Search Results for "word analysis"
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Showing 16 open source projects for "word analysis"
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TXM
Unicode XML TEI text analysis platform
TXM is a free and open-source cross-platform Unicode & XML based text analysis environment and graphical client, supporting Windows, Linux and Mac OS X. It can also be used online as a J2EE standard compliant web portal (GWT based) with access control built in. DOWNLOAD LATEST VERSION OF TXM : http://textometrie.ens-lyon.fr/spip.php?rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP... -
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Semantic Assistants
Natural Language Processing (NLP) for the Masses
Semantic Assistants support users in content retrieval, analysis, and development, by offering context-sensitive NLP services directly integrated in standard desktop clients, like a word processor, and web information systems, like a wiki. -
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buddidictionary
An English to Sinhala Dictionary with Morphological Processing
Buddidictionary is an English to Sinhala bilingual dictionary embed with English and Sinhala Morphological analysis. the system has been developed as a part of the EnSiMaS Project which is capable to translate English sentence into Sinhala. System has been developed through the MaSMT MUlti agent system development framework -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify... -
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The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. ...
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JCLTP
A Java Class Library for Text Processing
JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types... -
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Welsh Natural Language Toolkit
WNLT is a suite of open source natural language modules for the Welsh
The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. ... -
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FALCON - Text Search Java Project
JSON based text search Java Project
----------------- - What is it? - ----------------- The "Falcon Search" is a JAVA API and tool to search inside the documents. It was originally started to search the content in pdf files under the project "HAWK Search". Searching with this tool is query-based not word-based as in most of the document search tools OR document readers. It also takes care of jumbling of words within query and spelling mistakes. Commonly used techniques in this project are Natural Language... -
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DocCO
Non-disjoint groupping of Documents based on word sequence approach
This is a GUI for learning non disjoint groups of documents based on Weka machine learning framework. It offers the possibility to make non disjoint clustering of documents using both vectorial and sequential representation (word sequence approach based on WSK kernel). All data format supported by WEKA could be used in DocCO. Data could be loaded from files, from databases or from specified URL. All the preprocessing techniques implemented in WEKA could be used before performing the learning. -
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The Deep Email Miner Application is a software solution for the multistaged analysis of an Email Corpus. Social network analysis and text mining techniques are connected to enable an in depth view into the underlying information. The self-executable Version 1.1 jar file will now run on Java 1.5 or higher. A Windows executable file of Version 1.1 is also provided in the Files section. Documentation can be found on the project homepage.
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The Neurpheus Morphological Analyser performs morphological analysis, stemming or word form generation tasks using sophisticated classification methods for an analysis of words unseen in a training dictionary.
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A voice recognition application which detect Quran (Islamic Holy book) pronunciation and result in a detection success percentage for each word of the Quran statements, when complete it can be considered a base for Arabic language recognition.
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The Word Vector Tool is a simple but flexible Java library to create word vector representations of text documents. Word vectors can be used for various text processing tasks, as text classification, text clustering or information retrieval.
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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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JTextPro: A Java-based Text Processing tool that includes sentence boundary detection (using maximum entropy classifier), word tokenization (following Penn conventions), part-of-speech tagging (using CRFTagger), and phrase chunking (using CRFChunker).
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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.
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