Search Results for "simple java code"
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Showing 15 open source projects for "simple java code"
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Stanford CoreNLP
Stanford CoreNLP, a Java suite of core NLP tools
CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. -
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BioNLP is an initiative by the University of Colorado Denver Health Sciences Center to create and distribute code, software, and data for applying natural language processing techniques to biomedical texts
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Next Generation Programming
Compose Software Without Writing Any Programing Code
"Next Generation Programming - Programming Without Coding Software" is a drag-drop wizard for creating simple or complex applications without writing any programming language code The Software is coded/designed with "Java Programming Language" for novice/expert programmers; Programmers can write softwares with visual tools : drag-drop components;visual editors... Programmers can use the software to compose of simple/complex applications : Database programs, circuit design, generate code and upload to chip for designed circuits (ESP8266, ESP32 chips) The Software in question is much simpler to use than PWCT (https://sourceforge.net/projects/doublesvsoop/) software. ... -
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aseryla
Aseryla code repositories
This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format. It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts. https://aseryla2.sourceforge.io/ -
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masmt
A frame work for Multi agent system development
MaSMT is a java based multi-agent system development framework, especially designed for development of English to Sinhala machine translation system. MaSMT also capable to develop any multi-agent based system through its architecture. Reference: B. Hettige, A. S. Karunananda, G. Rzevski, Multi-agent solution for managing complexity in English to Sinhala Machine Translation, International Journal of Design & Nature and Ecodynamics, Volume 11, Issue 2, 2016, 88 – 96. B. Hettige, A. S.... -
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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining. -
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Graphical Grammar Studio
An user friendly grammar tool for natural language processing tasks
Full documentation with tutorials is included in the download package. Graphical Grammar Studio is a tool for applying grammars which behave as words acceptors/consumers and annotators. GGS grammars can be used to find and annotate sequences of words which respect certain conditions, in a given input. Its purpose is for creating NLP tools like phrase chunkers, named entity finders, pronoun co-reference solvers etc. A grammar is represented by a state machine which can be visualized, edited... -
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gannu
Java API and tools for performing NLP and other AI tasks
Java API and tools for performing a wide range of AI tasks such as: word sense disambiguation (released), optimization (5 Evolutionary Algorithms Implemented ETA February 2014), opinion mining (ETA November 2014) and text wikification (ETA July 2014). Gannu includes some graphical interfaces for scientific purposes. When using Gannu please cite: *Jiménez, F. -
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TextProcessor
A Java package to preprocess text datasets for posterior text analysis
The TextProcessor Java package is a text processing toolkit, which provides some frequently used text processing functions such as stemming, removing stop-words, generating a term vocabulary, and calculating the term-doc frequency matrix. Basic topic mining models such as LDA and sparse NMF are also supported. The package can also generate feature files from a given text dataset with LDA and LIBSVM format for posterior procedures such as classification or clustering. The toolkit is also... -
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miac-p
Code for syntactic parsing and other NLP apps.
Code for syntactic parsing and other natural language processing applications. -
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A multi-agent architecture for building interactive dramas. It uses the Jason's BDI engine, being the Jason's agent-oriented programming language utilized for performing the drama management and for authoring behaviors for the characters.
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This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text.
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This project is contains implementations of algorithms to integrate the output of different NLP tools (part of speech taggers, morphologies, parsers, etc.) in order to obtain more accurate, more robust and more fine-grained linguistic analyses. Note that the code is outdated, but left here for documentation purposes. Its functionality may be reimplemented within the NLP2RDF project (http://code.google.com/p/nlp2rdf).
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This project is a compilation of tools/libraries to help with tasks related to Text Analytics mainly in Java. These tools range from simple wrappers to sophisticated mining tasks that can improve the productivity of researchers and engineers.
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QuickAI (pronounced, "quickeye", or just "Quick" for short) is a return to the fundamental goals of creating an artificial intelligence. The priorities are to implement core models of knowledge and knowing, a reasoning engine, and a simple interface.
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