Identifying buzz in social media: a hybrid approach using artificial bee colony and k-nearest neighbors for outlier detection-Reference-Cited by-同舟云学术

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Identifying buzz in social media: a hybrid approach using artificial bee colony and k-nearest neighbors for outlier detection

Published:2017-08-19 Issue:1 Volume:7 Page:
ISSN:1869-5450
Container-title:Social Network Analysis and Mining
language:en
Short-container-title:Soc. Netw. Anal. Min.

Author:

Aswani Reema,Ghrera S. P.,Kar Arpan Kumar,Chandra Satish

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems

Link

http://link.springer.com/article/10.1007/s13278-017-0461-2/fulltext.html

Reference91 articles.

1. Adaniya MHAC, Abrao T, Proenca ML Jr (2013) Anomaly detection using metaheuristic firefly harmonic clustering. J Netw 8(1):82–91

2. Aggrawal N, Ahluwalia A, Khurana P, Arora A (2017) Brand analysis framework for online marketing: ranking web pages and analyzing popularity of brands on social media. Soc Netw Anal Min 7(1):21

3. Akcora CG, Carminati B, Ferrari E, Kantarcioglu M (2014) Detecting anomalies in social network data consumption. Soc Netw Anal Min 4(1):231

4. Aswani R, Ghrera SP, Chandra S (2016) A novel approach to outlier detection using modified grey wolf optimization and k-nearest neighbors algorithm. Indian J Sci Technol 9(44):1–8

5. Aswani R, Ghrera SP, Chandra S, Kar AK (2017a) Outlier detection among influencer blogs based on off-site web analytics data. Forthcoming in Lecture Notes in Computer Science. In: Proceedings of 16th IFIP conference on e-business, e-services and e-society. Springer International Publishing (in press)

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