REPRESENTING A CONTENT-BASED LINK PREDICTION ALGORITHM IN SCIENTIFIC SOCIAL NETWORKS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SOLAIMANNEZHAD HOSNA; FATEMI OMID

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Information Systems and Telecommunication Year:2017 | Volume:5 | Issue:3 Page(s): 146-154

Download Full-Text

View:

417

Download:

160

Cites:

Information Journal Paper

Title

REPRESENTING A CONTENT-BASED LINK PREDICTION ALGORITHM IN SCIENTIFIC SOCIAL NETWORKS

Author(s)

SOLAIMANNEZHAD HOSNA | FATEMI OMID | Issue Writer Certificate

Keywords

LINK PREDICTION

SOCIAL NETWORKS

CONTENT-BASED

INTEREST

Abstract

Predicting collaboration between two authors, using their research INTERESTs, is one of the important issues that could improve the group researches. One type of SOCIAL NETWORKS is the co-authorship network that is one of the most widely used data sets for studying. As a part of recent improvements of research, far much attention is devoted to the computational analysis of these SOCIAL NETWORKS. The dynamics of these networks makes them challenging to study. LINK PREDICTION is one of the main problems in SOCIAL NETWORKS analysis. If we represent a social network with a graph, LINK PREDICTION means predicting edges that will be created between nodes in the future. The output of LINK PREDICTION algorithms is using in the various areas such as recommender systems. Also, collaboration prediction between two authors using their research INTERESTs is one of the issues that improve group researches. There are few studies on LINK PREDICTION that use content published by nodes for predicting collaboration between them. In this study, a new LINK PREDICTION algorithm is developed based on the people INTERESTs. By extracting fields that authors have worked on them via analyzing papers published by them, this algorithm predicts their communication in future. The results of tests on SID dataset as co-author dataset show that developed algorithm outperforms all the structure-based LINK PREDICTION algorithms. Finally, the reasons of algorithm’s efficiency are analyzed and presented.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

SOLAIMANNEZHAD, HOSNA, & FATEMI, OMID. (2017). REPRESENTING A CONTENT-BASED LINK PREDICTION ALGORITHM IN SCIENTIFIC SOCIAL NETWORKS. JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST), 5(3), 146-154. SID. https://sid.ir/paper/332742/en

Vancouver: Copy

SOLAIMANNEZHAD HOSNA, FATEMI OMID. REPRESENTING A CONTENT-BASED LINK PREDICTION ALGORITHM IN SCIENTIFIC SOCIAL NETWORKS. JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST)[Internet]. 2017;5(3):146-154. Available from: https://sid.ir/paper/332742/en

IEEE: Copy

HOSNA SOLAIMANNEZHAD, and OMID FATEMI, “REPRESENTING A CONTENT-BASED LINK PREDICTION ALGORITHM IN SCIENTIFIC SOCIAL NETWORKS,” JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST), vol. 5, no. 3, pp. 146–154, 2017, [Online]. Available: https://sid.ir/paper/332742/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops