找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪(fǎng)問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Web Information Systems and Applications; 19th International C Xiang Zhao,Shiyu Yang,Jianxin Li Conference proceedings 2022 The Editor(s) (

[復(fù)制鏈接]
樓主: analgesic
61#
發(fā)表于 2025-4-1 05:45:54 | 只看該作者
62#
發(fā)表于 2025-4-1 09:57:34 | 只看該作者
Yanting Jiang,Di Wu systematic description of a cyclic load. Then, the books use two probabilistic fatigue theories toestablish the limit state function of a component under cyclic load, and further to present how to calculate the reliability of a component under a cyclic loading spectrum. Finally, the book presents h
63#
發(fā)表于 2025-4-1 13:58:14 | 只看該作者
64#
發(fā)表于 2025-4-1 18:02:58 | 只看該作者
65#
發(fā)表于 2025-4-1 19:28:30 | 只看該作者
66#
發(fā)表于 2025-4-2 02:43:36 | 只看該作者
Shuning Hou,Xueqing Zhao,Ning Liu,Xin Shi,Yun Wang,Guigang Zhang rise to non-equivalent double fault mutants, and hence, cannot be discarded. Moreover, we have developed several supplementary test case selection strategies to detect double faults that cannot be detected by existing test case selection strategies which aim at single-fault detection.
67#
發(fā)表于 2025-4-2 05:16:25 | 只看該作者
68#
發(fā)表于 2025-4-2 08:33:24 | 只看該作者
Temporal Knowledge Graph Embedding for Link Predictioncing the position embedding characterizing the dynamic information of temporal knowledge graph, TKGE can generate the evolutional embedding of entities and relations for downstream applications, such as link prediction, recommender system, and so on. We conduct experiments on several real datasets.
69#
發(fā)表于 2025-4-2 11:16:50 | 只看該作者
Temporal Knowledge Graph Embedding for Link Predictioncing the position embedding characterizing the dynamic information of temporal knowledge graph, TKGE can generate the evolutional embedding of entities and relations for downstream applications, such as link prediction, recommender system, and so on. We conduct experiments on several real datasets.
70#
發(fā)表于 2025-4-2 16:53:07 | 只看該作者
Fusion of Natural Language and Knowledge Graph for Multi-hop Reasoninghe natural language. We tested the performance of the NLKGF model on two datasets requiring multi-hop reasoning. The experimental results show that NLKGF beats advanced benchmark models in multi-hop reasoning tasks, which proves superiority of our model.
 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(ài)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(píng) 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(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-15 06:44
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
偃师市| 大姚县| 黔江区| 治多县| 宝丰县| 甘孜县| 乌鲁木齐市| 昌都县| 五家渠市| 右玉县| 西峡县| 五莲县| 绥棱县| 镇平县| 启东市| 鄂托克前旗| 双城市| 历史| 青铜峡市| 都匀市| 大余县| 灵武市| 会同县| 关岭| 吉安市| 衡山县| 天祝| 隆昌县| 台南市| 鸡西市| 桂平市| 隆子县| 水城县| 富阳市| 临湘市| 克山县| 平山县| 江华| 韩城市| 杂多县| 图木舒克市|