Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Talent recommendation method and device

A recommendation method and talent technology, applied in the field of data retrieval, can solve problems such as low flexibility and accuracy, fixed number of topics, etc., to achieve the effect of improving accuracy and flexibility, and avoiding large topic redundancy

Active Publication Date: 2020-08-04
三螺旋大数据科技(昆山)有限公司
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The above three methods all belong to simple topic evolution. When using the above methods for topic evolution, it is easy to cause the problem that the number of topics in different time windows is fixed, which in turn leads to low flexibility and accuracy in talent recommendation based on popular topics.
[0004] No effective solution has been proposed for the above problems of low flexibility and accuracy of talent recommendation

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Talent recommendation method and device
  • Talent recommendation method and device
  • Talent recommendation method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] see figure 1 The flow chart of the first talent recommendation method is shown, and the method includes the following steps:

[0030] Step S102, acquiring text data from a preset database; wherein, the text data includes at least one of articles, papers and webpage texts;

[0031] For example, the above-mentioned database can be a comprehensive database covering multiple fields (including industry, agriculture, medicine, etc.) A professional database in the form of literature. When using a professional database for processing, you can get hot topics in the current field and their corresponding talents.

[0032] Step S104, classify the text data according to the publishing time of the text data;

[0033] According to the development level of the current field, the classification standard can be set in advance, that is, the classification time period can be set; for example, the text data can be classified according to the release year, quarter or month of the text dat...

Embodiment 2

[0045] see figure 2 The flow chart of the second talent recommendation method is shown. This method is implemented on the basis of the talent recommendation method provided in Embodiment 1. The method includes the following steps:

[0046] Step S202, acquiring text data from a preset database; wherein, the text data includes at least one of articles, papers and webpage texts;

[0047] Step S204, extracting the publishing time of the text data;

[0048] Step S206, matching the publishing time with a plurality of preset time periods, and determining the time period to which the text data belongs according to the matching result;

[0049] For example, if one year is used as the time period and the theme of each year in the last ten years is obtained, the above multiple time periods can be 2017, 2016, ... until 2008, a total of 10 time periods; determine the release time of the text data The specific time period it belongs to; for example, the time period published on June 22, ...

Embodiment 3

[0061] see image 3 The flow chart of the third talent recommendation method shown, which is implemented on the basis of the talent recommendation method provided in Embodiment 1 or 2; this method expands the traditional topic model into a more specific topic level by using the HDP model , so as to solve the problem of using only the fixed number of topics in the time window in LDA, the method includes the following steps:

[0062] Step S302, classifying academic articles such as papers according to time periods (also called time windows);

[0063] Step S304, using HDP to extract topics from the collection of articles in each time period;

[0064] Step S306, obtaining popular topics in the current time period according to the evolution process of topics;

[0065] Step S308, selecting talents from the authors of articles corresponding to popular topics for recommendation.

[0066] From the above steps S302 to S308, it can be seen that the method first discretizes academic ar...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a talent recommendation method and apparatus. The method comprises the steps of obtaining text data from a preset database, wherein the text data at least comprises one of articles, papers and webpage texts; according to release time of the text data, classifying the text data; by adopting a layered Dirichlet process, performing topic extraction processing on the text data corresponding to each type; according to a processing result, obtaining hot topics of a current time period; and recommending authors of the text data corresponding to the hot topics as talents. According to the method and the apparatus, the topic in each time period and the current hot topics can be flexibly and accurately obtained, so that the problem of high extracted topic redundancy or topic omission caused by manual setting of a topic number is avoided, and the accuracy and flexibility of recommending the talents according to the hot topics are improved.

Description

technical field [0001] The invention relates to the technical field of data retrieval, in particular to a talent recommendation method and device. Background technique [0002] In order to obtain the evolution of topics over time, the following three methods are usually used in the prior art: First, combine time information into the LDA model, and introduce time factors into the LDA model, so that each topic adds a time attribute, and then Express the distribution of topics at different times; the second is to first use LDA to obtain the topics, and then retrieve and quantify the distribution of topics in time; the third is to discretize the text to the corresponding time windows, and then according to each time window Topic extraction from text collections above. [0003] The above three methods all belong to simple topic evolution. When using the above methods for topic evolution, it is easy to cause the problem that the number of topics in different time windows is fixed...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F16/9535
CPCG06F16/35G06F16/9535
Inventor 李微王泽华吴志成张健徐衔郭晓茹
Owner 三螺旋大数据科技(昆山)有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com