Identification of modular or community structures a network is key to understanding the semantics and functions network. While many detection methods have been developed, which primarily explore topologies, they provide little semantic information communities discovered. Although are closely related, effort has made discover analyze these two essential properties together. By integrating topology on nodes, e.g., node attributes, we study problems inference their simultaneously. We propose...

Multi-view graph clustering, which seeks a partition of the with multiple views that often provide more comprehensive yet complex information, has received considerable attention in recent years. Although some efforts have been made for multi-view clustering and achieve decent performances, most them employ shallow model to deal relation within graph, may seriously restrict capacity modeling information. In this paper, we make first attempt deep learning technique attributed propose novel...

Popular online social networks (OSNs) like Facebook and Twitter are changing the way users communicate interact with Internet. A deep understanding of user interactions in OSNs can provide important insights into questions human behavior, design platforms applications. However, recent studies have shown that a majority on latent interactions, passive actions such as profile browsing cannot be observed by traditional measurement techniques. In this paper, we seek deeper both visible OSNs. For...

Network embedding aims to embed nodes into a low-dimensional space, while capturing the network structures and properties. Although quite few promising methods have been proposed, most of them focus on static networks. In fact, temporal networks, which usually evolve over time in terms microscopic macroscopic dynamics, are ubiquitous. The micro-dynamics describe formation process detailed manner, macro-dynamics refer evolution pattern scale. Both micro- key factors evolution; however, how...

Heterogeneous information network (HIN) embedding, aiming to project HIN into a low-dimensional space, has attracted considerable research attention. Most of the exiting embedding methods focus on preserving inherent structure and semantic correlations in Euclidean spaces. However, one fundamental problem is that whether spaces are appropriate or intrinsic isometric HIN? Recent researches argue complex may have hyperbolic geometry underneath, because underlying can naturally reflect some...

Popular online social networks (OSNs) like Facebook and Twitter are changing the way users communicate interact with Internet. A deep understanding of user interactions in OSNs can provide important insights into questions human behavior design platforms applications. However, recent studies have shown that a majority on latent , is, passive actions, such as profile browsing, cannot be observed by traditional measurement techniques. In this article, we seek deeper both active OSNs. For...

Community detection is important for understanding networks. Previous studies observed that communities are not necessarily disjoint and might overlap. It also agreed some outlier vertices participate in no community, hubs a community take more roles than others. Each of these facts has been independently addressed previous work. But there algorithm, to our knowledge, can identify three structures altogether. To overcome this limitation, we propose novel model where measured by their...

Abstract The electroreduction of nitrate (NO 3 RR) to ammonia (NH ) provides a promising solution enable environmental remediation caused by ‐containing waste and also allows for energy‐saving NH generation. Adsorption *NO 2 intermediate may be strengthened decrease byproducts (e.g., favor the eight‐electron NO RR into . In this work, copper‐incorporated O‐vacancy containing Ti C MXene (Cu@Ti O v is reported, which cooperatively inhibits production facilitates hydrogenation, leading...

Data confidentiality policies at major social network providers have severely limited researchers' access to large-scale datasets. The biggest impact has been on the study of dynamics, where researchers studied citation graphs and content-sharing networks, but few analyzed detailed dynamics in massive networks that dominate web today. In this paper, we present results analyzing a large Chinese network, covering period 2 years when grew from its first user 19 million users 199 edges. Rather...

The study of users' social behaviors has gained much research attention since the advent various media such as Facebook, Renren and Twitter. A major kind applications is to predict a user's future activities based on his/her historical behaviors. In this paper, we focus fundamental task: activity levels in network, e.g. weekly activeness, active or inactive. This problem closely related Social Customer Relationship Management (Social CRM). Compared traditional CRM, three properties: user...

Recently, video-language understanding has achieved great success through large-scale pre-training. However, data scarcity remains a prevailing challenge. This study quantitatively reveals an "impossible trinity" among quantity, diversity, and quality in pre-training datasets. Recent efforts seek to refine large-scale, diverse ASR datasets compromised by low synthetic annotations. These methods successfully the original annotations leveraging useful information multimodal video content...

This study introduces the Audit Risk Sentiment Value (ARSV), a novel audit risk proxy that leverages sentiment analysis to address limitations in traditional measures such as fees (LNFEE), hours (LNHOUR), and discretionary accruals (|MJDA|). Traditional proxies primarily capture quantitative dimensions, overlooking qualitative insights embedded report narratives. By systematically analyzing tone, ARSV captures nuanced dimensions reflect auditor’s perception. The validates using dataset of...

Habitat fragmentation (Sensu lato) represents a landscape-scale process involving both habitat loss and the breaking apart of (habitat per se). In ecological studies, understanding impacts se on biodiversity remains critical challenge. While previous research has explored effects various ecosystems, significant gaps remain in our its bryophyte assemblages. To explore assemblages subtropical forests, we investigated bryophytes environments 18 fragmented forest landscapes (including 166...

Six new pairs of bibenzyl-based meroterpenoid enantiomers, (±)-rasumatranin A–D (1–4) and (±)-radulanin M N (5 6), six known compounds were isolated from the adnascent Chinese liverwort, Radula sumatrana. Their structures elucidated based on spectroscopic data chiral phase HPLC-ECD analyses. The 1 7 also confirmed by single-crystal X-ray diffraction analysis. Cytotoxicity tests showed that 6-hydroxy-3-methyl-8-phenylethylbenzo[b]oxepin-5-one (8) activity against human cancer cell lines...

Abstract Plant leaves have evolved into diverse shapes and LATE MERISTEM IDENTITY1 (LMI1) its putative paralogous genes encode homeodomain leucine zipper transcription factors that are proposed evolutionary hotspots for the regulation of leaf development in plants. However, LMI1-mediated regulatory mechanism underlying shape formation is largely unknown. MtLMI1a MtLMI1b orthologs LMI1 model legume barrelclover (Medicago truncatula). Here, we investigated role margin morphogenesis by...

Recent advancements in video-language understanding have been established on the foundation of image-text models, resulting promising outcomes due to shared knowledge between images and videos. However, presents unique challenges inclusion highly complex semantic details, which result information redundancy, temporal dependency, scene complexity. Current techniques only partially tackled these issues, our quantitative analysis indicates that some methods are complementary. In light this, we...

Analyzing and modeling social network dynamics are key to accurately predicting resource needs system behavior in online networks. The presence of statistical scaling properties, that is, self-similarity, is critical for determining how model dynamics. In this work, we study the role self-similarity plays a edge creation (that links created between users) process, through analysis two detailed, time-stamped traces, 199 million trace over 2 years Renren network, 876K interactions 4-year...

Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on overlapping communities, where vertex may belong to more than one community. However, most current methods require number (or size) communities as priori information, which usually unavailable real-world Thus, practical algorithm should not only find community structure, but also automatically determine communities. Furthermore, it preferable if this method able...