Filters








1,815 Hits in 12.6 sec

A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals [article]

Cristian Santini, Genet Asefa Gesese, Silvio Peroni, Aldo Gangemi, Harald Sack, Mehwish Alam
2022 arXiv   pre-print
This study more specifically targets the problem of Author Name Disambiguation (AND) on Scholarly KGs and presents a novel framework, Literally Author Name Disambiguation (LAND), which utilizes Knowledge  ...  Graph Embeddings (KGEs) using multimodal literal information generated from these KGs.  ...  Acknowledgments This study was partially funded by the "Scholarship for research periods abroad aimed at the preparation of the master thesis" by the department of Classical Philology and Italian Studies  ... 
arXiv:2201.09555v3 fatcat:ndfd6zztn5f7ndldukzlunobvm

A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals [article]

Cristian Santini, Genet Asefa Gesese, Silvio Peroni, Aldo Gangemi, Harald Sack, Mehwish Alam
2022
This study more specifically targets the problem of Author Name Disambiguation (AND) on Scholarly KGs and presents a novel framework, Literally Author Name Disambiguation (LAND), which utilizes Knowledge  ...  Graph Embeddings (KGEs) using multimodal literal information generated from these KGs.  ...  Acknowledgments This study was partially funded by the "Scholarship for research periods abroad aimed at the preparation of the master thesis" by the department of Classical Philology and Italian Studies  ... 
doi:10.48550/arxiv.2201.09555 fatcat:6eqfiy2nnbezpmizclwlkat42m

A knowledge graph embeddings based approach for author name disambiguation using literals

Cristian Santini, Genet Asefa Gesese, Silvio Peroni, Aldo Gangemi, Harald Sack, Mehwish Alam
2022
This study more specifically targets the problem of Author Name Disambiguation (AND) on Scholarly KGs and presents a novel framework, Literally Author Name Disambiguation (LAND), which utilizes Knowledge  ...  Graph Embeddings (KGEs) using multimodal literal information generated from these KGs.  ...  Acknowledgements This study was partially funded by the "Scholarship for research periods abroad aimed at the preparation of the master thesis" by the Department of Classical Philology and Italian Studies  ... 
doi:10.5445/ir/1000149077 fatcat:o2rgp3p2cncajc2iulwg3ysnqe

The Microsoft Academic Knowledge Graph Enhanced: Author Name Disambiguation, Publication Classification, and Embeddings

Michael Färber, Lin Ao
2022 Quantitative Science Studies  
Based on a qualitative analysis of the MAKG, we address three aspects. First, we adopt and evaluate unsupervised approaches for large-scale author name disambiguation.  ...  In this article, we present methods for enhancing the Microsoft Academic Knowledge Graph (MAKG), a recently published large-scale knowledge graph containing metadata about scientific publications and associated  ...  Ultimately, we decided to use the high-precision setup to create the final knowledge graph, as precision is a much more meaningful metric for author name disambiguation as opposed to recall.  ... 
doi:10.1162/qss_a_00183 fatcat:fvkbhhyabzbm3arc2q6gtciq2y

AceKG: A Large-scale Knowledge Graph for Academic Data Mining [article]

Ruijie Wang, Yuchen Yan, Jialu Wang, Yuting Jia, Ye Zhang, Weinan Zhang, Xinbing Wang
2018 arXiv   pre-print
Most existing knowledge graphs (KGs) in academic domains suffer from problems of insufficient multi-relational information, name ambiguity and improper data format for large-scale machine processing.  ...  Based on AceKG, we conduct experiments of three typical academic data mining tasks and evaluate several state-of- the-art knowledge embedding and network representation learning approaches on the benchmark  ...  KNOWLEDGE EMBEDDING In this section, we will evaluate several state-of-the-art approaches for knowledge embedding using AceKG.  ... 
arXiv:1807.08484v2 fatcat:4aihears7rhkjdpkobprdqh5nq

The Data Set Knowledge Graph: Creating a Linked Open Data Source for Data Sets

Michael Färber, David Lamprecht
2021 Quantitative Science Studies  
As the author names of data sets can be ambiguous, we develop and evaluate a method for author name disambiguation and enrich the knowledge graph with links to ORCID.  ...  In this paper, we present an approach for constructing an RDF knowledge graph that fulfills these mentioned criteria.  ...  We implement and evaluate a method for author name disambiguation based on our data set knowledge graph.  ... 
doi:10.1162/qss_a_00161 fatcat:ixq2x4fga5b4dfgfyzk3hy4gia

Neural Entity Linking: A Survey of Models Based on Deep Learning [article]

Ozge Sevgili, Artem Shelmanov, Mikhail Arkhipov, Alexander Panchenko, Chris Biemann
2021 arXiv   pre-print
Finally, we briefly discuss applications of entity linking, focusing on the recently emerged use-case of enhancing deep pre-trained masked language models based on the transformer architecture.  ...  We distill generic architectural components of a neural EL system, like candidate generation and entity ranking, and summarize prominent methods for each of them.  ...  Acknowledgements The work was partially supported by a Deutscher Akademischer Austauschdienst (DAAD) doctoral stipend and the DFG-funded JOIN-T project BI 1544/4.  ... 
arXiv:2006.00575v3 fatcat:ra3kwc4tmbfhlmgtlevkcshcqq

Kanopy4Tweets: Entity Extraction and Linking for Twitter

Pablo Torres-Tramón, Hugo Hromic, Brian Walsh, Bahareh Rahmanzadeh Heravi, Conor Hayes
2016 Workshop on Making Sense of Microposts  
To this end, we adapted Kanopy -an unsupervised graph-based topic disambiguation system -to be used for the task of NEEL in the domain of Twitter, a fast-paced micro-blogging platform.  ...  Named Entity rEcognition and Linking (NEEL) from text is an essential task in many Natural Language Processing (NLP) applications because it enables a better understanding of the content.  ...  Named Entity Disambiguation The selected resource candidates for each named entity found in a Tweet are processed by Kanopy in an unsupervised graph-based approach for joint disambiguation that combines  ... 
dblp:conf/msm/Torres-TramonHW16 fatcat:45f7qtnarbejlgeghxxs3woleu

Graph integration of structured, semistructured and unstructured data for data journalism [article]

Oana Balalau
2020 arXiv   pre-print
We describe a complete approach for integrating dynamic sets of heterogeneous data sources along the lines described above: the challenges we faced to make such graphs useful, allow their integration to  ...  Our approach is implemented within the ConnectionLens system; we validate it through a set of experiments.  ...  We thank Julien Leblay for his contribution to earlier versions of this work [14, 15] . We thank Xin Zhang for extracting from YAGO 4 the subset used here.  ... 
arXiv:2007.12488v2 fatcat:tus7gf3wdngixnigc6qtjaminq

Enriching a Fashion Knowledge Graph from Product Textual Descriptions [article]

João Barroca, Abhishek Shivkumar, Beatriz Quintino Ferreira, Evgeny Sherkhonov, João Faria
2022 arXiv   pre-print
We use a transfer learning based approach to train an NER module on a small amount of manually labeled data, followed by an EL module that links the previously identified named entities to the appropriate  ...  Knowledge Graphs offer a very useful and powerful structure for representing information, consequently, they have been adopted as the backbone for many applications in e-commerce scenarios.  ...  Acknowledgements The authors would like to thank all team members of the FKS team at Farfetch. Their support was crucial for the conducted research.  ... 
arXiv:2206.01087v1 fatcat:nun6y53ijrc4hnonsh4tww27oi

Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking [article]

Isaiah Onando Mulang, Kuldeep Singh, Akhilesh Vyas, Saeedeh Shekarpour, Maria Esther Vidal, Jens Lehmann, Soren Auer
2020 arXiv   pre-print
The collaborative knowledge graphs such as Wikidata excessively rely on the crowd to author the information.  ...  In this paper, we examine the role of knowledge graph context on an attentive neural network approach for entity linking on Wikidata.  ...  In this work, we empirically illustrate that for a challenging KG like Wikidata, if a model is fused with additional context post-NER step, it improves entity linking performance.  ... 
arXiv:1912.06214v3 fatcat:l3atjeaam5f33p2wmccftzkvke

Text classification with semantically enriched word embeddings

N. Pittaras, G. Giannakopoulos, G. Papadakis, V. Karkaletsis
2020 Natural Language Engineering  
Concepts are selected via a variety of semantic disambiguation techniques, including a basic, a part-of-speech-based, and a semantic embedding projection method.  ...  We extract semantics for the words in the preprocessed text from the WordNet semantic graph, in the form of weighted concept terms that form a semantic frequency vector.  ...  In Li et al. (2017) , the authors use a document-level embedding that is based on word2vec and concepts mined from knowledge bases.  ... 
doi:10.1017/s1351324920000170 fatcat:g7bll3lbkrbwdmu4hwrg3fd7tq

Understanding metonymies in discourse

Katja Markert, Udo Hahn
2002 Artificial Intelligence  
In addition, metonymic interpretations that conform to a metonymy schema are preferred over metonymic ones that do not, and metonymic interpretations that are in conformance with knowledge-based aptness  ...  Therefore, in our approach, (metonymic or literal) interpretations that establish referential cohesion are preferred over ones that do not.  ...  We would also like to thank Michael Strube for his cooperation, as well as Bonnie Webber and two anonymous reviewers for their comments.  ... 
doi:10.1016/s0004-3702(01)00150-3 fatcat:jpifngxsmrf6lhswyfrmqcx6wy

MAG

Diego Moussallem, Ricardo Usbeck, Michael Röeder, Axel-Cyrille Ngonga Ngomo
2017 Proceedings of the Knowledge Capture Conference on - K-CAP 2017  
MAG is based on a combination of context-based retrieval on structured knowledge bases and graph algorithms. We evaluate MAG on 23 data sets and in 7 languages.  ...  We address this drawback by presenting a novel multilingual, knowledge-based agnostic and deterministic approach to entity linking, dubbed MAG.  ...  work has been supported by the H2020 project HOBBIT (GA no. 688227) as well as the EuroStars projects DIESEL (no. 01QE1512C) and QAMEL (no. 01QE1549C) and supported by the Brazilian National Council for  ... 
doi:10.1145/3148011.3148024 dblp:conf/kcap/MoussallemURN17 fatcat:jzwhxhhju5dizciojlia6cqqsu

DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection [article]

Mohit Mayank, Shakshi Sharma, Rajesh Sharma
2022 arXiv   pre-print
In this work, we propose DEAP-FAKED, a knowleDgE grAPh FAKe nEws Detection framework for identifying Fake News.  ...  to name a few.  ...  As we consider Wikidata KG as our knowledge base, we use disambiguation services 5 exposed by Wikidata for this step.  ... 
arXiv:2107.10648v2 fatcat:hm7wukgc6bdjdmy6basrkkzg2i
« Previous Showing results 1 — 15 out of 1,815 results