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A Meta-Path-Based Prediction Method for Disease Comorbidities

Eduardo Pantaleón García del Valle, Lucía Prieto Santamaría, Gerardo Lagunes García, Massimiliano Zanin, Ernestina Menasalvas Ruiz, González-Rodríguez
2021 Zenodo  
The use of meta-paths allows the complex semantics of the relationships between the different types of nodes to be included in heterogeneous networks.  ...  The results obtained improve those of similar studies based on biological data, and the predictions calculated for diabetes and Crohn's disease are supported by medical literature.  ...  ACKNOWLEDGMENT The work is a result of the project "DISNET (Creation and analysis of disease networks for drug repurposing from heterogeneous data sources applied to rare diseases)", that is being developed  ... 
doi:10.5281/zenodo.5708639 fatcat:43xkcwoppfhyncvzvnpui5kdly

Machine Learning with World Knowledge: The Position and Survey [article]

Yangqiu Song, Dan Roth
2017 arXiv   pre-print
Machine learning has become pervasive in multiple domains, impacting a wide variety of applications, such as knowledge discovery and data mining, natural language processing, information retrieval, computer  ...  Particularly, labeling large amount of data for each domain-specific problem can be very time consuming and costly.  ...  Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.  ... 
arXiv:1705.02908v1 fatcat:t4fypa6h3vampcp64eosvppsfe

Fraud Detection in Online Product Review Systems via Heterogeneous Graph Transformer

Songkai Tang, Luhua Jin, Fan Cheng
2021 IEEE Access  
Traditional fraud detection algorithm mainly utilizes rule-based methods, which is insufficient for the rich user interactions and graph-structured data.  ...  In recent years, graph-based methods have been proposed to handle this situation, but few prior works have noticed the camouflage fraudster's behavior and inconsistency heterogeneous nature.  ...  To handle inconsistent features, we adopt heterogeneous mutual attention for automatic meta path construction.  ... 
doi:10.1109/access.2021.3084924 fatcat:wzzwnmdptnfm5hvarripls7heu

Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning [article]

Ziyue Qiao, Pengyang Wang, Yanjie Fu, Yi Du, Pengfei Wang, Yuanchun Zhou
2020 arXiv   pre-print
The relational metric learning module aims to preserve the heterogeneity by embedding each type of nodes into a type-specific space with distinct distribution based on similarity metrics.  ...  Some work is proposed to alleviate such issue by exploiting relations or meta-path to sample neighbors with distinct categories, then use attention mechanism to learn different importance for different  ...  On the other hand, meta-path based neighborhoods preserve less structural information relatively than the tree-based neighborhoods.  ... 
arXiv:2008.10003v2 fatcat:rnmuindpgng2vfo47lr5i6lory

Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

Yu Shi, Qi Zhu, Fang Guo, Chao Zhang, Jiawei Han
2018 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18  
Heterogeneous information networks (HINs) are ubiquitous in real-world applications. In the meantime, network embedding has emerged as a convenient tool to mine and learn from networked data.  ...  With the intention to preserve the rich yet potentially incompatible information in HIN embedding, we propose to study the problem of comprehensive transcription of heterogeneous information networks.  ...  Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1145/3219819.3220006 dblp:conf/kdd/ShiZGZ018 fatcat:xnv5qvyp7jdrnpqprcxrecnda4

BiTe-GCN: A New GCN Architecture via BidirectionalConvolution of Topology and Features on Text-Rich Networks [article]

Di Jin, Xiangchen Song, Zhizhi Yu, Ziyang Liu, Heling Zhang, Zhaomeng Cheng, Jiawei Han
2021 arXiv   pre-print
We first transform the original text-rich network into an augmented bi-typed heterogeneous network, capturing both the global node-level information and the local text-sequence information from texts.  ...  Considering that in real world, the information network consists of not only the node-level citation information but also the local text-sequence information.  ...  We then introduce a discriminative joint convolution mechanism, based on the concept of meta-path, which can distinguish and learn out the contributions of network part and text part based on the learning  ... 
arXiv:2010.12157v2 fatcat:fuuemdemu5bfvkoihykkiipbje

Brain Network Organization in Focal Epilepsy: A Systematic Review and Meta-Analysis

Eric van Diessen, Willemiek J. E. M. Zweiphenning, Floor E. Jansen, Cornelis J. Stam, Kees P. J. Braun, Willem M. Otte, Sam Doesburg
2014 PLoS ONE  
Sub-analyses revealed similar results for functional and structural networks in terms of effect size and directionality for both metrics.  ...  Review and Meta-Analysis.  ...  A recent systematic review and meta-analysis of clinical studies provided evidence for widespread structural white matter damage distant from the epileptogenic zone [16] .  ... 
doi:10.1371/journal.pone.0114606 pmid:25493432 pmcid:PMC4262431 fatcat:5xgjqn2nnrfvhjqo3we6drgv7i

Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks [article]

Zifeng Wang and Rui Wen and Xi Chen and Shilei Cao and Shao-Lun Huang and Buyue Qian and Yefeng Zheng
2020 arXiv   pre-print
predefined meta-paths.  ...  We propose a Healthcare Graph Convolutional Network (HealGCN) to offer disease self-diagnosis service for online users, based on the Electronic Healthcare Records (EHRs).  ...  high order connections in the heterogeneous graph by meta-path.  ... 
arXiv:2009.02625v1 fatcat:hjuajp3je5gpln7xju6vl3g3ui

motif2vec: Motif Aware Node Representation Learning for Heterogeneous Networks [article]

Manoj Reddy Dareddy, Mahashweta Das, Hao Yang
2019 arXiv   pre-print
However, most of the methods are not adequate to handle heterogeneous information networks which pretty much represents most real-world data today.  ...  We propose a novel efficient algorithm, motif2vec that learns node representations or embeddings for heterogeneous networks.  ...  The augmentation of A → P → A → P → A path to the directed metapath A → P → V → P → A helps the meta-structure encode semantic relations between distant nodes.  ... 
arXiv:1908.08227v1 fatcat:v2rz4tieyzh4pkr6wajqdfunfq

HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories [article]

Yu Zhang, Frank F. Xu, Sha Li, Yu Meng, Xuan Wang, Qi Li, Jiawei Han
2021 arXiv   pre-print
In recognition of these challenges, we propose the HiGitClass framework, comprising of three modules: heterogeneous information network embedding; keyword enrichment; topic modeling and pseudo document  ...  GitHub has become an important platform for code sharing and scientific exchange. With the massive number of repositories available, there is a pressing need for topic-based search.  ...  We formally define a heterogeneous information network as below: Heterogeneous Information Network (HIN).  ... 
arXiv:1910.07115v2 fatcat:6thrlfurb5dvvn6kgc5ti726n4

A survey on knowledge graph-based recommender systems

Fuzhen ZHUANG, Hui XIONG, Qi ZHANG, Qingyu GUO, Chuan QIN, Chao WANG, Hengshu ZHU, Le ZHANG, Enhong CHEN
2020 Scientia Sinica Informationis  
Such an approach can not only alleviate the above mentioned issues for a more accurate recommendation, but also provide explanations for recommended items.  ...  ., embedding-based methods, connection-based methods, and propagation-based methods. Also, we further subdivide each category according to the characteristics of these approaches.  ...  [21] presented traditional recommendation methods based on the heterogeneous information network, however, latest developed deep learning based models are not covered. Liu et al.  ... 
doi:10.1360/ssi-2019-0274 fatcat:gw5u427ahfdnhdefiv724ns5hy

A Survey on Knowledge Graph-Based Recommender Systems [article]

Qingyu Guo, Fuzhen Zhuang, Chuan Qin, Hengshu Zhu, Xing Xie, Hui Xiong, Qing He
2020 arXiv   pre-print
Such an approach can not only alleviate the abovementioned issues for a more accurate recommendation, but also provide explanations for recommended items.  ...  In recent years, generating recommendations with the knowledge graph as side information has attracted considerable interest.  ...  For convenience, we list some symbols and their descriptions in Table 2 . • Heterogeneous Information Network (HIN).  ... 
arXiv:2003.00911v1 fatcat:qhyca7pu3beqtk6x55kpggowea

Path-Based Reasoning over Heterogeneous Networks for Recommendation via Bidirectional Modeling [article]

Junwei Zhang, Min Gao, Junliang Yu, Linda Yang, Zongwei Wang, Qingyu Xiong
2020 arXiv   pre-print
Heterogeneous Information Network (HIN) is a natural and general representation of data in recommender systems.  ...  To overcome the aforementioned issues, in this paper, we propose a novel path-based reasoning approach for recommendation over HIN.  ...  [29] introduce the concept of meta-path similarity to a HIN-based model. Yu et al.  ... 
arXiv:2008.04185v1 fatcat:5gn2ybrpm5b3zmcyer2yibpeb4

Tutorial on NLP-Inspired Network Embedding [article]

Boaz Shmueli
2019 arXiv   pre-print
Network embedding is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space.  ...  These new methods and developments in online learning of network embeddings have major applications for the analysis of graphs and networks, including online social networks.  ...  As mentioned, the random walks must follow the meta-paths that are hand-designed for the specific network and task. Examples of meta-paths for the academic network are given in Fig. 10 .  ... 
arXiv:1910.07212v1 fatcat:mi7fkwnidfgazccq26ik5eghki

The Evolving Transcriptome of Head and Neck Squamous Cell Carcinoma: A Systematic Review

Yau-Hua Yu, Hsu-Ko Kuo, Kuo-Wei Chang, Suzannah Rutherford
2008 PLoS ONE  
The objective of this review is to conduct a network-based meta-analysis to identify the underlying biological signatures of the HNSCC transcriptome.  ...  Conclusions: By means of a systems-biology approach via network-based meta-analyses, we provided a deeper insight into the evolving nature of the HNSCC transcriptome.  ...  To date, we conducted for the first time a genome-wide meta-analysis in the context of knowledge-based networks and systematic reviews.  ... 
doi:10.1371/journal.pone.0003215 pmid:18791647 pmcid:PMC2533097 fatcat:7f2yy7uba5a3pphh5c27x3toyu
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