Recommended System for Enhancing Tag Popularity in a Question Answering Community through Splay-net Techniques
| Main Author: | Jayashree R |
|---|---|
| Other Authors: | Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP) |
| Format: | Article eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2020
|
| Subjects: | |
| Online Access: |
https://zenodo.org/record/5526277 |
Daftar Isi:
- Collaborative filtering filters information by using the recommendations of peer participants. The long tail problem states users with higher points obtain a high reputation compared to less scored users. In popular community question answering websites, like stack exchange network sites, users with unanswered or ignored questions for a long time get a tumbleweed badge without considering their past history. This deteriorates their further contribution to the website. Mostly new or low-reputation people ask the tumbleweed questions. The popularity of the tags follows a long tail theory. The focus of this research work is to design a recommendation system that prevents participants from tumbleweed badge with tag suggestion method to add new or non-popular tags to the existing popular tag list. The splay-net has a self-balancing graph which brings the recently accessed item to the top of the tree. In this paper, we use the splay-net technique to represent users’ reputation along with their tags.