Employment recommendation method and system based on multi-source data analysis under Internet mode

Abstract

The invention discloses an employment recommendation method based on multi-source data analysis in the Internet mode, including: acquiring student multi-source data and enterprise multi-source data; cleaning and associating the student multi-source data to generate a student professional ability model The key data of students, cleans and correlates the multi-source data of the enterprise to generate the key data of the enterprise for the talent demand model of the enterprise; builds the professional ability model of students according to the key data of students, and constructs the talent demand model of the enterprise according to the key data of the enterprise; the professional ability of students The model matches the talent demand model of the enterprise, recommending jobs for students and recommending job resumes for enterprises. The invention also discloses an employment recommendation system based on multi-source data analysis in the Internet mode. With the present invention, accurate push between talents and positions can be realized through multi-dimensional data association, logical judgment and error correction, deep data mining, and recommendation algorithms.

Description

technical field [0001] The present invention relates to the field of big data technology, in particular to an employment recommendation method based on multi-source data analysis in Internet mode and an employment recommendation system based on multi-source data analysis in Internet mode. Background technique [0002] In the context of the rapid development of big data technology, the value of data is becoming more and more important. In massively parallel processing (MPP) databases, data mining, distributed file systems (HDFS), distributed databases (hive, Hbase), cloud computing platforms, While Internet and scalable storage system technologies are mature and applied on a large scale, all industries are pursuing and researching how to effectively use data, so that existing data assets can be analyzed and mined to enable enterprises or institutions to have stronger decision-making power and insights Capacity and process optimization capabilities to adapt to high growth rate...

AI Technical Summary

Problems solved by technology

[0004] The era of large amounts of data has also brought about the problem of low information value density. Users need to spend a lot of time screening valuable information, thereby reducing the efficiency of work; at this time, the technical field is exploring the use of technology to realize information Efficient screening and recommendation, so as to achieve accurate matching and recommendation of required information; and continue to explore the application of recommendation algorithms and technologies in actual scenarios

[0005] At present, the difficulty of employment of college students in my country has become a major concern of the country and society. Using big data technology to achieve accurate two-way push of graduates and corporate positions has become a rigid demand; currently there is no real product on the market to achieve this function. Simple keyword matching or information retrieval technology relying on single data source analysis is faced with problems such as low efficiency and low accuracy

Images