Share Your Papers!
Here are links to influential academic papers in NLP. Learning the history is important to learn about what is going on outside of our code in the communities.
There is definitely a rich history going back all the way to even as far as 1960 - 1980's that has shaped this field into what it is.
It is also a very exciting time due to the success of machine learning off springing originally from the study of Artificial Intelligence coming to fruition as Moores has consistently tipped computation to critical mass. Natural Language Processing is also seeing similar parallels and so is a hot topic everywhere. Reading through these documents will help give you the bigger picture and where we currently stand.
- Deep Learning for Web Search and Natural Language Processing
- Probabilistic topic models
- Natural language processing: an introduction
- A unified architecture for natural language processing: Deep neural networks with multitask learning
- A Critical Review of Recurrent Neural Networksfor Sequence Learning
- Deep parsing in Watson
- Online named entity recognition method for microtexts in social networking services: A case study of twitter
- NLTK: The Natural Language Toolkit
- Scikit-learn: Machine learning in Python
- TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text
Named Entity Recognition
- A survey of named entity recognition and classification
- Benchmarking the extraction and disambiguation of named entities on the semantic web
- Knowledge base population: Successful approaches and challenges
- SpeedRead: A fast named entity recognition Pipeline
- Cross-lingual Pseudo-Projected Expectation Regularization for Weakly Supervised Learning
- Generating Chinese Named Entity Data from a Parallel Corpus
- IXA pipeline: Efficient and Ready to Use Multilingual NLP tools
- The Unreasonable Effectiveness of Recurrent Neural Networks
- Statistical Language Models based on Neural Networks
- Slides from Google Talk