Results 41 to 50 of about 2,553,529 (294)

Promoting Cold-Start Items in Recommender Systems

PLoS ONE, 2014
As one of major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important.
Jin-Hu Liu, Tao Zhou, Zi-Ke Zhang, Zimo Yang, Chuang Liu, Wei-Min Li   +5 more
openaire   +5 more sources

Naïve filterbots for robust cold-start recommendations [PDF]

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, 2006
The goal of a recommender system is to suggest items of interest to a user based on historical behavior of a community of users. Given detailed enough history, item-based collaborative filtering (CF) often performs as well or better than almost any other recommendation method.
Seung-Taek Park, David M. Pennock, Omid Madani, Nathan Good, Dennis DeCoste   +4 more
openaire   +2 more sources

A Conscious Cross-Breed Recommendation Approach Confining Cold-Start in Electronic Commerce Systems

IEEE Access, 2023
When a new customer enters the spectrum of the E-Commerce system, the informative records and dataset, such as about the new user, purchasing history and other browsing data become insufficient, resulting in the emergence of one serious issue such as a ...
S. Gopal Krishna Patro, Brojo Kishore Mishra, Sanjaya Kumar Panda, Amrutashree Hota, Raghvendra Kumar, Shiyang Lyu, David Taniar   +6 more
doaj   +1 more source

A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation [PDF]

, 2022
Cold-start problem is a fundamental challenge for recommendation tasks. The recent self-supervised learning (SSL) on Graph Neural Networks (GNNs) model, PT-GNN, pre-trains the GNN model to reconstruct the cold-start embeddings and has shown great ...
Zhang, Jing, Hao, Bowen, Chen, Hong, Yin, Hongzhi, Li, Cuiping   +4 more
core  

Addressing the Extreme Cold-Start Problem in Group Recommendation

, 2022
The task of recommending items to a group of users, a.k.a. group recommendation, is receiving increasing attention. However, the cold-start problem inherent in recommender systems is amplified in group recommendation because interaction data between ...
Junliang, Yu, liang, Zhao, Wentao, Li, Min, Gao, yinghui, Tao, linxin, Guo   +5 more
core  

NFC: a Deep and Hybrid Item-based Model for Item Cold-start Recommendation [PDF]

, 2021
New items, also called cold-start items, are introduced every day in the catalogs of numerous online systems. Due to the absence of previous preferences, recommending these items is difficult but important task for a recommender system.
Cremonesi, Paolo, Bernardis, Cesare, Cesare Bernardis, Paolo Cremonesi   +3 more
core   +1 more source

Intelligent Service Recommendation for Cold-Start Problems in Edge Computing

IEEE Access, 2019
Memory-based collaborative filtering (i.e., MCF) is regarded as an effective technique to recommend appropriate services to target users. However, if recommendation data are very sparse in the edge environment, traditional MCF-based recommendation ...
Yichao Zhou, Zhenmin Tang, Lianyong Qi, Xuyun Zhang, Wanchun Dou, Shaohua Wan   +5 more
doaj   +1 more source

Purification and preparation of Marchantia polymorpha Auxin Response Factor 2 for phase separation studies

FEBS Open Bio, EarlyView.
We describe detailed protocols for the purification and preparation of Marchantia polymorpha Auxin Response Factor 2 (MpARF2). This protein is fused to an MBP solubility tag and an mNG fluorescent tag and is purified from Escherichia coli. The presented procedures make it possible to study MpARF2 assemblies, which could arise from phase separation ...
Bas Janssen, Robin Romein, Willy A. M. van den Berg, Simon Lindhoud, Jan Willem Borst, Carlo P. M. van Mierlo   +5 more
wiley   +1 more source

Overcoming the cold-start challenge in recommender systems: A novel two-stage framework

Open Computer Science
Cold-start recommendation helps personalize user experiences and improve the relevance of the recommendation system. Despite its importance, cold-start solutions are difficult to develop because new users and items lack interaction data, making user ...
Matam Vinay Kumar, Reddy Nooka Madhusudhana   +1 more
doaj   +1 more source

Protocol for quantifying miRNA trafficking across the endosomal membrane

FEBS Open Bio, EarlyView.
An in vitro protocol measures miRNA uptake into endosomes isolated from mammalian cell extracts, which are free of subcellular contaminants. Performed at 37 °C in the presence of ATP, it ensures the import of single‐stranded miRNA into the endosomal lumen.
Syamantak Ghosh, Kamalika Mukherjee, Suvendra N. Bhattacharyya   +2 more
wiley   +1 more source