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Named graphs, provenance and trust [PDF]

Proceedings of the 14th international conference on World Wide Web - WWW '05, 2005
The Semantic Web consists of many RDF graphs nameable by URIs. This paper extends the syntax and semantics of RDF to cover such Named Graphs. This enables RDF statements that describe graphs, which is beneficial in many Semantic Web application areas.
Carroll, Jeremy J., Bizer, Christian, Hayes, Pat, Stickler, Patrick   +3 more
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Named graphs

Journal of Web Semantics, 2005
The Semantic Web consists of many RDF graphs nameable by URIs. This paper extends the syntax and semantics of RDF to cover such named graphs. This enables RDF statements that describe graphs, which is beneficial in many Semantic Web application areas. Named graphs are given an abstract syntax, a formal semantics, an XML syntax, and a syntax based on N3.
Carroll, Jeremy J., Bizer, Christian, Hayes, Pat, Stickler, Patrick   +3 more
openaire   +3 more sources

Word-Character Graph Convolution Network for Chinese Named Entity Recognition

IEEE/ACM Transactions on Audio Speech and Language Processing, 2020
Recent researches try to integrate word information into the character-based Chinese NER by modifying the structure of the standard BiLSTM-CRF model. They follow the paradigm of explicitly modeling forward and backward sequences, adopting an LSTM variant
Zhuo Tang, Boyan Wan, Li Yang
semanticscholar   +1 more source

Named Entity Recognition as Graph Classification

2021
Injecting real-world information (typically contained in Knowledge Graphs) and human expertise into an end-to-end training pipeline for Natural Language Processing models is an open challenge. In this preliminary work, we propose to approach the task of Named Entity Recognition, which is traditionally viewed as a Sequence Labeling problem, as a Graph ...
Ismail Harrando, Raphaël Troncy
openaire   +2 more sources

On Graph-Based Name Disambiguation

Journal of Data and Information Quality, 2011
Name ambiguity stems from the fact that many people or objects share identical names in the real world. Such name ambiguity decreases the performance of document retrieval, Web search, information integration, and may cause confusion in other applications.
Xiaoming Fan, Lizhu Zhou, Xu Pu, Bing Lv, Jianyong Wang   +4 more
openaire   +2 more sources

Towards Adaptive Consensus Graph: Multi-View Clustering via Graph Collaboration

IEEE transactions on multimedia, 2023
Multi-view clustering is a long-standing important task, however, it remains challenging to exploit valuable information from the complex multi-view data located in diverse high-dimensional spaces.
Huibing Wang, Guangqi Jiang, Jinjia Peng, Ruoxi Deng, Xianping Fu   +4 more
semanticscholar   +1 more source

Cooperative Trajectory Design of Multiple UAV Base Stations With Heterogeneous Graph Neural Networks

IEEE Transactions on Wireless Communications, 2023
Unmanned aerial vehicles as base stations (UAV-BSs) are recognized as effective means for tackling eruptive communication service requirements especially when terrestrial infrastructures are unavailable.
Xiaochen Zhang, Haitao Zhao, Jibo Wei, Chao Yan, Jun Xiong, Xiaoran Liu   +5 more
semanticscholar   +1 more source

Statistical estimation of the names of HTTPS servers with domain name graphs

Computer Communications, 2016
We present the domain name graph (DNG), which is a formal expression that can keep track of CNAME chains and characterize the dynamic and diverse nature of DNS mechanisms and deployments.We develop a framework called Service-Flow map (SFMap) that works on top of the DNG.
Tatsuya Mori, Takeru Inoue, Akihiro Shimoda, Kazumichi Sato, Shigeaki Harada, Keisuke Ishibashi, Shigeki Goto   +6 more
openaire   +2 more sources

A deep learning method for predicting metabolite-disease associations via graph neural network

Briefings Bioinform., 2022
Metabolism is the process by which an organism continuously replaces old substances with new substances. It plays an important role in maintaining human life, body growth and reproduction.
Feiyue Sun, Jianqiang Sun, Qi Zhao
semanticscholar   +1 more source

Graph(Graph): A Nested Graph-Based Framework for Early Accident Anticipation

IEEE Workshop/Winter Conference on Applications of Computer Vision
Anticipating traffic accidents early using dashcam videos is an important task for ensuring road safety and building reliable intelligent autonomous vehicles.
Nupur Thakur, PrasanthSai Gouripeddi, Baoxin Li   +2 more
semanticscholar   +1 more source