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Scientific and technical literature quoting number predicting method based on time sequence

A technology of time series and forecasting method, applied in the computer field, can solve the problems that affect the evaluation of scientific and technological contribution of scientific and technological literature, and it is difficult to obtain citations.

Inactive Publication Date: 2015-03-25
DALIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, the statistics of the number of citations are easily limited by the current time point, and it is difficult to obtain the citations in the future time period, which in turn affects the evaluation of scientific and technological contributions of scientific and technological literature

Method used

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  • Scientific and technical literature quoting number predicting method based on time sequence
  • Scientific and technical literature quoting number predicting method based on time sequence
  • Scientific and technical literature quoting number predicting method based on time sequence

Examples

Experimental program
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Effect test

Embodiment Construction

[0035] Step 1: Collect the publication year, month and index list of each document, and count the number of citations of each document in each month after publication.

[0036] Use the database to search the index list of each document, according to the label and publication year and month of each document in the database, count the specific time and number of times the document was cited, and obtain the number of citations per month after each document was published.

[0037] Traverse each document in the collection, read the publication time (time) and the citation label (refid) in the index list 1 , refid 2 ,...,refid n ). For each citation label refid i , citing refid every month since publication i The number of documents in is the number of citations for that month.

[0038] Step 2: Take the month as the unit, calculate the total number of citations and the total number of cited documents of all documents to be analyzed each month, and divide them to obtain the aver...

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Abstract

The invention relates to a scientific and technical literature quoting number predicting method based on a time sequence. The predicting method includes the steps that statistics is carried out on scientific and technical literature quoting numbers, and then average literature quoting numbers of all the months are calculated; in combination with the average literature quoting numbers of all the months, the quoting numbers of the corresponding months are processed in a normalization mode to obtain the quoting time sequence; cluster analysis is carried out according to the time sequence, and a quoting number model with the optimal predicting performance is obtained through dividing training sets and verifying sets, building a regression model and performing error analysis; according to similarity analysis of literature to be predicted and time sequences of various kinds of literature, the class with the highest similarity is obtained, and the quoting number, in the next month, of the literature to be predicted is obtained through the model with the optimal predicting performance. The quoting conditions of each piece of published literature can be automatically analyzed, the average literature quoting numbers of all the months are obtained, different quoting modes of the literature are excavated through clustering, and then the future quoting number is predicted according to the existing time sequence of the literature to be predicted.

Description

technical field [0001] The invention belongs to the technical field of computers and relates to a method for predicting the number of citations of scientific and technological documents based on time series. Background technique [0002] The number of citations refers to the number of times a scientific literature is cited by other literature within a specified period of time, and it is an important method for evaluating the influence and quality of scientific literature. However, the statistics of the number of citations are easily limited by the current time point, and it is difficult to obtain the citations in the future time period, which in turn affects the evaluation of the contribution of scientific and technological literature to science and technology. It is urgent to provide a method for predicting the number of citations of scientific and technological documents based on time series, to identify potential documents faster, and to promote scientific research and th...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/2462
Inventor 姚念民李梦阳谭国真战福瑞
Owner DALIAN UNIV OF TECH
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