Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms
Nowadays, social networks are becoming more popular, so the number of their users and their information is growing accordingly. Therefore, we need a recommender system that uses all kinds of available information to create highly accurate recommendations. Regarding the general structure of these rec...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Iran Telecom Research Center
2018-03-01
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| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-232-en.html |
| _version_ | 1811169207387160576 |
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| author | Paria Dashtizadeh Ali Harounabadi |
| author_facet | Paria Dashtizadeh Ali Harounabadi |
| author_sort | Paria Dashtizadeh |
| collection | DOAJ |
| description | Nowadays, social networks are becoming more popular, so the number of their users and their information is growing accordingly. Therefore, we need a recommender system that uses all kinds of available information to create highly accurate recommendations. Regarding the general structure of these recommender systems, one criterion is first chosen to calculate the similarity between users and then people who are assumed to have great similarity are proposed to each other as friend. These similar criteria can calculate users’ similarity with regard to topological structure and some properties of graph vertices. In this paper, the properties that are required for clustering are extracted from users’ profile. Finally, by combining the similarity criteria of mean measure of divergence (MMD), cosine, and Katz, different aspects of the problem including graph topology, frequency of user interaction with each other, and normalization of the same scoring method are considered. |
| first_indexed | 2024-04-10T16:39:39Z |
| format | Article |
| id | doaj.art-1576f268fbc04232a2f01428177a1735 |
| institution | Directory Open Access Journal |
| issn | 2251-6107 2783-4425 |
| language | English |
| last_indexed | 2024-04-10T16:39:39Z |
| publishDate | 2018-03-01 |
| publisher | Iran Telecom Research Center |
| record_format | Article |
| series | International Journal of Information and Communication Technology Research |
| spelling | doaj.art-1576f268fbc04232a2f01428177a17352023-02-08T07:56:49ZengIran Telecom Research CenterInternational Journal of Information and Communication Technology Research2251-61072783-44252018-03-011015661Recommending Friends in Social Networks By Users\' Profiles And Using Classification AlgorithmsParia Dashtizadeh0Ali Harounabadi1 Nowadays, social networks are becoming more popular, so the number of their users and their information is growing accordingly. Therefore, we need a recommender system that uses all kinds of available information to create highly accurate recommendations. Regarding the general structure of these recommender systems, one criterion is first chosen to calculate the similarity between users and then people who are assumed to have great similarity are proposed to each other as friend. These similar criteria can calculate users’ similarity with regard to topological structure and some properties of graph vertices. In this paper, the properties that are required for clustering are extracted from users’ profile. Finally, by combining the similarity criteria of mean measure of divergence (MMD), cosine, and Katz, different aspects of the problem including graph topology, frequency of user interaction with each other, and normalization of the same scoring method are considered.http://ijict.itrc.ac.ir/article-1-232-en.htmlsocial networkfriend recommendationgraph clusteringusers’ profileslink prediction |
| spellingShingle | Paria Dashtizadeh Ali Harounabadi Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms International Journal of Information and Communication Technology Research social network friend recommendation graph clustering users’ profiles link prediction |
| title | Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms |
| title_full | Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms |
| title_fullStr | Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms |
| title_full_unstemmed | Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms |
| title_short | Recommending Friends in Social Networks By Users\' Profiles And Using Classification Algorithms |
| title_sort | recommending friends in social networks by users profiles and using classification algorithms |
| topic | social network friend recommendation graph clustering users’ profiles link prediction |
| url | http://ijict.itrc.ac.ir/article-1-232-en.html |
| work_keys_str_mv | AT pariadashtizadeh recommendingfriendsinsocialnetworksbyusersprofilesandusingclassificationalgorithms AT aliharounabadi recommendingfriendsinsocialnetworksbyusersprofilesandusingclassificationalgorithms |