CFP last date
22 April 2024
Reseach Article

A Hybrid Approach to Social Network User Feed Generation

by Akhil Sudhakaran, Devipriya Sarkar, Praveen Kumar G., Ravikiran R., Sushila Shidnal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 48
Year of Publication: 2018
Authors: Akhil Sudhakaran, Devipriya Sarkar, Praveen Kumar G., Ravikiran R., Sushila Shidnal
10.5120/ijca2018917224

Akhil Sudhakaran, Devipriya Sarkar, Praveen Kumar G., Ravikiran R., Sushila Shidnal . A Hybrid Approach to Social Network User Feed Generation. International Journal of Computer Applications. 179, 48 ( Jun 2018), 7-9. DOI=10.5120/ijca2018917224

@article{ 10.5120/ijca2018917224,
author = { Akhil Sudhakaran, Devipriya Sarkar, Praveen Kumar G., Ravikiran R., Sushila Shidnal },
title = { A Hybrid Approach to Social Network User Feed Generation },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2018 },
volume = { 179 },
number = { 48 },
month = { Jun },
year = { 2018 },
issn = { 0975-8887 },
pages = { 7-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number48/29498-2018917224/ },
doi = { 10.5120/ijca2018917224 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:39.418061+05:30
%A Akhil Sudhakaran
%A Devipriya Sarkar
%A Praveen Kumar G.
%A Ravikiran R.
%A Sushila Shidnal
%T A Hybrid Approach to Social Network User Feed Generation
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 48
%P 7-9
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Existing social networks handle generation of user activity feeds by utilizing different data distribution models. Different models optimize different aspects of feed generation such as user specificity, processing efficiency, resource utilization and latency. This paper propo*ses a hybrid model to handle this problem elegantly. This model takes into account the frequency of query requests between individual users and classifies them into either a PUSH-Target user or PULL-Target user. The former is provided with prioritized data pushes and the latter with data pulls on user request basis.

References
  1. M. Hashemi “The Infrastructure Behind Twitter: Scale”, retrieved from https://blog.twitter.com/engineering/en_us/topics/infrastructure/2017/the-infrastructure-behind-twitter-scale.html (2017, 19 January).
  2. Y. Zhu “Serving Facebook Multifeed: Efficiency, performance gains through redesign”, retrieved from https://code.facebook.com/posts/781984911887151/serving-facebook-multifeed-efficiency-performance-gains-through-redesign/ (2015, 10 March).
  3. S. Schneider “How Instagram Feed Works: Celery and RabbitMQ”, retrieved from https://blogs.vmware.com/vfabric/2013/04/how-instagram-feeds-work-celery-and-rabbitmq.html (2013, 15 April).
  4. V. Sharma et al. “Scaling Deep Social Feeds at Pinterest” SocialCom, 2013.
  5. Instagram Engineering “What Powers Instagram: Hundreds of Instances, Dozens of Technologies”, retrieved from https://instagram-engineering.com/what-powers-instagram-hundreds-of-instances-dozens-of-technologies-adf2e22da2ad (2011, 2 December).
  6. A. Silberstein et al. “Feeding Frenzy: Selectively Materializing Users’ Event Feeds” SIGMOD, June 6–11, 2010.
  7. M. Zuckerberg et al. "Dynamically providing a news feed about a user of a social network." U.S. Patent 7,669,123, issued February 23, 2010.
  8. B.F. Cooper et al. "PNUTS: Yahoo!'s hosted data serving platform." Proceedings of the VLDB Endowment 1, no. 2 2008: 1277-1288.
Index Terms

Computer Science
Information Sciences

Keywords

Social Network Activity Feed Hybrid Model.