Showing 5 open source projects for "text batch processing tools"

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  • 1
    SpringAll

    SpringAll

    Step by step, learn Spring Boot, Spring Boot & Shiro, Spring Batch

    SpringAll is a comprehensive learning project that gathers a wide range of Spring, Spring Boot, and Spring Cloud demos in one repository. It is designed for developers who want to deepen their understanding of the Spring ecosystem by exploring concrete, runnable code samples. Each module focuses on a specific technology or integration—covering web applications, ORM frameworks, microservices, caching, messaging, security, distributed systems, and monitoring. The repository emphasizes both...
    Downloads: 0 This Week
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  • 2

    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...
    Downloads: 0 This Week
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  • 3

    JCLALtext

    Text processing module for JCLAL

    JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project.
    Downloads: 0 This Week
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  • 4
    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.
    Downloads: 0 This Week
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  • 5
    Provides a set of tools for processing text, such as text extraction and classification. Classification implementations to be implemented include: Bayesian and Statistical (N-gram).
    Downloads: 0 This Week
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