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The BioNLP UIMA Component Repository provides UIMA wrappers for novel and well-known 3rd-party NLP tools used in biomedical text prosessing, such as tokenizers, parsers, named entity taggers, and tools for evaluation.
...Commonly used techniques in this project are NaturalLanguageProcessing,
Information Extraction and Question-Answering Architecture.
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- Latest Version -
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Details of latest version can be found on project website -
http://geekdadaji.com
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- CONTACT DETAILS -
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CREATOR : SWAPNIL A JADHAV (saj1919)
EMAIL ID : dadajibudhau@gmail.com
WEBSITE : http://geekdadaji.com
LICENSE : CC BY-NC 4.0
The Wikipedia Miner toolkit provides simplified access to Wikipedia. This open encyclopedia represents a vast, constantly evolving multilingual database of concepts and semantic relations; a promising resource for nlp and related research.
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D.U.C.K (Determine segmentation of Unknown words by using Context Knowledge)is an NLP tool, which aims to find the correct segmentation for unknown words in written Hebrew. Statistics from different scopes will be used to determine the segmentation.
TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.
This is a suite of several software agents to provide a complete architecture of lexical base as proposed in Didier Schwab's PhD. thesis. It will be used for automatic translation, information retrieval and other natural language processing tasks.
JWebPro: A Java tool that can interact with Google search and then process the returned Web documents in a couple of ways. The outputs can serve as inputs for NLP, IR, infor extraction, Web mining, online social network extraction/analysis applications.
JVnSegmenter is a Java-based and open-source Vietnamese word segmentation tool. The segmentation model was trained on about 8,000 sentences using Conditional Random Fields (FlexCRFs). This tool would be useful for Vietnamese NLP community.
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AutoSummary uses Natural Language Processing to generate a contextually-relevant synopsis of plain text. It uses statistical and rule-based methods for part-of-speech tagging, word sense disambiguation, sentence deconstruction and semantic analysis.