Search Results for "summarization" - Page 3
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Showing 58 open source projects for "summarization"
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Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
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HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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WebCQ is a continual query system for large-scale Web information monitoring. It tracks various changes to static and dynamic web pages, delivers personalized notifications and summarization with prioritization, and analyzes page structures.
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Text classification and summarization library for .NET. A port of the Classifier4J Java library (see http://classifier4j.sourceforge.net).
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Jindex4U is a software, which provides assistance to the META tags insertion on your Web site. This software uses various technologies like N.L.P. (Natural Language Processing) and A.T.S. (Automatic Text Summarization).
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Google Cloud’s AI-powered APIs help you translate documents, websites, apps, audio files, videos, and more at scale with best-in-class quality and enterprise-grade control and security.
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The Gips project - Graph-based Information Processing and Search - develops a generic graph-based summarization framework. Third party modules can be plugged in, but basic functionality is provided.
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This project aims at providing an implementation of some state-of-the-art techniques for summarizing multi-dimensional data. Multi-dimensional data summarization can effectively support query optimization algorithms and OLAP applications.
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text_summurization_abstractive_methods
Multiple implementations for abstractive text summurization
This repo is built to collect multiple implementations for abstractive approaches to address text summarization it is built to simply run on google colab , in one notebook so you would only need an internet connection to run these examples without the need to have a powerful machine , so all the code examples would be in a jupyter format , and you don't have to download data to your device as we connect these jupyter notebooks to google drive -
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A set of classes for Natural Language Processing in PHP for: 1. Part of speech Tagging - Brill, n-gram, HMM 2. Princeton Wordnet querying and access 3. Document summarization 4. Document classification - EM, Bayes 5. Stemming - Porter, Lancaster