Predicting missing links via local information

Article Properties

Language

English
DOI (url)

10.1140/epjb/e2009-00335-8
Publication Date

2009/10/01
Journal

The European Physical Journal B
Indian UGC (Journal)
Refrences

66
Citations

889
Tao Zhou
Linyuan Lü
Yi-Cheng Zhang

Cite

Zhou, Tao, et al. “Predicting Missing Links via Local Information”. The European Physical Journal B, vol. 71, no. 4, 2009, pp. 623-30, https://doi.org/10.1140/epjb/e2009-00335-8.

Zhou, T., Lü, L., & Zhang, Y.-C. (2009). Predicting missing links via local information. The European Physical Journal B, 71(4), 623-630. https://doi.org/10.1140/epjb/e2009-00335-8

Zhou T, Lü L, Zhang YC. Predicting missing links via local information. The European Physical Journal B. 2009;71(4):623-30.

Journal Categories

Science

Physics

Technology

Chemical technology

Technology

Electrical engineering

Electronics

Nuclear engineering

Materials of engineering and construction

Mechanics of materials

Refrences

Refrences Analysis

Category	Category Repetition
Science: Physics	29
Science: Science (General)	8
Science: Mathematics: Instruments and machines: Electronic computers. Computer science	6
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication	4
Science: Chemistry: Physical and theoretical chemistry	3

The category Science: Physics 29 is the most frequently represented among the references in this article. It primarily includes studies from Physical Review E The chart below illustrates the number of referenced publications per year.

Refrences used by this article by year

Citations

Citations Analysis

Category	Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science	287
Science: Physics	273
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics	140
Science: Science (General): Cybernetics: Information theory	137
Science: Mathematics	129

The first research to cite this article was titled EFFECTS OF USER'S TASTES ON PERSONALIZED RECOMMENDATION and was published in 2009. The most recent citation comes from a 2024 study titled EFFECTS OF USER'S TASTES ON PERSONALIZED RECOMMENDATION . This article reached its peak citation in 2022 , with 127 citations.It has been cited in 257 different journals, 17% of which are open access. Among related journals, the Physica A: Statistical Mechanics and its Applications cited this research the most, with 111 citations. The chart below illustrates the annual citation trends for this article.