找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Database Systems for Advanced Applications; 27th International C Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki Conference proceedings

[復(fù)制鏈接]
樓主: Waterproof
31#
發(fā)表于 2025-3-26 23:47:43 | 只看該作者
32#
發(fā)表于 2025-3-27 01:41:11 | 只看該作者
Hyperbolic Personalized Tag Recommendationovel PTR model that operates on hyperbolic space, namely HPTR. HPTR learns the representations of entities by modeling their interactive relationships in hyperbolic space and utilizes hyperbolic distance to measure semantic relevance between entities. Specially, we adopt tangent space optimization t
33#
發(fā)表于 2025-3-27 05:30:11 | 只看該作者
Diffusion-Based Graph Contrastive Learning for?Recommendation with?Implicit Feedbacks. A symmetric contrastive learning objective is used to contrast local node representations of the diffusion graph with those of the user-item interaction graph for learning better user and item representations. Extensive experiments on real datasets demonstrate that GDCL consistently outperforms s
34#
發(fā)表于 2025-3-27 11:48:11 | 只看該作者
Multi-behavior Recommendation with?Two-Level Graph Attentional Networksn, we learn the dynamic feature of target users and target items by modeling the dependency relation between them. The results show that our model achieves great improvement for recommendation accuracy compared with other state-of-the-art recommendation methods.
35#
發(fā)表于 2025-3-27 15:27:41 | 只看該作者
36#
發(fā)表于 2025-3-27 19:42:25 | 只看該作者
37#
發(fā)表于 2025-3-27 22:07:54 | 只看該作者
César Fernández-de-las-Pe?as,Kimberly Bensen and fuse users’ personalized preferences on different modalities with a multi-modal probabilistic graph. Then, to filter out irrelevant and redundant information in multi-modal data, we extend the information bottleneck theory from single-modal to multi-modal scenario and design a multi-modal infor
38#
發(fā)表于 2025-3-28 04:55:30 | 只看該作者
Occlusal Diagnosis and Treatment of TMDrogeneous graphs from ratings and reviews to preserve inter- and intra-domain relations. Then, a relation-aware graph convolutional network is designed to simultaneously distill domain-shared and domain-specific features, by exploring the multi-hop heterogeneous connections across different graphs.
39#
發(fā)表于 2025-3-28 10:13:28 | 只看該作者
40#
發(fā)表于 2025-3-28 10:59:50 | 只看該作者
https://doi.org/10.1007/978-3-319-99909-8l, we not only design a personalized controller to enhance the deep knowledge tracing model for modeling learner’s forgetting behavior, but also use personality to model the individual differences based on the theory of cognitive psychology. In CRT, we adaptively combine learner’s knowledge level ob
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-5 04:30
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
惠州市| 定结县| 宝清县| 白朗县| 桃园县| 广东省| 孟津县| 万山特区| 大方县| 岳池县| 泰安市| 扬州市| 通州区| 常德市| 富阳市| 昌都县| 常德市| 喀什市| 务川| 固始县| 平陆县| 汉中市| 互助| 瑞金市| 巴楚县| 屯留县| 贺州市| 松江区| 民权县| 开原市| 英山县| 府谷县| 奇台县| 清涧县| 清镇市| 襄城县| 富源县| 汝州市| 海宁市| 宝应县| 紫阳县|