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A Paper Recommendation Method Based on Golden Citation Algorithm

A recommendation method and paper technology, applied in the field of paper recommendation based on the golden citation algorithm, can solve the problem that the quality of the paper cannot be fully reflected

Active Publication Date: 2019-05-14
北京市科学技术情报研究所
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Problems solved by technology

The application only considers the similarity of citations between the papers or the similarity of the content of the papers, but it does not fully reflect the quality of the papers

Method used

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  • A Paper Recommendation Method Based on Golden Citation Algorithm
  • A Paper Recommendation Method Based on Golden Citation Algorithm
  • A Paper Recommendation Method Based on Golden Citation Algorithm

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Embodiment 1

[0065] In the embodiment of the present invention, a method for sorting papers based on the Golden Citation Algorithm is introduced, which includes the following steps: first, select the paper group range in the paper database;

[0066] Second, construct an initial citation network model using the mutual citation relationships of papers in the selected paper population;

[0067] Then, calibrate the citation attribute of the paper in the initial citation network model, and introduce the self-citation coefficient of the paper to revise the number of citations to generate a group of self-citing revised papers;

[0068] Finally, the iterative screening method is used to narrow down the scope of the self-citing revision paper group layer by layer, and the papers screened out at each layer form the paper group and are arranged in descending order.

[0069] In this embodiment, the group of papers can be defined according to subject, field, subject and / or age, or according to a set re...

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Abstract

The invention discloses a golden citation algorithm-based paper recommendation method. The method comprises the following steps of: firstly, selecting a paper group range in a paper database; secondly, constructing an initial citation network model according to mutual citation relationships between papers in the selected paper group; thirdly, demarcating citation attributes of papers in the initial citation network model, and revising a citation frequency through a self-citation coefficient so as to generate a self-citation revising paper group; and finally, iteratively narrowing the range ofthe self-citation revising paper group until a result is converged, so as to obtain a golden citation paper. Through demarcating citation attributes of papers, interferences of self-citation in the paper citation relationships are eliminated; and paper groups are recursively narrowed according to self-citation revising citation frequencies, so that the interferences of low-quality and low-efficiency cited papers are eliminated, and users can rapidly and correctly retrieve high-quality papers.

Description

technical field [0001] The invention belongs to the technical field of big data paper retrieval and recommendation, and in particular relates to a paper recommendation method based on a golden citation algorithm. Background technique [0002] Based on different recommendation information, paper recommendation is mainly divided into content-based recommendation, collaborative filtering-based recommendation, social recommendation and hybrid model recommendation. In the recommendation system of papers, there is also a special kind of recommendation based on citations. However, it is very difficult to obtain high-quality scientific and technological papers from a large number of literature materials with mixed quality and quality. How to effectively and automatically evaluate The quality of scientific papers has become a research topic. The number of citations is an objective and intuitive indicator to measure the quality of papers. Paper citations include the author’s self-cit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9535
Inventor 吴晨生杜丽萍李梦辉刘静黄裕荣
Owner 北京市科学技术情报研究所
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