Emily Pitler

3.5k citations
27 papers · 1.4k · h-index 16

Impact in

Papers in

    • Natural Language Processing Techniques 24
    • Topic Modeling 21
    • Text Readability and Simplification 9
    • Algorithms and Data Compression 4
    • Semantic Web and Ontologies 4
    • Speech and dialogue systems 4
    • Software Engineering Research 2

Emily Pitler

27 papers receiving 1.3k citations

Peers

Emily Pitler
Comparison fields: 5 of 53
  • Artificial Intelligence 1.3k
  • Computer Vision and Pattern Recognition 153
  • Information Systems 146
  • Computer Science Applications 19
  • Health Informatics 4
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Citations per field
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Citations per year

Countries citing papers authored by Emily Pitler

Since Specialization
Citations

This map shows the geographic impact of Emily Pitler'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 Emily Pitler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily Pitler more than expected).

Fields of papers citing papers by Emily Pitler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emily Pitler. 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 Emily Pitler. The network helps show where Emily Pitler may publish in the future.

Co-authors

The 25 scholars most cited alongside Emily Pitler, 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 Emily Pitler Line = papers co-authored together Emily Pitler links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008259
2 2009193
3 2009176
4 2019111
5
Easily Identifiable Discourse Relations
200895
6
Revisiting Readability: A Unified Framework for Predicting Text Quality
200879
7 202078
8
Automatic Evaluation of Linguistic Quality in Multi-Document Summarization
201058
9 201047
10 201946
11 201334
12
Using Web-scale N-grams to Improve Base NP Parsing Performance
201029
13 201829
14
Creating Robust Supervised Classifiers via Web-Scale N-Gram Data
201025
15
Proceedings of the ACL 2011 Student Session
201125
16 202215
17
Structural features for predicting the linguistic quality of text: applications to machine translation, automatic summarization and human-authored text
201013
18 201412
19
Dynamic Programming for Higher Order Parsing of Gap-Minding Trees
201212
20 201810

About Emily Pitler

Emily Pitler is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Human Factors and Ergonomics and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 1.4k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Topic Modeling (21 papers), Text Readability and Simplification (9 papers), Algorithms and Data Compression (4 papers), Semantic Web and Ontologies (4 papers), Speech and dialogue systems (4 papers), Software Engineering Research (2 papers) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Artificial Intelligence (1.3k citations), Computer Vision and Pattern Recognition (153 citations), Information Systems (146 citations), Computer Science Applications (19 citations) and Health Informatics (4 citations). Emily Pitler has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Ani Nenkova, Annie Louis, Daniel Andor, Jacob Devlin, Chris Alberti, Michael Collins, Dekang Lin, Shane Bergsma, R. Thomas McCoy and Aravind K. Joshi. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Clinical journal of oncology nursing, Meeting of the Association for Computational Linguistics, University of Brighton Repository (University of Brighton) and ScholarlyCommons (University of Pennsylvania).

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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