专注于解决推荐领域与搜索领域的两个核心问题:排序预测(Ranking)和评分预测(Rating). 为相关领域的研发人员提供完整的通用设计与参考实现. 涵盖了70多种排序预测与评分预测算法,是最快最全的Java推荐与搜索引擎.

Sux4J is an effort to bring succinct data structures to Java.

Autorank is a Spigot/Bukkit plugin for automatically ranking players based on requirements

Bukkit plugin for customizing the sidebar of the scoreboard feature from minecraft

EARS is a free and open-source Java-based framework for ranking, developing, and experimenting with single- and multi-objective evolutionary algorithms

Fair search elasticsearch plugin

this repo for learning search engine such as elk and web search engine concept such as google to grow knowledge of software engineering

An object-oriented Java implementation of the Weng-Lin ranking system, providing accurate skill-based ranking for multiplayer games.

Java framework for Preference Learning

Apache Pig UDFs for ranking (ndcg, mrr, jaccard coefficient, cosine similarity, rank-biased overlap)

Crawler based search engine that demonstrates the main features of a search engine (web crawling, indexing and ranking) and the interaction between them.

Linked Open Data-based knowledge panel built during a seminar at Karlsruhe Institute of Technology

Ranky is a Discord bot that creates custom League of Legend rankings to compete with other people while playing soloQ/duoQ. This application is inspired in the SoloQChallenge done by twitch streamer ElmiilloR and pretends to extend the possibility to create custom challenges in smaller communities.

A web-search-engine developed harnessing Java with features such as web-crawling, searching, ranking, spell-checking etc.

[Retired] National football team ranking web application built with Spring, Hibernate, React, and MobX

Mirror of https://sourceforge.net/p/lemur/code/HEAD/tree/RankLib/

Disparate Exposure in Learning To Rank for Java

ClimbingCompRanking allows you to create a ranking for your climbing events, it supports discipline like speed, bouldering or lead and also the combined.

API para classificação por votos dos usuários.

In this project, most relevant documents for user queries are retrieved using TF-IDF.