liang-huilin's starred repositories

springboot-vue-pytorch

keypoints: java, springboot, vue3, pytorch, yolov5, deepsort

Language:PythonLicense:MITStargazers:47Issues:0Issues:0

Bug-Triaging-and-Developer-Recommendation-System

This project assigns reported bugs on Chromium bug repository to the developers using Data-driven Machine Learning Algorithm and NLTK for removing stop words. Developer Recommendation System automates the bug triaging process using three different approaches based on correlation method, DLG Algorithm and cosine similarity.It also generates the developers ranking for a particular bug reported in all the approaches.

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SDABT

S-DABT: Schedule and Dependency-Aware Bug Triage in Open-Source Bug Tracking Systems

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Automated-Bug-Triaging-to-Developer

For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming bugs is a time consuming task. Major part of bug triaging is the assignment of a bug report to a developer with the appropriate expertise, who can resolve/fix the bug without reassigning to some other developer. We present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report based on the identified software component the bug may reside in, obtained from the short description of the bug report. Our work is first to examine the impact of multiple machine learning dimensions( classifiers and training history) along with the ranked list of developers for prediction accuracy in bug assignment. We validate our approach on Eclipse Bugzilla covering 2,868,000 bug reports consisting of 253 components. We demonstrate that our techniques can achieve up to 93% prediction accuracy in bug assignment and significantly reduce the aberrant assignment of bugs. We compared the prediction time for our dataset using various algorithms such as Naive Bayes Text Classifier, Multinomial Naive Bayes and Linear SVM. We arrived at a conclusion that SVM provides higher prediction time and less learning time.

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ML-GCN

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.

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GraphEmbedding

Implementation and experiments of graph embedding algorithms.

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bank_interview

:bank: 银行笔试面试经验分享及资料分享(help you pass the bank interview, and get a amazing bank offer!)

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leetcode-javascript

:beers: 喝杯小酒,一起做题。前端攻城狮从零入门算法的宝藏题库,根据知名算法老师的经验总结了 100+ 道 LeetCode 力扣的经典题型 JavaScript 题解和思路。已按题目类型分 label,一起加油。

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leetcode

:seedling: Javascript solutions to problems on LeetCode

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bytedance-apm-group

字节跳动 APM 团队预备招聘社群,来一起聊聊大厂面试经验、简历如何编写、技术……

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HelloGitHub

:octocat: 分享 GitHub 上有趣、入门级的开源项目。Share interesting, entry-level open source projects on GitHub.

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vue-admin-template

a vue2.0 minimal admin template

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fe-agorithm-interview

前端算法面试常考题目解析。

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fe-interview

前端面试每日 3+1,以面试题来驱动学习,提倡每日学习与思考,每天进步一点!每天早上5点纯手工发布面试题(死磕自己,愉悦大家),6000+道前端面试题全面覆盖,HTML/CSS/JavaScript/Vue/React/Nodejs/TypeScript/ECMAScritpt/Webpack/Jquery/小程序/软技能……

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33-js-concepts

:scroll: 每个 JavaScript 工程师都应懂的33个概念 @leonardomso

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awesome-coding-js

用JavaScript实现的算法和数据结构,附详细解释和刷题指南

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CS-Notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

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countUp.js

Animates a numerical value by counting to it

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PPTist

An online presentation application that replicates most of the commonly used features of Microsoft Office PowerPoint, allowing for the editing and presentation of PPT online. It also supports the export of PPT files.

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new-grad-positions

本项目旨在收集 2023 届互联网公司校招和实习的最新官方招聘信息,帮助在校生消除信息不对称带来的劣势,欢迎贡献 👏🏻。

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vue-cli3.0-vueadmin

基于vue-cli3.0+vue+elementUI+vuex+axios+权限管理的后台管理系统

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async-validator

validate form asynchronous

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vue-netease-music

🎵 基于 Vue2、Vue-CLI3 的高仿网易云 mac 客户端播放器(PC) Online Music Player

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Vue3-TS-CMS

(感谢coderwhy老师)基于Vue3、TS、Vuex、VueRouter、Element-plus、ECharts、Webpack等后台管理系统解决方案。

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cloud-app-admin

cloud-app-admin 使用了最新的 Vue3.2 + Vite3 + Element-Plus + TypeScript 等主流技术开发。

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pygcn

Graph Convolutional Networks in PyTorch

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awesome-gcn

resources for graph convolutional networks (图卷积神经网络相关资源)

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recommenders

Best Practices on Recommendation Systems

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GNN-in-RS

GNN in Recommendation System (ACM Computing Surveys 2022)

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ranking

Learning to Rank in TensorFlow

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