Search Results for "search engine optimization"
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Showing 1342 open source projects for "search engine optimization"
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RATS Search
BitTorrent P2P multi-platform search engine for Desktop
Rats Search is a cross-platform search tool for torrent indexing across multiple BitTorrent DHT networks. It provides a GUI for searching decentralized torrent metadata in real time without relying on centralized indexes. Built with Electron and Vue.js, Rats Search emphasizes decentralization and anonymity, allowing users to explore content from distributed sources such as the BitTorrent Mainline DHT and WebTorrent. It supports filtering, magnet link generation, and acts as a... -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. ... -
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Text Search Engine
A text search engine that supports mixed Chinese and English search
Text-Search-Engine is a JavaScript-based lightweight search engine that enables full-text search functionality. It allows developers to implement fast search indexing and retrieval in web applications. -
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Zinc Search Engine
ZincSearch. A lightweight alternative to elasticsearch
Zinc is a search engine that does full text indexing. It is a lightweight alternative to Elasticsearch and runs using a fraction of the resources. It uses bluge as the underlying indexing library. It is very simple and easy to operate as opposed to Elasticsearch which requires a couple dozen knobs to understand and tune which you can get up and running in 2 minutes. -
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Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
Search with Lepton is an open source demonstration project that shows how to build a conversational search engine using the Lepton AI framework. It combines traditional web search with large language models to provide natural language answers to user queries. It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. -
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SEO GEO Content Engine
Professional SEO and GEO content workflows for brands, SaaS teams
SEO GEO Content Engine is a comprehensive system designed to combine content generation, optimization, and analysis into a single AI-driven pipeline. It builds on tools like GEO Content Writer and SEO GEO Audit to create an end-to-end workflow for producing and refining search-optimized content. The system automates the process of identifying opportunities, generating content, and validating its effectiveness based on modern search criteria. -
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Whoogle Search
A self-hosted, ad-free, privacy-respecting metasearch engine
Get Google search results, but without any ads, javascript, AMP links, cookies, or IP address tracking. Easily deployable in one click as a Docker app, and customizable with a single config file. Quick and simple to implement as a primary search engine replacement on both desktop and mobile. Autocomplete/search suggestions. POST request search and suggestion queries (when possible). -
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Search-Index
A persistent, network resilient, full text search library
Search-Index is a lightweight and fast JavaScript-based search engine that enables full-text search indexing and retrieval for web applications. -
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Riot search
Go Open Source, Distributed, Simple and efficient Search Engine
Go Open Source, Distributed, Simple and efficient full text search engine. Efficient indexing and search (1M blog 500M data 28 seconds index finished, 1.65 ms search response time, 19K search QPS). Support for logical search. Support Chinese word segmentation (use gse word segmentation package concurrent word, speed 27MB / s). Support the calculation of the keyword in the text close to the distance（token proximity). -
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Minecraft server optimization guide
Minecraft server optimization guide
...The goal of the project is to help administrators understand how the Minecraft server engine works so they can make informed decisions about optimization rather than blindly applying configuration changes. The documentation emphasizes experimentation and explains that every server has different requirements depending on player count, hardware, and gameplay style. -
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Wicked Engine
3D engine with modern graphics
...There are other example projects that you can build as well within the solution. If you want to develop a C++ application that uses Wicked Engine, you can build the WickedEngine static library project for the appropriate platform, such as WickedEngine_Windows, and link against it. Including the "WickedEngine.h" header will attempt to link the binaries for the appropriate platform, but search directories should be set up beforehand. -
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AIDE ML
AI-Driven Exploration in the Space of Code
AIDE ML is an open-source research framework designed to explore automated machine learning development through agent-based search and code optimization. The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. ... -
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LineSearches.jl
Line search methods for optimization and root-finding
Line search methods for optimization and root-finding. This package provides an interface to line search algorithms implemented in Julia. The code was originally written as part of Optim, but has now been separated out to its own package. -
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SEO Machine
A specialized Claude Code workspace for creating long-form
SEO Machine is an AI-powered content production system built as a structured workspace for generating long-form, SEO-optimized blog content through automated workflows. It integrates research, writing, analysis, and optimization into a single pipeline, allowing users to produce high-quality articles tailored to search engine performance. The system uses specialized commands and agents to perform tasks such as keyword research, competitor analysis, content drafting, and optimization. It incorporates real data sources like Google Analytics and Search Console to guide decision-making and improve content effectiveness. ... -
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Ansvisor
Open-source Answer Engine Optimization platform
Ansvisor is an open-source AI visibility and answer engine optimization platform built to help brands understand how they appear in AI-generated answers. It tracks mentions across platforms such as ChatGPT, Google AI Overview, Google AI Mode, Gemini, Perplexity, Copilot, Grok, and Claude. The platform helps teams measure visibility scores, compare competitors, analyze prompt performance, and identify which sources AI systems cite alongside their brand. -
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SEO GEO Audit
Professional SEO and GEO audit workflows for brands, SaaS teams
...It provides actionable insights into areas such as keyword usage, content clarity, and structural optimization. The tool is built as part of a broader ecosystem of AI-driven SEO utilities, emphasizing automation and data-driven recommendations. It is particularly useful for businesses aiming to adapt to the evolving landscape of AI-assisted search. Overall, SEO GEO Audit helps bridge the gap between traditional SEO practices and next-generation AI search optimization. -
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NVIDIA cuOpt
GPU accelerated decision optimization
NVIDIA cuOpt is a GPU-accelerated optimization engine designed to solve complex mathematical optimization problems at large scale. It supports a range of optimization models including linear programming (LP), mixed integer linear programming (MILP), quadratic programming (QP), and vehicle routing problems (VRP). Built primarily in C++, cuOpt leverages NVIDIA GPUs to deliver near real-time solutions for optimization tasks involving millions of variables and constraints. ... -
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theHarvester
E-mails, subdomains and names
theHarvester is a very simple to use, yet powerful and effective tool designed to be used in the early stages of a penetration test or red team engagement. Use it for open source intelligence (OSINT) gathering to help determine a company's external threat landscape on the internet. The tool gathers emails, names, subdomains, IPs and URLs using multiple public data sources. -
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KerasTuner
A Hyperparameter Tuning Library for Keras
KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search algorithms. -
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SearXNG
Free internet metasearch engine which aggregates
SearXNG is a free and open-source metasearch engine designed to aggregate results from multiple search engines while prioritizing user privacy and anonymity. Instead of maintaining its own index, it queries numerous external search providers and merges the results into a single interface, increasing coverage and diversity of information. One of its core principles is privacy, as it does not track users, store personal data, or create search profiles, making it a strong alternative to traditional search engines. . ... -
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Optuna
A hyperparameter optimization framework
...You can check the optimization history, hyperparameter importances, etc. in graphs and tables. You don't need to create a Python script to call Optuna's visualization functions. Automated search for optimal hyperparameters using Python conditionals, loops, and syntax. Efficiently search large spaces and prune unpromising trials for faster results. Parallelize hyperparameter searches over multiple threads or processes without modifying code. -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and then experiment with multiple strategies—evolutionary algorithms, Bayesian optimization, bandit methods, genetic algorithms, etc. ... -
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qBittorrent RuTracker plugin
qBittorrent search engine plugin for rutracker
qBittorrent RuTracker plugin is a lightweight search engine extension designed to integrate the RuTracker torrent index directly into the qBittorrent client, allowing users to search for torrents without leaving the application interface. The plugin follows qBittorrent’s official search plugin architecture and is implemented as a Python script that communicates with the RuTracker website to retrieve and display search results. -
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Grey Wolf Optimizer for Path Planning
Grey Wolf Optimizer (GWO) path planning/trajectory
...It allows simulation of both two-dimensional and three-dimensional UAV trajectory planning depending on parameter setups. The tool provides built-in functions to configure different UAV environments and supports multiple optimization objectives. It includes progress visualization to help monitor the optimization process during simulations. Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics. -
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EvoTorch
Advanced evolutionary computation library built on top of PyTorch
EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods.
