Quality Matters: Assessing cQA Pair Quality via Transductive Multi-View Learning
10.24963/ijcai.2018/623
Saved in:
Main Authors: | Xiaochi Wei, Heyan Huang, Liqiang Nie, Fuli Feng, Richang Hong, Tat-Seng Chu |
---|---|
Other Authors: | DEPARTMENT OF COMPUTER SCIENCE |
Format: | Conference or Workshop Item |
Published: |
2020
|
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/167408 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Segmentation of multi-sentence questions: Towards effective question retrieval in cQA services
by: Wang, K., et al.
Published: (2013) -
Mining slang and urban opinion words and phrases from cQA services: An optimization approach
by: Amiri, H., et al.
Published: (2013) -
Micro Tells Macro: Predicting the Popularity of Micro-Videos via a Transductive Model
by: Jingyuan Chen, et al.
Published: (2020) -
Computational Social Indicators: A Case Study of Chinese University Ranking
by: Fuli feng, et al.
Published: (2020) -
Classification problem of community question answering (CQA) services website
by: Sun, Fei.
Published: (2011)