- grammar-parser
- Grammar-German
- Grammar-Samskrit
- Grammar-Tamil
- Machine Translation
- NLP
- Pub-NLP
- Pub-Semantic
- RDF
- Search Engine
- SPARQL
- https://en.wikipedia.org/wiki/Languages_of_India
- https://en.wikipedia.org/wiki/List_of_languages_by_number_of_native_speakers_in_India
- https://news.ycombinator.com/item?id=11686029
- Announcement : https://research.googleblog.com/2016/05/announcing-syntaxnet-worlds-most.html?m=1
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https://en.wikibooks.org/wiki/German/Grammar/Prepositions_and_Postpositions
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https://www.lsa.umich.edu/german/hmr/Grammatik/Praepositionen/Prepositions.html
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http://www.dartmouth.edu/~deutsch/Grammatik/perfect/Perfect.html
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http://www.german-grammar.de/grammar/content/english_german_table_of_content.htm
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http://www.lsa.umich.edu/german/hmr/Grammatik/Gender/Gender.html
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Passive-perfekt, http://www.nthuleen.com/teach/grammar/passiv2.html
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http://www2.klett.de/sixcms/media.php/10/67524301_bewerbungstraining_LHB_EB.pdf
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http://www.dw.com/en/german-words-that-contradict-themselves/a-37145955
- GoldenDict :: dictionary lookup program
- https://sourceforge.net/projects/germandict/files/
- http://german.stackexchange.com/questions/491/where-can-i-find-a-parsable-list-of-german-words
- http://softwarerecs.stackexchange.com/questions/19693/offline-english-german-dictionary-for-gnu-linux
- Unicode equivalence
- http://en.wikipedia.org/wiki/Sanskrit#Phonology
- http://en.wikipedia.org/wiki/Unicode_equivalence
- https://en.wikipedia.org/wiki/Devanagari#Unicode
- http://www.unicode.org/charts/PDF/U0900.pdf
- https://en.wikipedia.org/wiki/Sanskrit_grammar#Compounds_.28sam.C4.81sa.29
- http://unicode.org/faq/indic.html
- Google's Grammar Pile for Indic scripts: https://drive.google.com/drive/folders/0B9QDHej9UGAdbW1ReUs4ZDZmRWc
- Yaska : https://en.wikipedia.org/wiki/Yāska
- Panini : https://en.wikipedia.org/wiki/P%C4%81%E1%B9%87ini
- Bahuvrihi
- Synecdoche.
- http://en.wikipedia.org/wiki/Pingala#Combinatorics
- http://en.wikipedia.org/wiki/Virahanka
- Origins of Fibonacci number
- http://en.wikipedia.org/wiki/Backus%E2%80%93Naur_Form
- http://en.wikibooks.org/wiki/Algorithm_Implementation/Mathematics/Fibonacci_Number_Program#Python
- http://en.wikipedia.org/wiki/List_of_ancient_Indian_writers
- NLP, A Paninian perspective.
- Toward a Global Science: Mining Civilizational Knowledge By Susantha Goonatilake.
- A Deterministic Dependency Parser with Dynamic Programming for Sanskrit, Amba Kulkarni, Department of Sanskrit Studies, University of Hyderabad, [email protected]. Proceedings of the Second International Conference on Dependency Linguistics (DepLing 2013), pages 157–166, Prague, August 27–30, 2013; Charles University in Prague, Matfyzpress, Prague, Czech Republic.
- Parsing Sanskrit texts: Some relation specificissues
- ANALYSIS OF SANSKRIT TEXT : PARSING AND SEMANTIC RELATIONS
Grammar-Tamil
- https://en.wikipedia.org/wiki/Statistical_machine_translation
- https://en.wikipedia.org/wiki/Apertium
- https://en.wikipedia.org/wiki/Anusaaraka
- https://en.wikipedia.org/wiki/OpenLogos, http://logos-os.dfki.de/#mozTocId415559
- http://NLTK.org
- An Introduction to Natural Language Processing that introduces text based machine learning techniques (ex. N-grams, corpus,..) inorder to do text classification and analysis.
- Front End Resources:
- Back End Resources:
- NLTK trainer, https://bitbucket.org/japerk/nltk-trainer/src
- https://github.com/marcua/tweeql/
- http://streamhacker.com/2010/10/25/training-binary-text-classifiers-nltk-trainer/
- http://www.laurentluce.com/posts/twitter-sentiment-analysis-using-python-and-nltk/
- http://spaceandtim.es/opennews/broca
- https://github.com/ftzeng/broca
- Automated Job Description Text analyzers :
- Textio
- Joblint and the source code.
- A topic modeling paper is Latent Dirichlet Allocation by Blei.
- https://mitpress.mit.edu/books/introduction-algorithms
- http://www.amazon.com/The-Art-Computer-Programming-Vol/dp/0201896834
- G. Bordogna, M. Pagani, and G. Pasi, Soft Computing for Information Retrieval on the Web. Springer Verlag, 2006.
- Indurkhya, N., and Damerau, F. Handbook Of Natural Language Processing, 2nd Edition CRC 2010
- Sebastiani, (2002) Machine learning in automated text categorization, ACM Computing Surveys, 34 (1), 1-47.
- On The Use of Fuzzy Rules to Text Document Classification: Tatiane M. Nogueira, Solange O. Rezende, Heloisa A. Camargo
- A fuzzy approach to classifying text documents, Liu , Song.
- http://www.nltk.org/book/ch06.html
- 2016, Yoav Goldberg, "A Primer on Neural Network Models for Natural Language Processing", Volume 57, pages 345-420, http://www.jair.org/papers/paper4992.html
- Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks : http://www.aclweb.org/anthology/P15-1150
- 2015, Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks.
- 2015, Improving Distributional Similarity with Lessons Learned from Word Embeddings: https://levyomer.files.wordpress.com/2015/03/improving-distributional-similarity-tacl-2015.pdf
- 2015, Compositional Vector Space Models for Knowledge Base Completion.
- 2015, Grammar as a Foreign Language.
- 2014, Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors, Marco Baroni, Georgiana Dinu, German Kruszewski, Center for Mind/Brain Sciences, University of Trento, Italy.
- 2014, Neural Word Embedding as Implicit Matrix Factorization: https://levyomer.files.wordpress.com/2014/09/neural-word-embeddings-as-implicit-matrix-factorization.pdf
- https://levyomer.files.wordpress.com/2014/09/neural-word-embeddings-as-implicit-matrix-factorization.pdf
- https://levyomer.files.wordpress.com/2015/03/improving-distributional-similarity-tacl-2015.pdf
- https://www.aaai.org/ocs/index.php/AAAI/AAAI11/paper/viewFile/3659/3898
- Graph Embeddings: https://www.utc.fr/~bordesan/dokuwiki/_media/en/transe_nips13.pdf
- http://www.aclweb.org/anthology/P/P14/P14-1023.pdf
- 2007, Charles A. Sutton, Andrew McCallum: Piecewise pseudolikelihood for efficient training of conditional random fields. ICML 2007: 863-870
- Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling Jenny Rose Finkel, Trond Grenager, and Christopher Manning
- Sunita Sarawagi and William W. Cohen: Semi-Markov Conditional Random Fields for Information Extraction
- Gang Luo, Xiaojiang Huang, Chin-Yew Lin, Zaiqing Nie: Joint Named Entity Recognition and Disambiguation
- J-NERD: Joint Named Entity Recognition and Disambiguation with Rich Linguistic Features, Dat Ba Nguyen, Martin Theobald, Gerhard Weikum
- Neural CRF Parsing, Greg Durrett and Dan Klein
- Learning to Compose Neural Networks for Question Answering, Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein
- David Belanger, Andrew McCallum: Structured Prediction Energy Networks
- 2008, Zhifei Li and Sanjeev Khudanpur, Large-scale Discriminative n-gram Language Models for Statistical Machine Translation: http://www.cs.jhu.edu/~zfli/pubs/discriminative_lm_for_smt_zhifei_amta_08.pdf
- 2001, John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML 2001: 282-289
- http://www.isi.edu/~gil/
- http://semantic-cora.org
- http://semantic-cora.org/index.php/Publications_and_Talks
- https://en.wikipedia.org/wiki/Semantic_query
- https://en.wikipedia.org/wiki/Semantic_Web
- MWE-aware English Dependency Corpus :: https://github.com/naist-cl-parsing/mwe-aware-dependency
- https://explorable.com/research-paper-format
- https://explorable.com/design-of-experiment
- Microsoft Research Concept Graph taxonomy from their ProBase project. This data contains 5,376,526 unique concepts, 12,501,527 unique instances, and 85,101,174 IsA relations for entity disambiguation.
- https://www.google.de/search?q=provenance+metadata&ie=utf-8&oe=utf-8&gws_rd=cr&ei=iwuWV8evJsn5UKb9h-gO
- https://www.w3.org/2005/Incubator/prov/wiki/What_Is_Provenance
- https://news.ycombinator.com/item?id=7946024
- https://en.wikipedia.org/wiki/Semantic_data_model
- RDF, https://en.wikipedia.org/wiki/Resource_Description_Framework
- http://fileinfo.com/extension/rdf
- http://www.file-extensions.org/rdf-file-extension
- http://hatis.techtarget.com/fileformat/RDF-Compiled-UIC-source-code-Geoworks-UI-Compiler
- http://wiki.opensemanticframework.org/index.php/Ontology_Tools
- https://en.wikipedia.org/wiki/Ontology_%28information_science%29
- http://www.obitko.com/tutorials/ontologies-semantic-web/ + https://en.wikipedia.org/wiki/Problem_solving
- https://en.wikipedia.org/wiki/Ontology_%28information_science%29
[Protégé](https://en.wikipedia.org/wiki/Protégé_(software) (Java)
- http://protege.stanford.edu :: A free, open-source ontology editor and framework for building intelligent systems.
- Source on Github: https://github.com/protegeproject/protege