Search Results for "extractive text summarizer"
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Showing 13 open source projects for "extractive text summarizer"
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Automatic text summarizer
Module for automatic summarization of text documents and HTML pages
Sumy is an automatic text summarization library that provides multiple algorithms for extracting key content from documents and articles. Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains a simple evaluation framework for text summaries. Implemented summarization methods are described in the documentation. I also maintain a list of alternative implementations of the summarizers in various programming languages. -
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LLM TLDR
95% token savings. 155x faster queries. 16 languages
LLM TLDR is a tool that leverages large language models (LLMs) to generate concise, coherent summaries (TL;DRs) of long documents, articles, or text files, helping users quickly understand large amounts of content without reading every word. It integrates with LLM APIs to handle input texts of varying lengths and complexity, applying techniques like chunking, context management, and multi-pass summarization to preserve accuracy even when the source is very large. The system supports both extractive and abstractive summarization styles so that users can choose whether they want condensed highlights or a more narrative paraphrase of key ideas. ... -
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SafeClaw
Chat with it via text and voice
...It emphasizes privacy and predictability by using traditional programming, rule-based intent parsing, and established machine learning tools rather than large language models, meaning there are no per-token API costs and deterministic behavior. The assistant offers features such as voice control using fully local speech-to-text (Whisper) and text-to-speech (Piper) capabilities, news aggregation with extractive summarization, and smart home or Bluetooth device control. SafeClaw supports multiple channels, including CLI and Telegram, and avoids prompt injection risk because it doesn’t rely on LLMs for core operations. -
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txtai
Build AI-powered semantic search applications
...Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid pace, models can understand concepts in documents, audio, images and more. Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. The following applications are powered by txtai. -
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PyTextRank
Python implementation of TextRank algorithms
PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, for graph-based natural language work -- and related knowledge graph practices. -
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Ainee
Ainee - AI Notetaking and Learning Companion
Ainee is your ultimate AI-powered notetaking and learning companion. Capture lecture notes in real-time and effortlessly transform audio, text, files, and YouTube videos into formatted notes, mindmaps, quizzes, flashcards, podcasts, and more. Explore our AI meeting note taker, AI notes, video transcript generator, PDF to AI converter, and AI flashcard maker. Enhance your learning with our AI voice recorder, article summarizer AI, and AI quiz generator. Additionally, share your knowledge base with others to foster the flow of information and help new users benefit from collective insights. ... -
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Desktop Plagiarism Checker
Free plagiarism software for .NET (Windows 7, 8.1, 10, 11)
Plagiarisma tools are a valuable resource for anyone who wants to ensure the originality and accuracy of their written work. The plagiarism checker is a useful tool for detecting any instances of copied content in a document. It compares the text with a vast database of sources to determine the level of similarity and highlights any potential areas of concern. The paraphraser tool allows writers to rephrase their sentences to avoid plagiarism, while the summarizer provides a concise overview of a longer text. The AI detector is an advanced feature that uses artificial intelligence to identify potential instances of plagiarism and provides suggestions for rewording. ... -
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DrQA
Reading Wikipedia to Answer Open-Domain Questions
DrQA is an open-domain question answering system that reads large text corpora—famously Wikipedia—to answer natural language questions with extractive spans. It follows a two-stage pipeline: a fast document retriever first narrows down candidate articles, and a neural machine reader then predicts the exact answer span from those passages. The retriever relies on classic IR features (like TF-IDF and n-gram statistics) to remain lightweight and scalable to millions of documents. ... -
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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. -
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We have implemented a core summarizer of scientific articles written in Spanish, with the following components: a tokenizer, a grammar checker, a clarity checker, a cohesion-coherence checker, a common-topic extractor and an output formatter.
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11
Text Expander, Inverse summarizer
Expand text, inverse summarizer
IT WILL WORK WITH A JAVA DEVELOPMENT KIT 1.7 ONLY !!! This program is a data-miner and a knowledge-miner. It does exactly the opposite of what the text summarizers do. A text summarizer produces a shortened text given some text as an input. An inverse summarizer takes the shortened input, a similar or a same text and does the process in reverse. This results in an expanded text. It can be used with any text or notes that have the knowledge gaps. It is a great aid to any creative work and it simply pin-points to data that may be of some relevance. ... -
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TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.
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13
Auto Summarization tool using java
Auto summarization provides a concise summary for a document.
Auto summarization provides a concise summary for a document. In this I present a Statistical approach to addressing the text generation problem in domain-independent, single-document summarization. My thesis Includes salton’s vector space model which divides the sentences into categories which can also be used for summarizing the contents in WebPages. The summarizer initially breaks the entire document into sentences based on the separators. The Second step is that the unnecessary words are removed from the document. ...
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