標(biāo)題: Titlebook: Network Embedding; Theories, Methods, a Cheng Yang,Chuan Shi,Maosong Sun Book 2021 Springer Nature Switzerland AG 2021 [打印本頁] 作者: melancholy 時(shí)間: 2025-3-21 19:59
書目名稱Network Embedding影響因子(影響力)
書目名稱Network Embedding影響因子(影響力)學(xué)科排名
書目名稱Network Embedding網(wǎng)絡(luò)公開度
書目名稱Network Embedding網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Network Embedding被引頻次
書目名稱Network Embedding被引頻次學(xué)科排名
書目名稱Network Embedding年度引用
書目名稱Network Embedding年度引用學(xué)科排名
書目名稱Network Embedding讀者反饋
書目名稱Network Embedding讀者反饋學(xué)科排名
作者: 驚惶 時(shí)間: 2025-3-21 21:11 作者: 小口啜飲 時(shí)間: 2025-3-22 00:39
1939-4608 Overview: heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.978-3-031-00462-9978-3-031-01590-8Series ISSN 1939-4608 Series E-ISSN 1939-4616 作者: Barter 時(shí)間: 2025-3-22 06:20
Synthesis Lectures on Artificial Intelligence and Machine Learninghttp://image.papertrans.cn/n/image/662796.jpg作者: 起皺紋 時(shí)間: 2025-3-22 09:17
Book 2021heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.作者: Rustproof 時(shí)間: 2025-3-22 16:56 作者: 手術(shù)刀 時(shí)間: 2025-3-22 19:09 作者: legacy 時(shí)間: 2025-3-22 23:42
the rubric of courtesy these idealized emotions influenced English in terms of its everyday pragmatics and literary style. This fascinating volume will be of broad interest to scholars of medieval language, literature and culture. .978-1-137-54069-0Series ISSN 2946-4056 Series E-ISSN 2946-4064 作者: overhaul 時(shí)間: 2025-3-23 01:40 作者: WITH 時(shí)間: 2025-3-23 06:31
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong SunGebiet von 2000?km. wurden rund 60?Mio. B?ume umgeknickt, und noch in einer Entfernung von 500?km wurde ein Lichtschein beobachtet. Dennoch hat dieses Ereignis unter den Zeitgenossen keine gr??ere Aufmerksamkeit gefunden. Erst durch eine Expedition in den frühen 1920er‐Jahren wurden so viele Informa作者: 嚙齒動(dòng)物 時(shí)間: 2025-3-23 10:13
Gebiet von 2000?km. wurden rund 60?Mio. B?ume umgeknickt, und noch in einer Entfernung von 500?km wurde ein Lichtschein beobachtet. Dennoch hat dieses Ereignis unter den Zeitgenossen keine gr??ere Aufmerksamkeit gefunden. Erst durch eine Expedition in den frühen 1920er‐Jahren wurden so viele Informa作者: Forehead-Lift 時(shí)間: 2025-3-23 17:03 作者: 重力 時(shí)間: 2025-3-23 18:18 作者: 松果 時(shí)間: 2025-3-24 00:12 作者: RAFF 時(shí)間: 2025-3-24 06:00
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong Sun作者: 免除責(zé)任 時(shí)間: 2025-3-24 08:35 作者: 返老還童 時(shí)間: 2025-3-24 12:08 作者: Hyperopia 時(shí)間: 2025-3-24 15:49
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong Sun作者: radiograph 時(shí)間: 2025-3-24 21:10
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong Sun作者: Palpitation 時(shí)間: 2025-3-25 02:22
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong Sun作者: Rejuvenate 時(shí)間: 2025-3-25 04:11
Network Embedding for Large-Scale Graphsf multi-label classification and link prediction, where baselines and our model have the same memory usage. Compared with baseline methods, COSINE has up to 23% increase on classification and up to 25% increase on link prediction. Moreover, time of all representation learning methods using COSINE de作者: 柔聲地說 時(shí)間: 2025-3-25 09:45
Network Embedding for Heterogeneous Graphsdistinctive characteristics of relations, we propose different models specifically tailored to handle ARs and IRs in RHINE, which can better capture the structures and semantics of the networks. Finally, we combine and optimize these models in a unified and elegant manner. Extensive experiments on t作者: 睨視 時(shí)間: 2025-3-25 14:06
Network Embedding for Recommendation Systems on LBSNsopt a network embedding method for the construction of social networks. Second, we consider four factors that influence the generation process of mobile trajectories, namely user visit preference, influence of friends, short-term sequential contexts, and long-term sequential contexts. Finally, the t作者: 助記 時(shí)間: 2025-3-25 16:48 作者: Abduct 時(shí)間: 2025-3-25 22:17 作者: ordain 時(shí)間: 2025-3-26 01:36 作者: 畫布 時(shí)間: 2025-3-26 05:06 作者: tackle 時(shí)間: 2025-3-26 09:00
Network Embedding for Graphs with Node Attributesll applied with typical representation learning methods. Taking text feature as an example, we will introduce text-associated DeepWalk (TADW) model for learning NEs with node attributes in this chapter. Inspired by the proof that DeepWalk, a state-of-the-art network representation method, is actuall作者: MORPH 時(shí)間: 2025-3-26 14:17 作者: 并置 時(shí)間: 2025-3-26 18:16
Network Embedding for Graphs with Node Contentsork and citation network, nodes have rich text content which can be used to analyze their semantic aspects. In this chapter, we assume that a node usually shows different aspects when interacting with different neighbors (context), and thus should be assigned different embeddings. However, most exis作者: obstinate 時(shí)間: 2025-3-26 23:38 作者: 外星人 時(shí)間: 2025-3-27 04:11
Network Embedding for Community-Structured Graphss of the graph. Nevertheless, vertices in many complex networks also exhibit significant global patterns widely known as communities. In community-structured graphs, nodes in the same community tend to connect densely, and share common attributes. These patterns are expected to improve NE and benefi作者: EPT 時(shí)間: 2025-3-27 05:45 作者: 某人 時(shí)間: 2025-3-27 10:40
Network Embedding for Heterogeneous Graphs aims to embed multiple types of nodes into a low-dimensional space. Although most HIN embedding methods consider heterogeneous relations in HINs, they usually employ one single model for all relations without distinction, which inevitably restricts the capability of NE. In this chapter, we take the作者: famine 時(shí)間: 2025-3-27 16:37 作者: 無能力之人 時(shí)間: 2025-3-27 20:00 作者: 絕食 時(shí)間: 2025-3-27 22:05 作者: 配置 時(shí)間: 2025-3-28 03:38
Future Directions of Network Embeddinga scales and the development of deep learning techniques, there are also new challenges and opportunities for next-stage researches of network embedding. In the last chapter, we will look into the future directions of NRL. Specifically, we will consider the following directions including employing a作者: Insul島 時(shí)間: 2025-3-28 06:32
n the collection. This generalization of commutativity is the subject of many classical theorems due to Engel, Kolchin, Kaplansky, McCoy and others. The concept has been extended to collections of bounded linear operators on Banach spaces: such a collection is defined to be triangularizable if there作者: nonradioactive 時(shí)間: 2025-3-28 10:44 作者: ACRID 時(shí)間: 2025-3-28 15:38 作者: 修改 時(shí)間: 2025-3-28 22:46
rary and emotional histories to cast new light on medieval tThis book traces the development of the ideal of sincerity from its origins in Anglo-Saxon monasteries to its eventual currency in fifteenth-century familiar letters. Beginning by positioning sincerity as an ideology at the intersection of 作者: 的是兄弟 時(shí)間: 2025-3-28 23:17
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong Sunrary and emotional histories to cast new light on medieval tThis book traces the development of the ideal of sincerity from its origins in Anglo-Saxon monasteries to its eventual currency in fifteenth-century familiar letters. Beginning by positioning sincerity as an ideology at the intersection of 作者: Lyme-disease 時(shí)間: 2025-3-29 05:58
Cheng Yang,Chuan Shi,Zhiyuan Liu,Cunchao Tu,Maosong Suns spektakul?ren Charakters auch gro?e Aufmerksamkeit in den Medien. Handelte es sich hierbei um eine Naturkatastrophe? Dies würden die meisten Beobachter verneinen. Es war zwar ein Extremereignis mit gro?en Wirkungen, aber um zur Katastrophe werden zu k?nnen, h?tte es auf der Erde stattfinden und h?作者: Encoding 時(shí)間: 2025-3-29 09:16 作者: 刪減 時(shí)間: 2025-3-29 14:36
Network Embedding for General Graphs a general framework for NE based on matrix factorization and show that the typical methods are actually special cases of our framework from the theoretic perspective. Finally, with the help of our framework, we propose an efficient and effective algorithm which can be applied on any NE methods to enhance their performances.作者: 修正案 時(shí)間: 2025-3-29 17:29 作者: 消息靈通 時(shí)間: 2025-3-29 20:04
Revisiting Attributed Network Embedding: A GCN-Based Perspective (AGE), a novel attributed graph embedding framework, to address these issues. Finally, we conduct experiments using four public benchmark datasets to demonstrate the effectiveness of AGE. Experimental results on node clustering and link prediction tasks show that AGE consistently outperforms state-of-the-art graph embedding methods.作者: 不成比例 時(shí)間: 2025-3-30 03:39
Network Embedding for Graphs with Node Labelsbut also have the characteristic of discrimination. The visualizations of learned representations indicate that MMDW is more discriminative than unsupervised ones, and the experimental results on node classification demonstrate that MMDW achieves a significant improvement than previous NE methods.作者: V洗浴 時(shí)間: 2025-3-30 05:20 作者: Affectation 時(shí)間: 2025-3-30 08:19
Network Embedding for Community-Structured Graphs embeddings of both vertices and communities. Moreover, the proposed community enhancement mechanism can be applied to various existing NE models. In experiments, we evaluate our model on node classification, link prediction, and community detection using several real-world datasets to demonstrate the effectiveness of CNRL.
