Search Results for "accurate"

Wren Engine is a semantic engine designed to empower Model Context Protocol (MCP) clients and AI agents by providing accurate, contextual, and governed access to business data. It serves as a bridge between large language models (LLMs) and enterprise systems, facilitating seamless integration and interaction. ​

VnCoreNLP is a Java-based natural language processing toolkit tailored for Vietnamese. It offers a fast and accurate pipeline for essential NLP tasks, facilitating research and application development in Vietnamese language processing. ​

DeepCode AI has always been the backbone of Snyk code, which is why it's the fastest, most accurate SAST on the market. DeepCode AI, powering the Snyk platform, utilizes multiple AI models, is trained on security-specific data, and is all curated by top security researchers to give you all the power of AI without any of the drawbacks. With 11 supported languages, and multiple AI models, Snyk's DeepCode AI was designed to find and fix vulnerabilities and manage tech debt.

Weka wrapper for the SGM toolkit for text classification and modeling. Provides Sparse Generative Models for scalable and accurate text classification and modeling for use in high-speed and large-scale text mining. Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification.

GUAJE stands for Generating Understandable and Accurate fuzzy models in a Java Environment. Thus, it is a free software tool (licensed under GPL-v3) with the aim of supporting the design of interpretable and accurate fuzzy systems by means of combining several preexisting open source tools, taking profit from the main advantages of all of them. It is a user-friendly portable tool designed and developed in order to make easier knowledge extraction and representation for fuzzy systems, paying special attention to interpretability issues. ...

The JSparse Matrix Package, developed by Philipp Geigenmüller during an internship at the prudsys AG in Chemnitz, Germany, is an extension of the well-known Java Matrix Package (JAMA) and allows the use of sparse matrices and related algorithms.

This project is contains implementations of algorithms to integrate the output of different NLP tools (part of speech taggers, morphologies, parsers, etc.) in order to obtain more accurate, more robust and more fine-grained linguistic analyses. Note that the code is outdated, but left here for documentation purposes. Its functionality may be reimplemented within the NLP2RDF project (http://code.google.com/p/nlp2rdf).