Search Results for "recommendation"
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Showing 31 open source projects for "recommendation"
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in Scala, it shows the architecture of large-scale recommendation systems, including candidate sourcing, ranking, and heuristics. ... -
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Vespa
The open big data serving engine
...This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. This makes it possible to make recommendations specifically for each user or situation, using completely up to date information. -
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What to cook?
Get a recipe to cook today, based on the ingredients you have at home
WhatToCook is a recipe recommendation tool that suggests recipes based on available ingredients, helping users reduce food waste by utilizing what they have on hand. -
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paicoding
A user-friendly and powerful open source community
paicoding is an open-source community platform built as a practical Java project for publishing and discovering technical content. Its stack includes Spring Boot, MyBatis-Plus, MySQL, Redis, Elasticsearch, MongoDB, RabbitMQ, and Docker. The application supports complete workflows for publishing, searching, commenting on, and measuring articles and tutorials. Its modular structure separates shared models, reusable components, business services, frontend resources, and web entry points. Core... -
PRTG Catches Network Issues Before They Cause DowntimeReactive troubleshooting usually means hearing about a problem from frustrated users, not your monitoring tool. PRTG sets threshold-based alerts across devices, servers and applications, notifying your team by email, SMS or push the moment a metric crosses a set limit. That means catching a failing disk or overloaded server before it becomes an outage and getting time back from firefighting. Start a free trial and set your first alerts today.
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mall
Set of ecommerce systems, including the front-end and back-end
mallThe project is an e-commerce system, including a front-end mall system and a back-end management system, implemented based on SpringBoot+MyBatis, and deployed with Docker containers. The front-end mall system includes homepage portal, product recommendation, product search, product display, shopping cart, order process, member center, customer service, help center and other modules. The background management system includes modules such as product management, order management, member management, promotion management, operation management, content management, statistical reports, financial management, authority management, and settings. -
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Alink
Alink is the Machine Learning algorithm platform based on Flink
Alink is Alibaba’s scalable machine learning algorithm platform built on Apache Flink, designed for batch and stream data processing. It provides a wide variety of ready-to-use ML algorithms for tasks like classification, regression, clustering, recommendation, and more. Written in Java and Scala, Alink is suitable for enterprise-grade big data applications where performance and scalability are crucial. It supports model training, evaluation, and deployment in real-time environments and integrates seamlessly into Alibaba’s cloud ecosystem. -
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Similarity
Text similarity calculation Toolkit for Java
...It includes approaches such as edit distance, cosine similarity, Euclidean distance, Jaccard similarity, Jaro distance, Jaro-Winkler distance, Manhattan distance, SimHash with Hamming distance, and Sørensen-Dice coefficient. It also supports Java dependency integration through Maven or Gradle workflows. It is useful for Chinese NLP projects, search features, duplicate detection, recommendation systems, and text analysis experiments. -
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MorganaXProc (Implements XProc 1.0)
A Java implementation of XProc: An XML Pipeline Language
...The current version is 1.0.x. It is very close to the recommendation with all related tests of the XProc Test Suite passed. -
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Seldon Server
Machine learning platform and recommendation engine on Kubernetes
Seldon Server is a machine learning platform and recommendation engine built on Kubernetes. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Core focuses purely on deploying a wide range of ML models on Kubernetes, allowing complex runtime serving graphs to be managed in production. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Format-Preserving Encryption
Format-Preserving Encryption Library for Java
This package implements the FF1, FF3, and FFX algorithms and the A2 and A10 parameter sets for format-preserving encryption. The FF1 and FF3 methods for format-preserving encryption are implementations of NIST Special Publication 800-38G, Recommendation for Block Cipher Modes of Operation: Methods for Format-Preserving Encryption. The FFX algorithm and A2 and A10 parameter sets are implementations of "The FFX Mode of Operation for Format-Preserving Encryption," by Mihir Bellare, Phillip Rogaway, and Terence Spies. For more information see the README.txt and package-info.java files in the source. -
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Bilibili Android Client
An unofficial bilibili client for Android
The realization of six modules on the homepage, recommendation, drama, live broadcast, follow, partition, and discovery. Video details interface, video comments, video playback completed by ijkplayer, and barrage functions implemented by the flame barrage library. The realization of the fan drama module, including the topic details interface, the fan drama details interface, the fan drama broadcasting table, the fan drama index, the new fan serial, and the new fan by season. -
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LibRec
Leading Java Library for Recommender Systems
LibRec is a Java library for recommender systems (Java version 1.7 or higher required). It implements a suit of state-of-the-art recommendation algorithms, aiming to resolve two classic recommendation tasks: rating prediction and item ranking. -
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easyrec is a recommender system that aims for easy integration of recommendations into web applications. It has a web based admin tool, and its recommendation engine is accessible through a REST API, providing methods like 'other users also bought'
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TER implements the CCSDS Recommendation for Image Data Compression (CCSDS 122.0-B-1). TER also adds new features to the Recommendation. TER is designed and programmed with the aim to provide a good basis to test and develop the CCSDS Recommendation.
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INACTIVE STATUS: The Recommendation Tracker is not actively being developed. SUMMARY: The Recommendation Tracker facilitates consistent standardized (XCCDF, OVAL, CCE, CPE) guidance authoring through an established format for creating, developing, and tracking all information pertinent to security guide and benchmark generation.
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iTEC SDE
A recommender system for Educational Resources (iTEC Project)
...Functionalities provided by this API can be classified into three categories: A) Technical Localisation: methods in this category support the identification of Learning Stories and Learning Activities that may be implemented in a school according to the technological resources available there. B) Resource Planning: collects methods targeted to support the location and recommendation of resources useful to implement a Learning Story / Learning Activity. C) Validation: -
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SimCampus. Social Simulation
Recommendation system of extracurricular activities for students
SimCampus is a software programmed in java. The goal of this project has been the development of a simulation tool for recommendation system of extracurricular activities on a university campus. This simulation provides the advantage to avoid problems that may develop during a real implementation and operation of this system. It is simulated a recommendation system of extracurricular activities for students of a university campus considering their free time (time between classes) and preferences (interest, hobbies). ... -
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MyIGo
IGO helps you find want you need!
...UI Design to enhance the interaction between user and app ,offering a cool user experience interaction between the user and the business part. 2. Combine context awareness technology to analyse the user’s need. 3. Make the better recommendation of shops to the customer. -
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The Idealize Recommendation Framework supports the development of recommender systems. We have devised a set of requirements all recommender systems must address, an architecture for those requirements, a technical vocabulary and a production model.
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This project has the objective of defining a recommendation layer that will communicate with several LMS like .LRN, Moodle, etc.
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The Benchmark Editor enhances and simplifies the creation and editing of benchmark documents written in standard languages such as XCCDF and OVAL. NOT CURRENTLY MAINTAINED: please see the Recommendation Tracker for a similar, actively maintained tool
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The project consist in an open source implementation of the W3C Recommendation of the XML Key Management Specification 2.0 XKMS 2.0. It is compound of a XKMS Server and a Client API to access to the Server via Web Service.
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The metabolomics standards initiative (msi) will develop a Core Information for Metabolomics Reporting (CIMR) recommendation and a more formal and semantically defined corresponding ontology (msi-ontology).
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Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
