Affiliation:
1. Faculty of Computing and Information Technology, University of the Punjab, Pakistan
2. National University of Sciences and Technology (NUST), Pakistan
Abstract
The advancement in the production, distribution, and consumption of news has fostered easy access to the news with fair challenges. The main challenge is to present the right news to the right audience. The news recommendation system is one of the technological solutions to this problem. Much work has been done on news recommendation systems for the major languages of the world, but trivial work has been done for resource-poor languages like Urdu. Another significant hurdle in the development of an efficient news recommendation system is the scarcity of an accessible and suitable Urdu dataset. To this end, an Urdu news mobile application was used to collect the news data and user feedback for 1 month. After refinement, the first-ever Urdu dataset of 100 users and 23,250 news was curated for the Urdu news recommendation system. In addition,
SEEUNRS
, a semantically enriched entity-based Urdu news recommendation system, is proposed. The proposed scheme exploits the hidden features of a news article and entities to suggest the right article to the right audience. Results have shown that the presented model has an improvement of 6.9% in the F1 measure from traditional recommendation system techniques.
Publisher
Association for Computing Machinery (ACM)
Reference38 articles.
1. Hamed Aboutorab Ran Yu Alishiba Dsouza Morteza Saberi and Omar Khadeer Hussain. 2023. A news recommendation system for environmental risk management. In Proceedings of the 2nd International Workshop on Linked Data-Driven Resilience Research (D2R2’23). 1–10.
2. Automatic Detection of Offensive Language for Urdu and Roman Urdu
3. Neural News Recommendation with Long- and Short-term User Representations
4. Aspect Based Recommendations
5. Latent Dirichlet allocation;Blei D. M.;Journal of Machine Learning Research,2003