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Found 9 papers, 3 papers with code
Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open Challenges
The emergence of Large Language Models (LLMs) has achieved tremendous success in the field of Natural Language Processing owing to diverse training paradigms that empower LLMs to effectively capture intricate linguistic patterns and semantic representations.
MOPO-LSI: A User Guide
MOPO-LSI is an open-source Multi-Objective Portfolio Optimization Library for Sustainable Investments.
Hybrid Multi-Criteria Preference Ranking by Subsorting
To alleviate this issue, we proposed a hybrid multi-criteria ranking method by using subsorting.
ITM-Rec: An Open Data Set for Educational Recommender Systems
With the development of recommender systems (RS), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS.
Multi-Objective Recommendations: A Tutorial
Recommender systems (RecSys) have been well developed to assist user decision making.
Time-Aware Music Recommender Systems: Modeling the Evolution of Implicit User Preferences and User Listening Habits in A Collaborative Filtering Approach
In the collaborative filtering method proposed in this work, daily listening habits are captured in order to characterize users and provide them with more reliable recommendations.
Galactic Gas Flows from Halo to Disk: Tomography and Kinematics at the Milky Way's Disk-Halo Interface
We calculate covering fractions of $f_{CaII}$ = 63%, $f_{NaI}$ = 26%, and $f_{HI}$ = 52%, consistent with a picture of the CGM that includes multi-phase clouds containing small clumps of cool gas within hotter, more diffuse gas.
Astrophysics of Galaxies
Fast Radio Burst Tomography of the Unseen Universe
The discovery of Fast Radio Bursts (FRBs) at cosmological distances has opened a powerful window on otherwise unseen matter in the Universe.
High Energy Astrophysical Phenomena Astrophysics of Galaxies
A User's Guide to CARSKit
Context-aware recommender systems extend traditional recommenders by adapting their suggestions to users' contextual situations.
Information Retrieval
