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Method for personally recommending software projects for open source communities

A technology for software projects and recommended methods, applied in software maintenance/management, program control devices, demand analysis, etc., can solve problems such as low accuracy, aggravate human resource waste, and developers' distrust, to improve efficiency and reduce The effect of the threshold

Active Publication Date: 2016-12-07
YANGZHOU UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

At the same time, if a developer is good at one development direction, it is also likely to be able to speak multiple languages ​​in this development direction.
This kind of coarse-grained recommendation is not only not accurate, but also leaves an impression of distrust to developers, further aggravating the waste of human resources

Method used

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  • Method for personally recommending software projects for open source communities
  • Method for personally recommending software projects for open source communities
  • Method for personally recommending software projects for open source communities

Examples

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Embodiment Construction

[0029] Technical thinking of the present invention is:

[0030] The TF-IDF feature extraction is performed on the project content, combined with the user's evaluation of known projects, and similar projects that combine the user's personality and project needs are recommended to the user. When recommending related items, on the one hand, according to user personality, the candidate recommendation results are calculated through ALS collaborative filtering. On the other hand, each item feature is calculated using word frequency-inverse text frequency, and candidate recommendation results are calculated according to the similarity of item features. Then linearly combine the two recommendation results, perform filtering and ranking, and generate recommendation results. Finally, the word frequency-inverse text frequency is used as a label to make a reasonable explanation for the recommendation results. Such as figure 1 shown.

[0031]Term Frequency-Inverse Document Frequency (T...

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Abstract

The invention relates to a method for personally recommending software projects for open source communities. TF-IDF (term frequency-inverse document frequency) characteristics of project contents are extracted and are combined with known project evaluation of users, the similar projects which are combined with personality and project requirements of the users are recommended, candidate recommendation results are computed for the personality of the users by means of ALS (alternating least squares) collaborative filtering, each project characteristic is computed by the aid of term frequencies-inverse document frequencies, candidate recommendation results are computed according to the similarity of the project characteristics, recommendation results for the personality of the users and recommendation results for the project characteristics are linearly combined with one another and are filtered and ranked, and accordingly recommendation results can be generated. The method has the advantages that shortcomings of incapability of completely embodying project characteristics, coarse granularity, low accuracy and the like of existing recommendation technologies can be overcome by the aid of the method; the similar projects for the personality of the users and the project contents can be recommended from angles of known project scores of the users and known project contents, accordingly, the project contents similar to projects currently developed by the users can be recommended, the method has personal recommendation functions and can bring reference or reuse convenience for the users, and the project searching efficiency of developers can be improved.

Description

technical field [0001] The invention belongs to the field of software maintenance recommendation, in particular to a software project personalized recommendation method for open source communities. Background technique [0002] Due to the large number of software projects, according to the statistics of Github, the largest open source software community at present, as of 2016, Github has more than 14 million registered users and 35 million code warehouses. As of 2014, there are 68 warehouses on Github with more than 10,000 stars, 10 warehouses with more than 8,000 forks, and 944,872 warehouses with more than 1 forks. It can be seen that the distributed development of software has become a trend. Developers have different personalities and have different needs for projects. If there is no good recommendation mechanism, there will be serious problems such as waste of human resources. The recommendation task of recommending similar items based on user personality and item need...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/44
CPCG06F8/10G06F8/70
Inventor 孙小兵徐文远李斌李云
Owner YANGZHOU UNIV
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