David Day

842 citations
27 papers · 515 indexed · h-index 11

Impact in

    • Natural Language Processing Techniques
    • Topic Modeling
    • Semantic Web and Ontologies
    • Speech and dialogue systems
    • Advanced Text Analysis Techniques
    • AI-based Problem Solving and Planning
    • Web Data Mining and Analysis

Papers in

Journals
Language Resources and Evaluation (4 papers)International Journal of Approximate Reasoning (2 papers)˜The œJohn Marshall law review (1 paper)The Journal of Negro History (1 paper)Scholarworks (University of Massachusetts Amherst) (1 paper)
Partner nations
United StatesEgyptItaly

In The Last Decade

David Day

25 papers receiving 422 citations

Peers

David Day
Comparison fields: 5 of 67
  • Artificial Intelligence 438
  • Information Systems 94
  • Management Science and Operations Research 35
  • Signal Processing 22
  • Geography, Planning and Development 10
Replace Kevin Humphreys with:
Kevin Humphreys United Kingdom
José M. Castaño United States
Cristian Ursu United Kingdom
Stephen Tratz United States
Valentin Jijkoun Netherlands
Leonardo Lesmo Italy
Hristo Tanev Italy
Nicola Stokes Ireland
Luís Sarmento Portugal
Maria Teresa Pazienza Italy
David Day relative to Kevin Humphreys United Kingdom Kevin Humphreys's profile →
Citations per field
00.5×1.7×
Kevin Humphreys · 1×
Citations per year

Countries citing papers authored by David Day

Since Specialization
Citations

This map shows the geographic impact of David Day's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Day with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Day more than expected).

Fields of papers citing papers by David Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Day. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Day. The network helps show where David Day may publish in the future.

Co-authorship network

The 25 scholars most cited alongside David Day, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Day Line = papers co-authored together David Day links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20222
2
A Corpus for Cross-Document Co-reference.
20086
3
A Platform for the Empirical Analysis of Translation Resources, Tools and their Use
20050
4
Callisto: A Configurable Annotation Workbench.
200421
5
Recognizing and Organizing Opinions Expressed in the World Press
200344
6
Real users, real data, real problems: the MiTAP system for monitoring bio events
20028
7 200210
8 20025
9 20023
10
A Framework for Cross-Document Annotation
20001
11 200012
12 200055
13
Alembic Workbench corpus developrnent tool.
19981
14 199748
15
Achieving flexibility for autonomous agents in dynamic environments
19910
16 19883
17
A Judicial Perspective on Expert Discovery under Federal Rule 26(b)(4): An Empirical Study of Trial Court Judges and a Proposed Amendment, 20 J. Marshall L. Rev. 377 (1987)
19871
18 198733
19 198524
20 19806

About David Day

David Day is a scholar working on Artificial Intelligence, Management Science and Operations Research, Statistics and Probability, Health and Law, having authored 27 papers that have together received 515 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (11 papers), Topic Modeling (10 papers), Semantic Web and Ontologies (9 papers), Biomedical Text Mining and Ontologies (4 papers), AI-based Problem Solving and Planning (3 papers), Speech and dialogue systems (2 papers), Logic, Reasoning, and Knowledge (2 papers) and Web Data Mining and Analysis (2 papers). The work is most often cited by research in Artificial Intelligence (438 citations), Information Systems (94 citations), Management Science and Operations Research (35 citations), Signal Processing (22 citations) and Geography, Planning and Development (10 citations). David Day has collaborated with scholars based in United States, Egypt and Italy. Frequent co-authors include Marc Vilain, Lynette Hirschman, Patricia Robinson, John Aberdeen, David D. Palmer, Robyn Kozierok, John D. Burger, John C. Henderson, Paul R. Cohen and John S. Garofolo. Their work appears in journals such as Language Resources and Evaluation, International Journal of Approximate Reasoning, ˜The œJohn Marshall law review, The Journal of Negro History and Scholarworks (University of Massachusetts Amherst).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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