This page lists academic papers on which OpenNLP is based, and papers which are interesting for its future development.
Please extend the lists with new papers.
Papers implemented by OpenNLP
This list contains papers which are implemented by OpenNLP or influenced its development.
- Coreference for NLP Applications
- Learning to Parse Natural Language with Maximum Entropy Models, by Adwait Ratnaparkhi
- Maximum entropy models for natural language ambiguity resolution, by Adwait Ratnaparkhi
- A Maximum Entropy Approach to Identifying Sentence Boundaries, by Jeff Reynar and Adwait Ratnaparkhi
- Topic segmentation: Algorithms and applications, by Jeff Reynar
- A Simple Introduction to Maximum Entropy Models for Natural Language Processing, by Adwait Ratnaparkhi
- Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms, by Michael Collins
Machine Learning Papers
- Online Passive-Aggressive Algorithms, by Crammer, Koby. Dekel, Ofer. Keshet, Joseph. Shalev-Shwartz, Shai. Singer, Yoram
Papers on Similarity component of OpenNLP
- Building a repository of background knowledge using semantic skeletons, by Boris Galitsky 2006
- Improving relevancy accessing linked opinion data, by Boris Galitsky, Gabor Dobrocsi, Josep Lluis de la Rosa 2010
- Improving Relevancy Accessing Linked Opinion Data, by Boris Galitsky, Josep Lluis de la Rosa and Gábor Dobrocsi 2010
- From Generalization of Syntactic Parse Trees to Conceptual Graphs, by Boris Galitsky, Gabor Dobrocsi, Josep Lluis de la Rosa and Sergei O Kuznetsov 2011
- Using Generalization of Syntactic Parse Trees for Taxonomy Capture on the Web, by Boris Galitsky, Gabor Dobrocsi, Josep Lluis de la Rosa and Sergei O Kuznetsov 2011
- Learning Ontologies from the Web for Microtext Processing, by Boris Galitsky, Gabor Dobrocsi and Josep Lluis de la Rosa 2011