Modeling user behaviour in research paper recommendation system
User intention which often changes dynamically is considered to be an important factor for
modeling users in the design of recommendation systems. Recent studies are starting to …
modeling users in the design of recommendation systems. Recent studies are starting to …
News recommendation based on collaborative semantic topic models and recommendation adjustment
YS Liao, JY Lu, DR Liu - 2019 International Conference on …, 2019 - ieeexplore.ieee.org
Providing news recommendations is an important trend for online news websites to attract
more users and create more benefits. In this research, we propose a novel recommendation …
more users and create more benefits. In this research, we propose a novel recommendation …
User profile based research paper recommendation
H Sahijwani, S Dasgupta - arXiv preprint arXiv:1704.07757, 2017 - arxiv.org
We design a recommender system for research papers based on topic-modeling. The users
feedback to the results is used to make the results more relevant the next time they fire a …
feedback to the results is used to make the results more relevant the next time they fire a …
Modeling multiple coexisting category-level intentions for next item recommendation
Purchase intentions have a great impact on future purchases and thus can be exploited for
making recommendations. However, purchase intentions are typically complex and may …
making recommendations. However, purchase intentions are typically complex and may …
Intention-aware user modeling for personalized news recommendation
Although tremendous efforts have been made in the field of personalized news
recommendations, how to accurately model users' reading preferences to recommend …
recommendations, how to accurately model users' reading preferences to recommend …
News Recommendation with Word-related Joint Topic Prediction
X Pu, JC Zhang, X Chen, YJ Qian, R Zhang - IEEE Access, 2024 - ieeexplore.ieee.org
As the problem of information overload becomes more severe, it has become increasingly
difficult for users to browse news that they are interested in. News recommendation is an …
difficult for users to browse news that they are interested in. News recommendation is an …
A novel temporal recommender system based on multiple transitions in user preference drift and topic review evolution
C Wangwatcharakul, S Wongthanavasu - Expert Systems with Applications, 2021 - Elsevier
Recommender systems are challenging research problems being exploited to suggest new
items or services, such as books, music and movies, and even people, to users based on …
items or services, such as books, music and movies, and even people, to users based on …
Dynamic sequential recommendation: Decoupling user intent from temporal context
Nowadays sequential recommender systems have been equipped with various deep
learning techniques such as recurrent neural networks and self-attention mechanisms …
learning techniques such as recurrent neural networks and self-attention mechanisms …
Time aware topic based recommender system
News recommender systems efficiently handle the overwhelming number of news articles,
simplify navigations, and retrieve relevant information. Many conventional news …
simplify navigations, and retrieve relevant information. Many conventional news …
[PDF][PDF] Time-aware Collaborative Topic Regression: Towards Higher Relevance in Textual Item Recommendation.
A Alzogbi - BIRNDL@ SIGIR, 2018 - ceur-ws.org
Time is an important aspect in Recommender Systems. Its impact is observed in several
aspects ranging from the change in user interest to the dynamics of adding new users and …
aspects ranging from the change in user interest to the dynamics of adding new users and …