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researcher

D. Shi

15 papers hereh-index 10590 citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author7
  • last author3

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.AI4
  • cs.CL2
  • cs.IT1
same name
  • D. Shi — 21 papers, h 53
  • D. Shi — 12 papers, h 15
  • D. Shi — 4 papers, h 9
  • D. Shi — 4 papers, h 4
  • D. Shi — 4 papers, h 6
  • D. Shi — 4 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedCharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising

31 citations · 71 across the 14 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2023★ 1 cited

Towards a Gateway for Knowledge Graph Schemas Collection, Analysis, and Embedding

Mattia Fumagalli, Marco Boffo, Daqian Shi +2

One of the significant barriers to the training of statistical models on knowledge graphs is the difficulty that scientists have in finding the best input data to address their pre…

cs.AI2023

Recognizing Entity Types via Properties

Daqian Shi, Fausto Giunchiglia

The mainstream approach to the development of ontologies is merging ontologies encoding different information, where one of the major difficulties is that the heterogeneity motivat…

cs.AI2023

Towards Ranking Schemas by Focus

Mattia Fumagalli, Daqian Shi, Fausto Giunchiglia

The main goal of this paper is to evaluate knowledge base schemas, modeled as a set of entity types, each such type being associated with a set of properties, according to their fo…

cs.AI2022

LiveSchema: A Gateway Towards Learning on Knowledge Graph Schemas

Mattia Fumagalli, Marco Boffo, Daqian Shi +2

One of the major barriers to the training of algorithms on knowledge graph schemas, such as vocabularies or ontologies, is the difficulty that scientists have in finding the best i…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.