delusion 发表于 2025-3-23 11:13:52
Robust Sequence Embedding for Recommendationti-classification task with the historical sequence as the input, and the next item as the output class label. Sequence representation learning in the multi-classification task is of our main concern. The item frequency usually follows the long tail distribution in recommendation systems, which will灰心丧气 发表于 2025-3-23 16:17:24
Deep Generative Recommendation with Maximizing Reciprocal Rankative model is that it can break through the limited modeling capabilities of linear models which dominate collaborative filtering research to a large extend. In this paper, we propose a deep generative recommendation model by enforcing a list-wise ranking strategy to VAE with the aid of multinomial沙发 发表于 2025-3-23 18:08:21
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Seeds Selection for Influence Maximization Based on Device-to-Device Social Knowledge by Reinforcemege D2D social knowledge to select influential users (seed users or seeds) for influence maximization to minimize network traffic. Lots of work has been done for seeds selection in a single community. However, few studies are about seeds selection in multiple communities. In this paper, we build a Mu没血色 发表于 2025-3-24 09:38:25
CIFEF: Combining Implicit and Explicit Features for Friendship Inference in Location-Based Social Nemost active problems in LBSNs is friendship inference based on their rich check-in data. Previous studies are mainly based on co-occurrences of two users, however, a large number of user pairs have no co-occurrence, which weakens the performance of previous proposed methods. In this paper, we proposObserve 发表于 2025-3-24 14:35:10
r Neuzeit zu eigenständigen Teildisziplinen entwickelt haben: Analysis, Wahrscheinlichkeitstheorie, angewandte Mathematik, Topologie und Mengenlehre. Die Darstellung verzichtet auf Vollständigkeit und konzentriert sich stattdessen ganz bewusst auf wesentliche oder besonders interessante Aspekte: EinMILK 发表于 2025-3-24 17:27:14
http://reply.papertrans.cn/55/5441/544059/544059_18.pngIRK 发表于 2025-3-24 21:22:22
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