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Russa Biswas
Russa Biswas
Postdoctoral Researcher at Hasso-Plattner Institute, Potsdam
Verified email at hpi.de
Title
Cited by
Cited by
Year
A survey on knowledge graph embeddings with literals: Which model links better literal-ly?
GA Gesese, R Biswas, M Alam, H Sack
Semantic Web 12 (4), 617-647, 2021
732021
A Comprehensive Survey of Knowledge Graph Embeddings with Literals: Techniques and Applications.
GA Gesese, R Biswas, H Sack
DL4KG@ ESWC, 31-40, 2019
322019
Large Language Models and Knowledge Graphs: Opportunities and Challenges
JZ Pan, S Razniewski, JC Kalo, S Singhania, J Chen, S Dietze, H Jabeen, ...
arXiv preprint arXiv:2308.06374, 2023
272023
Wikipedia Infobox Type Prediction Using Embeddings.
R Biswas, R Türker, FB Moghaddam, M Koutraki, H Sack
DL4KGS@ ESWC, 46-55, 2018
182018
Entity typing based on RDF2Vec using supervised and unsupervised methods
R Sofronova, R Biswas, M Alam, H Sack
The Semantic Web: ESWC 2020 Satellite Events: ESWC 2020 Satellite Events …, 2020
142020
Cat2Type: Wikipedia Category Embeddings for Entity Typing in Knowledge Graphs
R Biswas, R Sofronova, H Sack, M Alam
Proceedings of the 11th on Knowledge Capture Conference, 81-88, 2021
132021
Do judge an entity by its name! entity typing using language models
R Biswas, R Sofronova, M Alam, N Heist, H Paulheim, H Sack
The Semantic Web: ESWC 2021 Satellite Events: Virtual Event, June 6–10, 2021 …, 2021
122021
Entity Type Prediction in Knowledge Graphs using Embeddings. arXiv (2020)
R Biswas, R Sofronova, M Alam, H Sack
10*2020
MADLINK: Attentive multihop and entity descriptions for link prediction in knowledge graphs
R Biswas, H Sack, M Alam
Semantic Web, 1-24, 2022
92022
Entity type prediction leveraging graph walks and entity descriptions
R Biswas, J Portisch, H Paulheim, H Sack, M Alam
International Semantic Web Conference, 392-410, 2022
82022
Colex2Lang: Language Embeddings from Semantic Typology
Y Chen, R Biswas, J Bjerva
Proceedings of the 24th Nordic Conference on Computational Linguistics …, 2023
62023
Contextual Language Models for Knowledge Graph Completion
B Russa, R Sofronova, M Alam, H Sack
MLSMKG 2021: Machine Learning with Symbolic Methods and Knowledge Graphs 2021, 2021
6*2021
Embedding based link prediction for knowledge graph completion
R Biswas
Proceedings of the 29th ACM International Conference on Information …, 2020
62020
Hierclassart: knowledge-aware hierarchical classification of scholarly articles
M Alam, R Biswas, Y Chen, D Dessě, GA Gesese, F Hoppe, H Sack
Companion Proceedings of the Web Conference 2021, 436-440, 2021
52021
Is aligning embedding spaces a challenging task? a study on heterogeneous embedding alignment methods
R Biswas, M Alam, H Sack
arXiv preprint arXiv:2002.09247, 2020
5*2020
Measuring biosignals of overweight and obese children for real-time feedback and predicting performance
N Öksüz, R Biswas, I Shcherbatyi, W Maass
Information Systems and Neuroscience: Gmunden Retreat on NeuroIS 2017, 185-193, 2018
52018
Knowledge graphs evolution and preservation
VA Carriero, L Asprino, R Biswas, I Celino, J Domingue, M Dumontier, ...
4*2020
Exploiting equivalence to infer type subsumption in linked graphs
R Biswas, M Koutraki, H Sack
The Semantic Web: ESWC 2018 Satellite Events: ESWC 2018 Satellite Events …, 2018
42018
Predicting wikipedia infobox type information using word embeddings on categories
R Biswas, M Koutraki, H Sack
2018 EKAW Posters and Demonstrations Session, EKAW-PD 2018; Nancy; France …, 2018
32018
Linked Open Data Validity--A Technical Report from ISWS 2018
TA Ghor, E Agrawal, M Alam, O Alqawasmeh, C D'amato, A Annane, ...
arXiv preprint arXiv:1903.12554, 2019
2*2019
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