Search Results for "text based"

...In simple terms Bayesian probability determines what is likely to be true based on past information. This book is interactive. While you can read it online as static content, it's better to use it as intended. It is written using Jupyter Notebook, which allows you to combine text, math, Python, and Python output in one place.

...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 project emphasizes performance and memory efficiency compared to simpler pointer-heavy trie structures, which can matter a lot for large dictionaries or latency-sensitive services. This makes it a strong fit for tasks like content filtering, entity/term spotting, dictionary-based annotation, or high-throughput log/text processing. ...

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.

Libcutils provides a self-contained set of fundamental routines which are essential to basically any Unix utility or daemon application written in C. The library provides fundamental data structures such as lists, hash-maps, strings and parsing functions for JSON or the typical dot-file based configuration data. The following list summarizes the currently supported functionality: * length delimited instead of NULL terminated strings * memory management based on reference counting * several list processing functions like iterators and map-reduce * support of [Ideal Hash Tries](http://infoscience.epfl.ch/record/64398/files/idealhashtrees.pdf) for highly efficient hash map data structures * parsers for [JSON](http://json.org) data and the text configuration files found in Unix system * doubly linked circular lists for reliable event queues * support for test and debugging of memory management problems such as memory leaks

Open Source Tool for Search Engine Optimization (SEO & SEM) used for automatic content processing. These SEO Content Genrators and Article Writers based on Text Writer: https://www.artikelschreiber.com/en/ https://www.unaique.net/en/ https://www.unaique.com/ https://www.artikelschreiben.com/ https://www.buzzerstar.com/ https://googleduplicatecontentsolver.sourceforge.io/ https://inkassos.github.io/inkasso/ https://www.artikelschreiber.com/opensource/ https://www.sebastianenger.com/ https://www.artikelschreiber.com/marketing/review/ https://muckrack.com/markus-muller https://linktr.ee/textgenerator Code Contains: - Perl Source code, language databases and more

This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text.

An information extraction library implementing modern algorithms for the extraction of named entities from text.

Java classes that enable definition of new Charsets based on other existing Charsets, without additional programming. Includes a character set with Kamenik encoding.

LiMa means Lightweight Markup Language. It is a parser for an easy to use ASCII/Text-based markup - comparable to Markdown or the Wikipedia-Markup language with special configurable extensions in defining Links and image-resources.

Small software suite for text string manipulation using well-known algorithms. Coded for academic purposes.

reputron is a knowledge extraction engine platform that covers all aspect of text mining, relevance, indexing and querying on a corpus of text documents.