IIIT Hyderabad Publications |
|||||||||
|
Neural Content-Collaborative Filtering for News RecommendationAuthors: Dhruv Khattar,Vaibhav Kumar,Manish Gupta,Vasudeva Varma Conference: 2018 European Conference on Information Retrieval (ECIR-2018 2018) Location Grenoble, France Date: 2018-03-26 Report no: IIIT/TR/2018/43 AbstractPopular methods like collaborative filtering and content-based filtering have their own disadvantages. The former method requires a considerable amount of user data before making predictions, while the latter, suffers from over-specialization. In this work, we address both of these issues by coming up with a hybrid approach based on neural networks for news recommendation. The hybrid approach incorporates for both (1) user-item interaction and (2) content-information of the articles read by the user in the past. We first come up with an article-embedding based profile for the user. We then use this user profile with adequate positive and negative samples in order to train the neural network based model. The resulting model is then applied on a real-world dataset. We compare it with a set of established baselines and the experimental results show that our model outperforms the state-of-the-art. Full paper: pdf Centre for Search and Information Extraction Lab |
||||||||
Copyright © 2009 - IIIT Hyderabad. All Rights Reserved. |