World's Best Scientists 2026 revealed!
Stan Szpakowicz

Stan Szpakowicz

D-Index & Metrics

Computer Science

D-Index
31
Citations
7052
World Ranking
13389
National Ranking
519

Overview

Stan Szpakowicz is affiliated with the University of Ottawa in Canada and has contributed to the field of computer science, focusing primarily on artificial intelligence. Their research spans several specialized areas including natural language processing techniques, topic modeling, advanced graph neural networks, speech and dialogue systems, semantic web and ontologies, as well as business process modeling and analysis.

The scientist's publication record includes papers in venues such as Synthesis Lectures on Human Language Technologies and arXiv (Cornell University). Notable recent works include:

  • Semantic Relations Between Nominals, Second Edition (2021), published in Synthesis Lectures on Human Language Technologies
  • Semantic Relations and Deep Learning (2020), published in arXiv (Cornell University)

Stan Szpakowicz has co-authored multiple papers with several frequent collaborators. These include Vivi Năstase, with whom they have collaborated on nine publications; Preslav Nakov, with eight shared works; and Diarmuid Ó Séagdha, also with eight joint publications.

Their book publications include at least one title published by Morgan & Claypool Publishers: "Semantic Relations Between Nominals, Second Edition" released in 2021.

Szpakowicz's work integrates various main topics such as natural language processing techniques and topic modeling, areas that feature prominently in their eight publications within artificial intelligence. The inclusion of advanced graph neural networks points to an interest in machine learning approaches, while research into speech and dialogue systems aligns with human-computer interaction subfields.

Frequent publication venues for Szpakowicz's research reflect a focus on human language technologies and preprint dissemination, offering contributions to both established and emergent research outlets.

Best Publications

  • Beyond accuracy, f-score and ROC: a family of discriminant measures for performance evaluation

    Marina Sokolova;Nathalie Japkowicz;Stan Szpakowicz

  • SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • Identifying expressions of emotion in text

    Saima Aman;Stan Szpakowicz

  • SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • Roget’s thesaurus and semantic similarity

    Mario Jarmasz;Stan Szpakowicz

  • SemEval-2007 Task 04: Classification of Semantic Relations between Nominals

    Roxana Girju;Preslav Nakov;Vivi Nastase;Stan Szpakowicz

  • Detecting Emotion Stimuli in Emotion-Bearing Sentences

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz

  • A WordNet-based algorithm for word sense disambiguation

    Xiaobin Li;Stan Szpakowicz;Stan Matwin

  • Negoplan: an expert system shell for negotiation support

    S. Matwin;S. Szpakowicz;Z. Koperczak;G.E. Kersten

  • Semi-Automatic Recognition of Noun Modifier Relationships

    Ken Barker;Stan Szpakowicz

  • Restructurable representations of negotiation

    Gregory E. Kersten;Wojtek Michalowski;Stan Szpakowicz;Zbig Koperczak

  • Using Roget's Thesaurus for Fine-grained Emotion Recognition.

    Saima Aman;Stan Szpakowicz

  • Hierarchical versus Flat Classification of Emotions in Text

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz

  • Learning noun-modifier semantic relations with corpus-based and WordNet-based features

    Vivi Nastase;Jelber Sayyad-Shirabad;Marina Sokolova;Stan Szpakowicz

  • Classification of semantic relations between nominals

    Roxana Girju;Preslav Nakov;Preslav Nakov;Vivi Nastase;Stan Szpakowicz;Stan Szpakowicz

  • SemEval-2 Task 9: The Interpretation of Noun Compounds Using Paraphrasing Verbs and Prepositions

    Cristina Butnariu;Su Nam Kim;Preslav Nakov;Diarmuid Ó Séaghdha

  • Summarizing short stories

    Anna Kazantseva;Stan Szpakowicz

  • plWordNet 3.0 - a Comprehensive Lexical-Semantic Resource.

    Marek Maziarz;Maciej Piasecki;Ewa Rudnicka;Stan Szpakowicz

  • SemEval-2010 Task 9: The Interpretation of Noun Compounds Using Paraphrasing Verbs and Prepositions

    Cristina Butnariu;Su Nam Kim;Preslav Nakov;Diarmuid Ó Séaghdha

  • Prior and contextual emotion of words in sentential context

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz;Stan Szpakowicz

  • A survey of book recommender systems

    Haifa Alharthi;Diana Inkpen;Stan Szpakowicz

  • Semantic Relations Between Nominals

    Vivi Nastase;Preslav Nakov;Diarmuid Saghdha;Stan Szpakowicz

  • Multi-way classification of semantic relations between pairs of nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • SemEval-2013 Task 4: Free Paraphrases of Noun Compounds

    Iris Hendrickx;Preslav Nakov;Stan Szpakowicz;Zornitsa Kozareva

Frequent Co-Authors

Preslav Nakov
Preslav Nakov Mohamed bin Zayed University of Artificial Intelligence
Diana Inkpen
Diana Inkpen University of Ottawa
Stan Matwin
Stan Matwin Dalhousie University
Sebastian Padó
Sebastian Padó University of Stuttgart
Peter D. Turney
Peter D. Turney Ronin Institute
Nathalie Japkowicz
Nathalie Japkowicz American University
Rada Mihalcea
Rada Mihalcea University of Michigan–Ann Arbor
Saif M. Mohammad
Saif M. Mohammad National Research Council Canada
Christiane Fellbaum
Christiane Fellbaum Princeton University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Computer Science in the USA opens up a world of flexible online education opportunities. Many students opt for associates degrees online as a first step, building essential skills while saving on costs. For those seeking to accelerate their learning, the shortest online masters degree programs allow you to earn a respected qualification quickly, helping you enter the workforce faster.

If your focus is on career ROI, consider pursuing masters degrees that are worth it in computer science or related tech fields. These programs are designed to meet industry demand and boost your employment prospects.

Affordability is a key concern for many students. There are many cheap online degrees fast that can help you gain a recognized credential while minimizing student debt. Exploring these flexible online pathways can help you advance your career in technology no matter where you start.

Best Scientists Citing Stan Szpakowicz

Trending Scientists

Recently Published Articles