Search Results for "text extraction" - Page 6

Showing 224 open source projects for "text extraction"

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  • 1
    FAR - Find And Replace
    Search and replace operations on file content accross multiple files. Recursive operations within entire directory trees. FAR comes with support for regular expressions (regex) over multiple lines, automatic backup and various character encodings. Run grep like extractions to condense or rearrange sources, or perform bulk file renaming.
    Downloads: 28 This Week
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  • 2
    Tashkeela processed

    Tashkeela processed

    Tashkeela dataset cleaned and normalized.

    A version of the Tashkeela Arabic diacritized text dataset cleaned from the non-Arabic content and the undiacritized text, then divided into training, development, and testing sets. The cleaning process includes removing the XML tags and strange symbols, as well as fixing diacritics errors. After that, the tokenization is performed while focusing on the extraction of the Arabic words.
    Downloads: 0 This Week
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  • 3
    DeText

    DeText

    A Deep Neural Text Understanding Framework

    DeText is a Deep Text understanding framework for NLP-related ranking, classification, and language generation tasks. It leverages semantic matching using deep neural networks to understand member intents in search and recommender systems. As a general NLP framework, DeText can be applied to many tasks, including search & recommendation ranking, multi-class classification and query understanding tasks.
    Downloads: 3 This Week
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  • 4
    A collection of small utilities for: data extraction (text or binary files), data buffering, message queue control, column addition, date/time manipulation, and data recovery testing.
    Downloads: 5 This Week
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    Delta ML

    Delta ML

    Deep learning based natural language and speech processing platform

    ...It helps you to train, develop, and deploy NLP and/or speech models. Use configuration files to easily tune parameters and network structures. What you see in training is what you get in serving: all data processing and features extraction are integrated into a model graph. Text classification, named entity recognition, question and answering, text summarization, etc. Uniform I/O interfaces and no changes for new models.
    Downloads: 0 This Week
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  • 6
    jieba

    jieba

    Stuttering Chinese word segmentation

    "Jaba" Chinese word segmentation, do the best Python Chinese word segmentation component. Four word segmentation modes are supported. Precise mode, which tries to cut the sentence most precisely, suitable for text analysis. Full mode, scans all the words that can be formed into words in the sentence, the speed is very fast, but the ambiguity cannot be resolved. The search engine mode, on the basis of the precise mode, divides the long words again to improve the recall rate, which is suitable...
    Downloads: 9 This Week
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  • 7
    AhoCorasickDoubleArrayTrie

    AhoCorasickDoubleArrayTrie

    An extremely fast implementation of Aho Corasick algorithm

    AhoCorasickDoubleArrayTrie is a Java implementation of the Aho–Corasick multi-pattern matching algorithm that is optimized using a Double-Array Trie data structure. It is designed for fast keyword scanning across large texts, where you want to search for many patterns simultaneously and efficiently. The core idea is to build an automaton from a dictionary of patterns, then stream through input text to emit matches with minimal overhead. By using a double-array trie representation, the...
    Downloads: 9 This Week
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  • 8
    cocoNLP

    cocoNLP

    A Chinese information extraction tool

    cocoNLP is a lightweight natural-language processing toolkit geared toward practical information extraction from raw text, especially for Chinese and mixed Chinese–English content. Instead of requiring a heavy pipeline, it focuses on quick wins such as extracting names, places, organizations, emails, phone numbers, and dates directly from unstructured sentences. The project blends pattern-based methods with NLP heuristics, giving developers dependable results for real-world texts like chats, comments, and user-generated content. ...
    Downloads: 0 This Week
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  • 9
    Snips NLU

    Snips NLU

    Snips Python library to extract meaning from text

    Snips NLU is a Natural Language Understanding python library that allows to parse sentences written in natural language, and extract structured information. It’s the library that powers the NLU engine used in the Snips Console that you can use to create awesome and private-by-design voice assistants. The exact output is a bit richer, the point here is to give a glimpse on what kind of information can be extracted. Behind every chatbot and voice assistant lies a common piece of technology:...
    Downloads: 0 This Week
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  • 10
    Duckling (Old)

    Duckling (Old)

    Clojure library that parses text into structured data

    Duckling (the “old” archived version) is a natural language processing library (in Clojure) for parsing text to structured data — specifically, recognizing quantities such as dates, times, durations, measurements, currencies, etc., from free-form text. To use Duckling in your project, you just need two functions: load! to load the default configuration, and parse to parse a string. Duckling is a Clojure library that parses text into structured data. See our blog post announcement for more...
    Downloads: 0 This Week
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  • 11
    TIES

    TIES

    A smart search engine for medical documents

    TIES (Text Information Extraction System) is a clinical text search engine that uses Natural Language Processing techniques to extract medical concepts from free text clinical reports. It provides secure de-identified access to this information and has in built collaboration tools and honest broker functionality. It is licensed for academic use under the BSD license.
    Downloads: 2 This Week
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  • 12
    @Note2

    @Note2

    @Note2 - A workbench for Biomedical Text Mining

    Biomedical Text Mining (BioTM) is providing valuable approaches to the automated curation of scientific literature.
    Downloads: 3 This Week
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  • 13
    NeuroNER

    NeuroNER

    Named-entity recognition using neural networks

    Named-entity recognition (NER) aims at identifying entities of interest in the text, such as location, organization and temporal expression. Identified entities can be used in various downstream applications such as patient note de-identification and information extraction systems. They can also be used as features for machine learning systems for other natural language processing tasks. Leverages the state-of-the-art prediction capabilities of neural networks (a.k.a. ...
    Downloads: 0 This Week
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  • 14
    TextRank

    TextRank

    TextRank implementation for Python 3

    TextRank is an implementation of the TextRank algorithm for extractive text summarization and keyword extraction, inspired by Google’s PageRank.
    Downloads: 0 This Week
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  • 15
    ComplexEventExtraction

    ComplexEventExtraction

    Expression pattern collection of Chinese compound event extraction

    ...The project is intended as a research reference for event extraction, knowledge modeling, forecasting, and language-resource development.
    Downloads: 1 This Week
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  • 16
    TextGrapher

    TextGrapher

    Text Content Grapher based on keyinfo extraction by NLP method

    TextGrapher is a Python project that converts unstructured Chinese text into a structured semantic graph. It extracts high-frequency terms, keywords, named entities, and subject-verb-object phrases from an input document. The system then organizes these elements into connected nodes and relationships for visual inspection. Generated results are saved as an HTML graph that can be opened in a browser. The repository includes parsing, keyword extraction, graph construction, and visualization scripts. ...
    Downloads: 0 This Week
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  • 17

    StepPy

    Method of fast data extraction from structured documents

    Fast data extraction from structured documents like HTML and XML by using a phrase sequence search technique. The required data is found by searching for one or more signature phrases prior to the required data text followed by a terminal phrase after the data. No parsing is required which results in very high speed data extraction.
    Downloads: 0 This Week
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  • 18
    NLP Tasks

    NLP Tasks

    Natural Language Processing Tasks and References

    NLP Tasks is a curated reference map of natural language processing problems and supporting learning resources. It organizes a broad range of NLP subjects so researchers and students can quickly discover areas for further study. Topics include speech recognition, text classification, question answering, machine translation, summarization, sentiment analysis, information extraction, and many others. Individual sections link to research papers, datasets, software projects, challenges, and background material. The collection places particular emphasis on deep-learning approaches that were prominent when the repository was assembled. ...
    Downloads: 1 This Week
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  • 19
    iText®, a JAVA PDF library

    iText®, a JAVA PDF library

    PDF Library for Developers

    iText is an open-source PDF library available for Java and .NET (C#). iText allows you to effortlessly generate and manipulate standards-compliant PDF documents with a powerful and feature-rich SDK. With iText, you can create archivable and accessible PDFs, split and merge documents, fill and flatten forms, digitally sign documents, and more. iText add-ons enable additional functionality, such as PDF creation from HTML templates, secure redaction, OCR, and much more. The latest...
    Downloads: 43 This Week
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  • 20

    Information Extraction from Arabic Text

    Java based framework for extraction information from Arabic text

    This project presents a model a for extracting information from Arabic text. The project executables include three Java based modules that can be used to implement a rule-based information extraction process from Arabic text. These modules are: 1-A module for annotating a selected Arabic text file using a custom morpho-syntactic Part-of-Speech tagging scheme. 2-A module that can be used along with Protégé for establishing Ontology Web Language (OWL) based ontologies based on the concepts and relations in a text file. 3-A module for automatically extracting information from annotated Arabic text files. ...
    Downloads: 0 This Week
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  • 21
    Convolutional Recurrent Neural Network

    Convolutional Recurrent Neural Network

    Convolutional Recurrent Neural Network (CRNN) for image-based sequence

    Convolutional Recurrent Neural Network provides an implementation of the Convolutional Recurrent Neural Network (CRNN) architecture, a deep learning model designed for image-based sequence recognition tasks such as optical character recognition and scene text recognition. The architecture combines convolutional neural networks for extracting visual features from images with recurrent neural networks that model sequential dependencies in the extracted features. This hybrid approach allows the...
    Downloads: 0 This Week
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  • 22

    pdi-jira

    JIRA plugin for Pentaho Data Integration

    Using this PDI plugin you can connect any JIRA service even using SSL connection and perform JSON data extraction over the results. JQL is used to obtain data from the JIRA remote service.
    Downloads: 0 This Week
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  • 23
    Deeplearning-papernotes

    Deeplearning-papernotes

    Summaries and notes on Deep Learning research papers

    Deeplearning-papernotes is an implementation of Convolutional Neural Networks for sentence and text classification in TensorFlow, based on a well-known research paper that applies CNN architectures to natural language processing tasks with strong performance in sentiment analysis and similar classification problems. The repository provides the complete network definition, including an embedding layer to convert words into dense representations, convolution and max-pooling layers to extract...
    Downloads: 1 This Week
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  • 24
    TextTeaser

    TextTeaser

    TextTeaser is an automatic summarization algorithm

    textteaser is an automatic text summarization algorithm implemented in Python. It extracts the most important sentences from an article to generate concise summaries that retain the core meaning of the original text. The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant. By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative....
    Downloads: 8 This Week
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  • 25

    cbrTekStraktor

    an application to automatically extract text from comic books.

    ...The text extraction is achieved by a combination of statistical and graphical processing operations. It is based on the following 3 major algorithms - Binarization of color images (Niblak and other methods) - Connected components - K-Means clustering Apache Tesseract is used to perform Optical Character Recognition on the extracted text.
    Downloads: 0 This Week
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