Video Recommendation System for YouTube Considering Users Feedback

Md. Shamim Reza Sajib; Md. Ariful Islam Malik; Md. Ashraful Islam

Video Recommendation System for YouTube Considering Users Feedback

Md. Shamim Reza Sajib * §

Contact

Md. Ariful Islam Malik §

Contact

Md. Ashraful Islam §

Contact

sudiphalderruet §

Contact

§ Bangladesh University of Business & Technology

Video Recommendation System for YouTube Considering Users Feedback

Article Fingerprint

ReserarchID

VAV6F

Video Recommendation System for YouTube Considering Users Feedback Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant

This converted HTML version may contain rendering inconsistencies. Please refer to the PDF for the authoritative version, or click here to provide feedback.

Abstract

Youtube is the most video sharing and viewing platform in the world. As there are many people of different tastes, hundreds of categories of videos can be found on YouTube while thousands of videos of each. So, when the site recommends videos for a user it takes some issues which fill the needs of the user. Most of the time a user watches videos related to the previously watched video. But sometimes user’s mood changes with time or weather. A user may not hear a song in the whole year but can search the song on a rainy day. Another case a user may watch some types of videos at day but another type of videos at night or another at midnight. In this paper, we propose a recommendation system considering some attributes like weather, time, month to understand the dynamic mood of a user. Each attribute is assigned a weight calculated by performing a survey on some YouTube users.

References

7 Cites in Article

Reference Format

1. James Davidson,Benjamin Liebald,Junning Liu,Palash Nandy,Taylor Van Vleet,Ullas Gargi,Sujoy Gupta,Yu He,Mike Lambert,Blake Livingston,Dasarathi Sampath (2010). The YouTube video recommendation system. Proceedings of the fourth ACM conference on Recommender systems, 293-296.
2. Fay Chang,Jeffrey Dean,Sanjay Ghemawat,Wilson Hsieh,Deborah Wallach,Mike Burrows,Tushar Chandra,Andrew Fikes,Robert Gruber (2006). Bigtable. ACM Transactions on Computer Systems, 26(2), 1-26.
3. Shumeet Baluja,Rohan Seth,D Sivakumar,Yushi Jing,Jay Yagnik,Shankar Kumar,Deepak Ravichandran,Mohamed Aly (2008). Video suggestion and discovery for youtube. Proceedings of the 17th international conference on World Wide Web, 895-904.
4. Paul Covington,Jay Adams,Emre Sargin (2016). Deep neural networks for youtube recommendations. Proceedings of the 10th ACM Conference on Recommender Systems
5. Mukund Deshpande,George Karypis (2004). Item-based top-Nrecommendation algorithms. ACM Transactions on Information Systems, 22(1), 143-177.
6. Ellen Spertus,Mehran Sahami,Orkut Buyukkokten (2005). Evaluating similarity measures. Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, 678-684.
7. Fay Chang,Jeffrey Dean,Sanjay Ghemawat,Wilson Hsieh,Deborah Wallach,Mike Burrows,Tushar Chandra,Andrew Fikes,Robert Gruber (2006). Bigtable. ACM Transactions on Computer Systems, 26(2), 1-26.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Md. Shamim Reza Sajib, Md. Ariful Islam Malik, Md. Ashraful Islam, sudiphalderruet. 2018. "Video Recommendation System for YouTube Considering Users Feedback". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 18 (GJCST Volume 18 Issue G1).

More Citation Formats

Select Citation Style:

Download Citation

GJCST Volume 18 Issue G1

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

GJCST-G Classification H.5.2

Submission ReceivedDecember 8, 2017
Peer Review Double Blind
Handling Editor
Accepted January 1, 2018
Published April 11, 2018

Version of record

v1.2

Issue date

April 11, 2018

Language

English

Order Article Reprint

Experience in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 104

Country: Bangladesh

Subject: Global Journal of Computer Science and Technology - G: Interdisciplinary

Authors: Md. Shamim Reza Sajib, Md. Ariful Islam Malik, Md. Ashraful Islam, Sudip Kumar Halder (PhD/Dr. count: 0)

View Count (all-time): 413

Total Views (Real + Logic): 2086

Total Downloads (simulated): 186

Publish Date: 2018 01, Mon

Monthly Totals (Real + Logic):

Month 1: 58 views
Month 2: 41 views
Month 3: 49 views
Month 4: 55 views
Month 5: 28 views
Month 6: 38 views
Month 7: 52 views
Month 8: 32 views
Month 9: 56 views
Month 10: 19 views
Month 11: 59 views
Month 12: 39 views
Month 13: 14 views
Month 14: 24 views
Month 15: 29 views
Month 16: 23 views
Month 17: 34 views
Month 18: 11 views
Month 19: 34 views
Month 20: 40 views
Month 21: 34 views
Month 22: 16 views
Month 23: 25 views
Month 24: 43 views
Month 25: 21 views
Month 26: 34 views
Month 27: 35 views
Month 28: 49 views
Month 29: 21 views
Month 30: 40 views
Month 31: 22 views
Month 32: 29 views
Month 33: 28 views
Month 34: 32 views
Month 35: 40 views
Month 36: 25 views
Month 37: 14 views
Month 38: 22 views
Month 39: 26 views
Month 40: 29 views
Month 41: 17 views
Month 42: 29 views
Month 43: 42 views
Month 44: 34 views
Month 45: 27 views
Month 46: 21 views
Month 47: 28 views
Month 48: 29 views
Month 49: 43 views
Month 50: 27 views
Month 51: 18 views
Month 52: 39 views
Month 53: 44 views
Month 54: 28 views
Month 55: 14 views
Month 56: 27 views
Month 57: 14 views
Month 58: 38 views
Month 59: 12 views
Month 60: 19 views
Month 61: 41 views
Month 62: 40 views
Month 63: 23 views
Month 64: 39 views
Month 65: 28 views
Month 66: 37 views
Month 67: 40 views
Month 68: 22 views
Month 69: 35 views
Month 70: 42 views
Month 71: 37 views
Month 72: 37 views
Month 73: 35 views
Month 74: 23 views
Month 75: 27 views
Month 76: 19 views
Month 77: 42 views
Month 78: 28 views
Month 79: 22 views
Month 80: 16 views
Month 81: 17 views
Month 82: 40 views
Month 83: 22 views
Month 84: 28 views
Month 85: 39 views
Month 86: 26 views
Month 87: 43 views
Month 88: 29 views
Month 89: 32 views
Month 90: 25 views
Month 91: 39 views
Month 92: 40 views
Month 93: 24 views
Month 94: 23 views
Month 95: 42 views
Month 96: 55 views
Month 97: 55 views
Month 98: 35 views
Month 99: 38 views
Month 100: 21 views
Month 101: 38 views
Month 102: 44 views
Month 103: 35 views
Month 104: 49 views
Month 105: 33 views
Month 106: 45 views

Total Views: 2.1K

Total Downloads: 186

All Trends