基于协同过滤的大学生就业推荐算法研究
Research on Employment Recommendation Algorithm of College Students Based on Collaborative Filtering
付洋 1周勇 1马凯2
作者信息
- 1. 重庆工程学院,重庆 400056
- 2. 重庆工程学院大数据技术与应用研究所,重庆 400056
- 折叠
摘要
面对当前严峻的就业形势,提出一种基于加权余弦相似度和ALS模型的招聘推荐算法,采用APH层次分析法评估用户画像与招聘信息之间的权重关系,利用加权的余弦相似度算法对其进行评分,运用Spark ML的ALS算法对相似度矩阵进行训练,建立用户-招聘信息的推荐模型.经过实验验证,提出的招聘推荐模型在招聘信息匹配及推荐准确性方面表现出较好的效果,这一研究成果可为解决大学生就业难题提供新方法和新方向.
Abstract
In the current severe employment situation,the study proposes a recruitment recommendation algorithm based on weighted cosine similarity and ALS model,evaluates the weight relationship between user profiles and recruitment information with APH,scores it with the weighted cosine similarity algorithm,trains the similarity matrix with Spark ML ALS algorithm,and establishes a recommendation model for user-recruitment information.Through experimental verification,the proposed recruitment recommendation model has a good effect on recruitment information matching and recommendation accuracy.This research result can provide a new method and direction for solving the problem of college students'employment.
关键词
就业推荐/加权余弦相似度/ALS算法/APH/SparkKey words
Employment recommendation/Weighted cosine similarity/ALS algorithm/APH/Spark引用本文复制引用
出版年
2024
NETL
NSTL
万方数据