Nitish Aggarwal

Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here

2016

pdf bib
NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity
John P. McCrae | Kartik Asooja | Nitish Aggarwal | Paul Buitelaar
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

pdf bib
Non-Orthogonal Explicit Semantic Analysis
Nitish Aggarwal | Kartik Asooja | Georgeta Bordea | Paul Buitelaar
Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

2014

pdf bib
Exploring ESA to Improve Word Relatedness
Nitish Aggarwal | Kartik Asooja | Paul Buitelaar
Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014)

pdf bib
Using Distributional Semantics to Trace Influence and Imitation in Romantic Orientalist Poetry
Nitish Aggarwal | Justin Tonra | Paul Buitelaar
Proceedings of the First AHA!-Workshop on Information Discovery in Text

2012

pdf bib
DERI&UPM: Pushing Corpus Based Relatedness to Similarity: Shared Task System Description
Nitish Aggarwal | Kartik Asooja | Paul Buitelaar
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)

pdf bib
Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation
Kartik Asooja | Jorge Gracia | Nitish Aggarwal | Asunción Gómez Pérez
Proceedings of the Second Workshop on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid MT

Search
Co-authors
Venues
Fix data