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Knowledge Graph [article]

2018 Zenodo  
Wikipedia article about the Knowlegde Graph (30/06/2018).  ...  [9] In October 2016, Google announced that the Knowledge Graph held over 70 billion facts. [10] There is no official documentation on the technology used for the Knowledge Graph implementation.  ...  Information from the Knowledge Graph is presented as a box to the right or top on mobile of search results.  ... 
doi:10.5281/zenodo.1326505 fatcat:x7ryz44s65fxdouepw54xbwwsy

Knowledge Graphs [article]

Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutierrez, José Emilio Labra Gayo, Sabrina Kirrane, Sebastian Neumaier, Axel Polleres, Roberto Navigli, Axel-Cyrille Ngonga Ngomo (+6 others)
2021 arXiv   pre-print
We provide an overview of prominent open knowledge graphs and enterprise knowledge graphs, their applications, and how they use the aforementioned techniques.  ...  We conclude with high-level future research directions for knowledge graphs.  ...  Acknowledgements: We thank the attendees of the Dagstuhl Seminar on "Knowledge Graphs" for discussions that inspired and influenced this paper, and all those that make such seminars possible.  ... 
arXiv:2003.02320v5 fatcat:ab4hmm2f2bbpvobwkjw4xbrz4u

Knowledge Graph Lifecycle: Building and maintaining Knowledge Graphs

Umutcan Simsek
2021 Zenodo  
Knowledge Graph Lifecycle  ...  Knowledge Graph Lifecycle Knowledge Graph Maintenance Knowledge Hosting Knowledge Curation Knowledge Deployment Knowledge Assesment Knowledge Cleaning Knowledge Enrichment Error Detection  ...  Page 18 Knowledge Creation Lessons Learned • Different perspectives on knowledge integrity ○ One experience we had with Tyrolean and German Tourism Knowledge Graph use cases is that the different instances  ... 
doi:10.5281/zenodo.5036184 fatcat:lrmdjgeyhjcznjiwcn4qydm7ja

Knowledge Questions from Knowledge Graphs

Dominic Seyler, Mohamed Yahya, Klaus Berberich
2017 Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '17  
We address the novel problem of automatically generating quiz-style knowledge questions from a knowledge graph such as DBpedia.  ...  The approach first selects a named entity from the knowledge graph as an answer. It then generates a structured triple-pattern query, which yields the answer as its sole result.  ...  We propose an end-to-end approach to the novel problem of generating quiz-style knowledge questions from knowledge graphs.  ... 
doi:10.1145/3121050.3121073 dblp:conf/ictir/SeylerYB17 fatcat:anvyhnxyizgz5h5mnswkb4jo5m

Knowledge Graph Validation [article]

Elwin Huaman, Elias Kärle, Dieter Fensel
2020 arXiv   pre-print
Knowledge graphs (KGs) have shown to be an important asset of large companies like Google and Microsoft.  ...  To do so a critical task is knowledge validation, which measures whether statements from KGs are semantically correct and correspond to the so-called "real" world.  ...  INTRODUCTION Knowledge curation (aka knowledge refinement) [8] is the process of ensuring (or ideally improving) the quality of knowledge graphs (KGs).  ... 
arXiv:2005.01389v1 fatcat:zalw5b7xxzb6vb5bsbxphvjnn4

Knowledge Graph Maintenance

Paul Groth
2020 Zenodo  
The challenges of ongoing knowledge graph maintenance and the role of people in that process are reflected on. Finally, we look to need for a knowledge scientist in these processes.  ...  Knowledge graphs are increasingly built using complex multifaceted machine learning-based systems relying on a wide of different data sources.  ...  "Sources of Change for Modern Knowledge Organization Systems." Knowledge Organization 43, no. 8 (2016).  ... 
doi:10.5281/zenodo.3813904 fatcat:zh2efvvt6fhvtaegmilqjogiv4

Knowledge Graph Embeddings [chapter]

Paolo Rosso, Dingqi Yang, Philippe Cudré-Mauroux
2018 Encyclopedia of Big Data Technologies  
Learning knowledge graph embeddings Learning KG embeddings consists in two key steps in general: 1.  ...  Conclusion With the booming of multi-relational data on the Web, knowledge graphs have become an important data source empowering many applications.  ... 
doi:10.1007/978-3-319-63962-8_284-1 fatcat:xwmtv26vyrayvk3uwudy32xaz4

Knowledge Graph Identification [chapter]

Jay Pujara, Hui Miao, Lise Getoor, William Cohen
2013 Lecture Notes in Computer Science  
The extractions form an extraction graph and we refer to the task of removing noise, inferring missing information, and determining which candidate facts should be included into a knowledge graph as knowledge  ...  In this paper, we show how uncertain extractions about entities and their relations can be transformed into a knowledge graph.  ...  We refer to this process of inferring a knowledge graph from a noisy extraction graph as knowledge graph identification.  ... 
doi:10.1007/978-3-642-41335-3_34 fatcat:x3i4cbm57ndp5hw44aaio4orke

Bridging Knowledge Graphs to Generate Scene Graphs [article]

Alireza Zareian, Svebor Karaman, Shih-Fu Chang
2020 arXiv   pre-print
In this paper, we present a unified formulation of these two constructs, where a scene graph is seen as an image-conditioned instantiation of a commonsense knowledge graph.  ...  On the other hand, commonsense knowledge graphs are rich repositories that encode how the world is structured, and how general concepts interact.  ...  C Commonsense graph construction Our method utilizes a background knowledge graph which encodes commonsense knowledge about the target entity and predicate classes.  ... 
arXiv:2001.02314v4 fatcat:ew4hwlvtybhpfiiwrpwmatgowe

Knowledge Graph Reasoning with Relational Directed Graph [article]

Yongqi Zhang, Quanming Yao
2021 arXiv   pre-print
Reasoning on the knowledge graph (KG) aims to infer new facts from existing ones.  ...  Here, we propose a variant of graph neural network, i.e., RED-GNN, to address the above challenges by learning the RElational Digraph with a variant of GNN.  ...  Require: a knowledge graph K = {V, R, F}, query (eq, rq, ?), depth L. 1: initialize h 0 eq (eq, rq) = 0 and the entity set V 0 eq = {eq}; 2: for = 1 . . .  ... 
arXiv:2108.06040v1 fatcat:55ej2pco2jc5jca6tsg4mvoavm

Probabilistic Knowledge Graph Construction

Dongwoo Kim, Lexing Xie, Cheng Soon Ong
2016 Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16  
Knowledge graph construction consists of two tasks: extracting information from external resources (knowledge population) and inferring missing information through a statistical analysis on the extracted  ...  We propose a new probabilistic knowledge graph factorisation method that benefits from the path structure of existing knowledge (e.g. syllogism) and enables a common modelling approach to be used for both  ...  An obstacle to knowledge graph construction is a gap between knowledge population and completion. The more a knowledge graph is populated, the better a statistical model predict the unknown triples.  ... 
doi:10.1145/2983323.2983677 dblp:conf/cikm/KimXO16 fatcat:uddabtjjgjephonblbhfiq52he

Binarized Knowledge Graph Embeddings [article]

Koki Kishimoto, Katsuhiko Hayashi, Genki Akai, Masashi Shimbo, and Kazunori Komatani
2019 arXiv   pre-print
Tensor factorization has become an increasingly popular approach to knowledge graph completion(KGC), which is the task of automatically predicting missing facts in a knowledge graph.  ...  This limitation is expected to become more stringent as existing knowledge graphs, which are already huge, keep steadily growing in scale.  ...  in a knowledge graph, whose number is enormous because knowledge graphs are sparse.  ... 
arXiv:1902.02970v1 fatcat:2bjnoae4ojdxfng7ipho6hbkza

Enterprise Knowledge Graph Foundation

Mike Atkin
2020 Zenodo  
Launch presentation of the Enterprise Knowledge Graph Foundation A non-profit organization to help accelerate adoption of semantic standards, promote data interoperability and facilitate reuse.  ...  graph End-User Tools The ability of end users to navigate, search, link and extract value from the knowledge graph Executive Leadership EKG engagement, commitment and prioritization by CIO, CTO  ...  (i.e. use cases, accountability, data sources, data flows, SLAs) are modeled and registered into the knowledge graph Level 3: Enterprise  Data inventory is centralized in the graph and linked to governance  ... 
doi:10.5281/zenodo.3874814 fatcat:ucyjjewlsfcbnersz3tokd76ti

Embedding Uncertain Knowledge Graphs [article]

Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun, Carlo Zaniolo
2019 arXiv   pre-print
Embedding models for deterministic Knowledge Graphs (KG) have been extensively studied, with the purpose of capturing latent semantic relations between entities and incorporating the structured knowledge  ...  The capturing of uncertain knowledge will benefit many knowledge-driven applications such as question answering and semantic search by providing more natural characterization of the knowledge.  ...  Uncertain Knowledge Graph Embedding Problem.  ... 
arXiv:1811.10667v2 fatcat:joig6esu7jgqvfgnys3grohxt4

Metalexicography as Knowledge Graph

David Lindemann, Christiane Klaes, Philipp Zumstein, Michael Wagner
2019 International Conference on Language, Data, and Knowledge  
various existing infrastructures, such as the Linguistic Linked Open Data Cloud (LLOD), Wikidata, or to the ongoing project coli-conc, a resource for managing and sharing concordances between library knowledge  ... 
doi:10.4230/oasics.ldk.2019.19 dblp:conf/ldk/LindemannKZ19 fatcat:acvnum7xenhprgx55hm7f36i6i
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