Search Results for "recommendation system php"

Taste Skill is a project focused on structured skill development, likely combining curated content, learning paths, and interactive elements to help users build expertise in specific domains. It appears to emphasize personalized or modular learning, allowing users to explore topics based on interest or progression level. The platform may integrate recommendation systems or categorized content to guide users through a learning journey efficiently. Its design suggests an emphasis on accessibility and practical skill acquisition rather than purely theoretical knowledge. The repository likely includes tools or interfaces that support content organization, tracking, and user engagement. Overall, it positions itself as a lightweight, adaptable system for continuous learning and skill discovery.

The Hydroponic Automation Platform Initiative (HAPI) develops and provides hardware and software components for automating food production using hydroponic, aquaponics, and precision agriculture techniques. High-yield production in urban settings is one of the primary goals. Artifacts include hardware design (mainly Arduino-based), firmware, management software and reporting modules.

This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else? Status: PreAlpha, so...

Photios attempts to aggregate, normalize, analyze, and present system log data in an accessible, searchable, and sortable fashion.

Prastava (hindi for "suggestion") - a generic open source recommendation system built entirely in ruby. This system gives recommendations to users on the basis of their past likings (ratings of items) and an item file(for content based similarity).

This is a recommendation system built in ruby which is able to generate recommendations for user inputted data (a text file and a ratings matrix). It works on a hybrid model of collaborative filtering and content based filtering.

Main task is automating the creation of simulation models of complex model. The originalities of proposed software are explicit representation of conceptual model in the concept – attribute – relation form and applying expert system approach to transform designed ontology into agent model. Researchers develop the structure and behavior of agents using declarative approach. Web: https://84.237.20.67/RFFI/Main.php