as needed.  ...  We also propose to specify knowledge graph in a progressive manner as four basic forms including data graph, information graph, knowledge graph and wisdom graph.  ...  This new setting of large knowledge graphs presents an opportunity to tackle the question answering problem using new approaches.  ... 
doi:10.18293/seke2017-079 dblp:conf/seke/ShaoDSGZM17 fatcat:qsx655iyt5gj7gjyyndtj44sda

Knowledge Graphs Representation for Event-Related E-News Articles

M.V.P.T. Lakshika, H.A. Caldera
2021 Machine Learning and Knowledge Extraction  
We propose an enhanced representation of a scalable knowledge graph by automatically extracting the information from the corpus of e-news articles and determine whether a knowledge graph can be used as  ...  Inclusively, it has been observed that the proposed knowledge graph generates a comprehensive and precise knowledge representation for the corpus of e-news articles.  ...  Data Availability Statement: The e-news articles presented in this study are available on https: // (accessed on 20 March 2021).  ... 
doi:10.3390/make3040040 fatcat:hwspn2ma4vh5fn3o4oh3zgwj6m

Residual Network and Embedding Usage: New Tricks of Node Classification with Graph Convolutional Networks [article]

Huixuan Chi, Yuying Wang, Qinfen Hao, Hong Xia
2021 arXiv   pre-print
Graph Convolutional Networks (GCNs) and subsequent variants have been proposed to solve tasks on graphs, especially node classification tasks.  ...  Experiments on Open Graph Benchmark (OGB) show that, by combining these techniques, the test accuracy of various GCNs increases by 1.21%~2.84%.  ...  For example, in molecular graph datasets, we can use chemical information and knowledge to handcraft more features for molecular representation learning, which is an interdisciplinary research direction  ... 
arXiv:2105.08330v2 fatcat:jy6q53444zchhj62dxyfby5e7a

Unsupervised Fake News Detection

Siva Charan Reddy Gangireddy, Deepak P, Cheng Long, Tanmoy Chakraborty
2020 Proceedings of the 31st ACM Conference on Hypertext and Social Media  
We develop GTUT, a graph-based approach for the task which operates in three phases.  ...  Through an extensive empirical evaluation over multiple real-world datasets, we establish the improved effectiveness of our method over state-of-the-art techniques for the task.  ...  The authors would like to thank Kaiqiang Yu (PhD candidate at NTU) for enriching discussions.  ... 
doi:10.1145/3372923.3404783 dblp:conf/ht/Gangireddy0L020 fatcat:s4koozmlinfxbk7okkfecl62hu
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