Recommending people in social networks using data mining

Alsaleh, Slah (2013) Recommending people in social networks using data mining. PhD thesis, Queensland University of Technology.


This thesis improves the process of recommending people to people in social networks using new clustering algorithms and ranking methods. The proposed system and methods are evaluated on the data collected from a real life social network. The empirical analysis of this research confirms that the proposed system and methods achieved improvements in the accuracy and efficiency of matching and recommending people, and overcome some of the problems that social matching systems usually suffer.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

654 since deposited on 13 Aug 2013
144 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 61736
Item Type: QUT Thesis (PhD)
Supervisor: Nayak, Richi & Xu, Yue
Keywords: Recommendation, Social networks, Community detection, Clustering, Constraints, Ranking
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 13 Aug 2013 03:05
Last Modified: 07 Sep 2015 05:13

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page