Filters








6,975 Hits in 6.9 sec

Personalized Service Recommendation With Mashup Group Preference in Heterogeneous Information Network

Fenfang Xie, Liang Chen, Dongding Lin, Zibin Zheng, Xiaola Lin
2019 IEEE Access  
In this paper, we propose a mashup group preference-based service recommendation method in the heterogeneous information network for mashup creation.  ...  INDEX TERMS Heterogeneous information network, meta path, service recommendation, group preference.  ...  Definition 1 (Heterogeneous Information Network): An information network is denoted as a directed graph G = (V, E). It has two functions, i.e.  ... 
doi:10.1109/access.2019.2894822 fatcat:3c2ijwlfv5arzd6apwkmushs3u

A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources [article]

Xiao Wang and Deyu Bo and Chuan Shi and Shaohua Fan and Yanfang Ye and Philip S. Yu
2020 arXiv   pre-print
Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension  ...  survey and categorize the state-of-the-art HG embedding methods based on the information they used in the learning process to address the challenges posed by the HG heterogeneity.  ...  [92] employs graph convolutional network on heterogeneous graphs for basket recommendation.  ... 
arXiv:2011.14867v1 fatcat:phfoxj7qsrfshfednomeok7pau

Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation

Fengli Xu, Jianxun Lian, Zhenyu Han, Yong Li, Yujian Xu, Xing Xie
2019 Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19  
Extensive experiments on a real-world dataset demonstrate RecoGCN is able to learn meaningful node embeddings in HIN, and consistently outperforms baseline methods in recommendation tasks.  ...  To effectively fuse the embeddings learned from different meta-paths, we further develop a co-attentive mechanism to dynamically assign importance weights to different meta-paths by attending the threeway  ...  For example, a user may purchase a cloth based on her preference or based on the recommendation of friends.  ... 
doi:10.1145/3357384.3357924 dblp:conf/cikm/XuLHLX019 fatcat:wgznfbekajeg5kezix2dgjeecm

A mobile tourist assistance and recommendation system based on complex networks

Alf-Christian Schering, Martin Dueffer, Andreas Finger, Ilvio Bruder
2009 Proceeding of the 1st ACM international workshop on Complex networks meet information & knowledge management - CNIKM '09  
Our project aims for digital tourism assistance by combining mobile guiding and route recommendation based on community networks.  ...  This article describes ongoing work on the recommendation system and mobile semantic replication strategies.  ...  Hence, this approach focuses on route recommendation based on information given prior to the tour.  ... 
doi:10.1145/1651274.1651290 dblp:conf/cikm/ScheringDFB09 fatcat:rimlpkyfq5gvregt7sz2p56m2u

Heterogeneous Graph Attention Network [article]

Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, P. Yu, Yanfang Ye
2021 arXiv   pre-print
The heterogeneity and rich semantic information bring great challenges for designing a graph neural network for heterogeneous graph.  ...  In this paper, we first propose a novel heterogeneous graph neural network based on the hierarchical attention, including node-level and semantic-level attentions.  ...  Some previous works introduce the attention mechanism for graph based applications, e.g., the recommendation [15, 16] .  ... 
arXiv:1903.07293v2 fatcat:wrwdajlnm5bahhh26ngd5z7pfe

Q-HeteLearn: A Progressive Learning approach for Classifying Meta-Paths in Heterogeneous Information Networks

Sadhana Kodali
2020 International Journal of Emerging Trends in Engineering Research  
In this paper a novel approach called Q-HeteLearn a Progressive Learning method is introduced to classify the objects by traversing the meta-paths in the Heterogeneous Information Networks.  ...  Reinforcement learning is a machine learning paradigm which has a number of applications in gaming, stock prediction, robot navigation etc.  ...  CONCLUSION In this paper a Progressive reinforcement learning approach called the Q-HeteLearn is devised for classification of meta-paths in heterogeneous information networks .This approach uses a progression  ... 
doi:10.30534/ijeter/2020/35832020 fatcat:m6xvtws7mzhyzb526w4eme57da

Introduction of Key Problems in Long-Distance Learning and Training

Shuai Liu, Zhaojun Li, Yudong Zhang, Xiaochun Cheng
2018 Journal on spesial topics in mobile networks and applications  
Imrich Chlamtac for his supportive guidance during the entire process. The editorial is supported by National Natural Science  ...  Acknowledgements The guest editors are thankful to our reviewers for their effort in reviewing these manuscripts. We also thank the Edit-in-Chief, Dr.  ...  In this way, this paper studies the problem of new paper recommendation in the heterogeneous bibliographic network, and a new method of meta-graph based recommendation model called HipRec is proposed.  ... 
doi:10.1007/s11036-018-1136-6 fatcat:o56hifzmbrc4vnhvs2qqnsp4gy

LBSN2Vec++: Heterogeneous Hypergraph Embedding for Location-Based Social Networks

Dingqi Yang, Bingqing Qu, Jie Yang, Philippe Cudre-Mauroux
2020 IEEE Transactions on Knowledge and Data Engineering  
Location-Based Social Networks (LBSNs) have been widely used as a primary data source for studying the impact of mobility and social relationships on each other.  ...  Against this background, we propose in this paper LBSN2Vec++, a heterogeneous hypergraph embedding approach designed specifically for LBSN data for automatic feature learning.  ...  These approaches mainly focus on capturing the meta-structures of a heterogeneous graph (using meta-paths, for example) and project nodes into a unified embedding space.  ... 
doi:10.1109/tkde.2020.2997869 fatcat:m5zamr37rzectgo5lyciuvupry

Mobile Link Prediction: Automated Creation and Crowd-sourced Validation of Knowledge Graphs [article]

Mark Christopher Ballandies, Evangelos Pournaras
2020 arXiv   pre-print
In particular, current approaches relying on human experts have limited scalability, while automated approaches are often not accountable to users resulting in knowledge graphs of questionable quality.  ...  Building trustworthy knowledge graphs for cyber-physical social systems (CPSS) is a challenge.  ...  In particular, a user could reason why a link was recommended based on the observed metric weights.  ... 
arXiv:2006.16858v1 fatcat:w53nldzryrb4jngyczyenktr3a

An Attentional Recurrent Neural Network for Personalized Next Location Recommendation

Qing Guo, Zhu Sun, Jie Zhang, Yin-Leng Theng
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
In particular, we first design a meta-path based random walk over a novel knowledge graph to discover location neighbors based on heterogeneous factors.  ...  A recurrent neural network is then adopted to model the sequential regularity by capturing various contexts that govern user mobility.  ...  We first design a meta-path based random walk on a novel knowledge graph to discover relevant neighbors based on heterogeneous factors.  ... 
doi:10.1609/aaai.v34i01.5337 fatcat:nfd3l2eu25bnncqc3fhlkcxmoy

Cyber Threat Intelligence Modeling Based on Heterogeneous Graph Convolutional Network

Jun Zhao, Qiben Yan, Xudong Liu, Bo Li, Guangsheng Zuo
2020 International Symposium on Recent Advances in Intrusion Detection  
To explore intricate security knowledge, we propose a threat intelligence computing framework based on graph convolutional networks for effective knowledge discovery.  ...  We then model the interdependent relationships among IOCs using a newly constructed heterogeneous information network (HIN).  ...  Acknowledgement We would like to thank our shepherd Tobias Fiebig, and the anonymous reviewers for providing valuable feedback on our work.  ... 
dblp:conf/raid/0017YL0Z20 fatcat:hl5wt5spzvatlpkb3wm5xuwln4

A Knowledge Graph based Approach for Mobile Application Recommendation [article]

Mingwei Zhang, Jiawei Zhao, Hai Dong, Ke Deng, Ying Liu
2020 arXiv   pre-print
Extensive experiments conducted on a real-world dataset validate the effectiveness of the proposed approach compared to the state-of-the-art recommendation approaches.  ...  To meet this challenge, we proposed a novel end-to-end Knowledge Graph Convolutional Embedding Propagation Model (KGEP) for app recommendation.  ...  [10] exploited weighted meta-graph and heterogeneous information network for mobile app recommendation, mainly considering user review information. However, it is not an end-to-end method.  ... 
arXiv:2009.08621v1 fatcat:vzmneguhdzhddpyas75kmyfgby

Metapaths guided Neighbors aggregated Network for?Heterogeneous Graph Reasoning [article]

Bang Lin, Xiuchong Wang, Yu Dong, Chengfu Huo, Weijun Ren, Chuanyu Xu
2021 arXiv   pre-print
We conduct extensive experiments for the proposed MHN on three real-world heterogeneous graph datasets, including node classification, link prediction and online A/B test on Alibaba mobile application.  ...  To address these limitations, we propose a Metapaths-guided Neighbors-aggregated Heterogeneous Graph Neural Network(MHN) to improve performance.  ...  Online A/B Test We deploy our inductive model MHN on Alibaba mobile application for it's recall process of recommendation system.  ... 
arXiv:2103.06474v1 fatcat:rt7lwzapebccrg3ta4zrztwc4u

Provisional Access of Workflow Scheduling with Mobile Agents in Agricultural Application

2020 International journal of recent technology and engineering  
Here, MATLAB environment is used for simulation. Metrics like cost, Make span is evaluated for agricultural dataset. Comparison is done with anticipated Dense mobile Network and Deep Q Network.  ...  As, building an accurate and effectual model with constraint time is also an essential factor, specifically for difficult conditions, this work initiates reinforcement model base learning approach based  ...  However, weight based item set is needed for scheduling workflow of mobile application and to compute input state of agriculture based application.  ... 
doi:10.35940/ijrte.f8048.038620 fatcat:6kitget35fdh5hqldhdkfdqzfq

A Hybrid Service Recommendation Prototype Adapted for the UCWW: A Smart-City Orientation

Haiyang Zhang, Ivan Ganchev, Nikola S. Nikolov, Zhanlin Ji, Máirtín O'Droma
2017 Wireless Communications and Mobile Computing  
To alleviate these problems, this paper proposes a hybrid service recommendation prototype utilizing user and item side information, which naturally constitute a heterogeneous information network (HIN)  ...  Two recommendation models defined at both global and personalized level are proposed, with model learning based on the Bayesian Personalized Ranking (BPR).  ...  Disclosure This paper is extended from the paper entitled "Hybrid Recommendation for Sparse Rating Matrix: A Heterogeneous Information Network Approach," presented at the IAEAC 2017.  ... 
doi:10.1155/2017/6783240 fatcat:yxnsas7h6rei3f7pxz6633d36u
« Previous Showing results 1 — 15 out of 6,975 results