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 Yuxiao Dong

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Average citations per article5.11
Citation Count92
Publication count18
Publication years2012-2017
Available for download9
Average downloads per article584.00
Downloads (cumulative)5,256
Downloads (12 Months)2,356
Downloads (6 Weeks)313
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18 results found Export Results: bibtexendnoteacmrefcsv

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1 published by ACM
August 2017 KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 53,   Downloads (12 Months): 487,   Downloads (Overall): 487

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Progress in science has advanced the development of human society across history, with dramatic revolutions shaped by information theory, genetic cloning, and artificial intelligence, among the many scientific achievements produced in the 20th century. However, the way that science advances itself is much less well-understood. In this work, we study ...
Keywords: scientific impact, funding policy, big data, microsoft academic graph, diversity in science, science of science

2 published by ACM
August 2017 KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 174,   Downloads (12 Months): 1,019,   Downloads (Overall): 1,019

Full text available: PDFPDF
We study the problem of representation learning in heterogeneous networks. Its unique challenges come from the existence of multiple types of nodes and links, which limit the feasibility of the conventional network embedding techniques. We develop two scalable representation learning models, namely metapath2vec and metapath2vec++ . The metapath2vec model formalizes ...
Keywords: network embedding, latent representations, feature learning, heterogeneous information networks, heterogeneous representation learning

3 published by ACM
August 2017 KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 22,   Downloads (12 Months): 188,   Downloads (Overall): 188

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A widely recognized organizing principle of networks is structural homophily, which suggests that people with more common neighbors are more likely to connect with each other. However, what influence the diverse structures embedded in common neighbors have on link formation is much less well-understood. To explore this problem, we begin ...
Keywords: big data, embeddedness, network diversity, network signature, triadic closure, link prediction, social networks

4 published by ACM
July 2017 ACM Transactions on Information Systems (TOIS) - Special issue: Search, Mining and their Applications on Mobile Devices: Volume 35 Issue 4, August 2017
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 18,   Downloads (12 Months): 89,   Downloads (Overall): 89

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Users with demographic profiles in social networks offer the potential to understand the social principles that underpin our highly connected world, from individuals, to groups, to societies. In this article, we harness the power of network and data sciences to model the interplay between user demographics and social behavior and ...
Keywords: Gender and age, ego networks, computational social science, mobile communication, demographic prediction, mobile phone data, node attributes, social tie and triad

5 published by ACM
February 2016 WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 14,   Downloads (12 Months): 118,   Downloads (Overall): 324

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This proposal aims to harness the power of data, social, and network sciences to model user behavior in social networks. Specifically, we focus on individual users and investigate the interplay between their behavior and subsequently emergent social phenomena. Work in this proposal unveils the significant social strategies that are used ...
Keywords: computational social science, social impact, user behavior

6
September 2015 ECML PKDD 2015: Proceedings, Part III, of the European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 9286
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

A widely used measure of scientific impact is citations. However, due to their power-law distribution, citations are fundamentally difficult to predict. Instead, to characterize scientific impact, we address two analogous questions asked by many scientific researchers: "How will my h-index evolve over time, and which of my previously or newly ...

7
September 2015 ECMLPKDD'15: Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III
Publisher: Springer
Bibliometrics:
Citation Count: 0

A widely used measure of scientific impact is citations. However, due to their power-law distribution, citations are fundamentally difficult to predict. Instead, to characterize scientific impact, we address two analogous questions asked by many scientific researchers: "How will my h -index evolve over time, and which of my previously or ...

8
September 2015 ECMLPKDD'15: Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Publisher: Springer
Bibliometrics:
Citation Count: 0

The pervasiveness and availability of mobile phone data offer the opportunity of discovering usable knowledge about crowd behavior in urban environments. Cities can leverage such knowledge to provide better services (e.g., public transport planning, optimized resource allocation) and safer environment. Call Detail Record (CDR) data represents a practical data source ...

9
September 2015 ECML PKDD 2015: Proceedings, Part III, of the European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 9286
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

In this work, we unveil the evolution of social relationships across the lifespan. This evolution reflects the dynamic social strategies that people use to fulfill their social needs. For this work we utilize a large mobile network complete with user demographic information. We find that while younger individuals are active ...

10
September 2015 ECML PKDD 2015: Proceedings, Part II, of the European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 9285
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 1

The pervasiveness and availability of mobile phone data offer the opportunity of discovering usable knowledge about crowd behavior in urban environments. Cities can leverage such knowledge to provide better services e.g., public transport planning, optimized resource allocation and safer environment. Call Detail Record CDR data represents a practical data source ...

11
September 2015 ECMLPKDD'15: Proceedings of the 2015th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III
Publisher: Springer
Bibliometrics:
Citation Count: 0

In this work, we unveil the evolution of social relationships across the lifespan. This evolution reflects the dynamic social strategies that people use to fulfill their social needs. For this work we utilize a large mobile network complete with user demographic information. We find that while younger individuals are active ...

12 published by ACM
August 2015 ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015
Publisher: ACM
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 2,   Downloads (12 Months): 15,   Downloads (Overall): 83

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Collaboration is an integral element of the scientific process that often leads to findings with significant impact. While extensive efforts have been devoted to quantifying and predicting research impact, the question of how collaborative behavior influences scientific impact remains unaddressed. In this work, we study the interplay between scientists' collaboration ...
Keywords: Science of Science, Scientific Impact, Scientific Success, Academic Social Network, Collaboration Signature

13 published by ACM
August 2015 KDD '15: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 12
Downloads (6 Weeks): 9,   Downloads (12 Months): 173,   Downloads (Overall): 985

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We study the problem of link prediction in coupled networks , where we have the structure information of one (source) network and the interactions between this network and another (target) network. The goal is to predict the missing links in the target network. The problem is extremely challenging as we ...
Keywords: mobile communication networks, coupled networks, healthcare, link prediction, social networks

14 published by ACM
February 2015 WSDM '15: Proceedings of the Eighth ACM International Conference on Web Search and Data Mining
Publisher: ACM
Bibliometrics:
Citation Count: 8
Downloads (6 Weeks): 6,   Downloads (12 Months): 89,   Downloads (Overall): 507

Full text available: PDFPDF
Scientific impact plays a central role in the evaluation of the output of scholars, departments, and institutions. A widely used measure of scientific impact is citations, with a growing body of literature focused on predicting the number of citations obtained by any given publication. The effectiveness of such predictions, however, ...
Keywords: citation prediction, science of science, popularity prediction, scientific impact

15 published by ACM
August 2014 KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
Publisher: ACM
Bibliometrics:
Citation Count: 30
Downloads (6 Weeks): 16,   Downloads (12 Months): 179,   Downloads (Overall): 1,575

Full text available: PDFPDF
Demographics are widely used in marketing to characterize different types of customers. However, in practice, demographic information such as age, gender, and location is usually unavailable due to privacy and other reasons. In this paper, we aim to harness the power of big data to automatically infer users' demographics based ...
Keywords: demographic prediction, mobile social network, human communication, social strategy

16
September 2013 ECMLPKDD'13: Proceedings of the 2013th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Call duration analysis is a key issue for understanding underlying patterns of (mobile) phone users. In this paper, we study to which extent the duration of a call between users can be predicted in a dynamic mobile network. We have collected a mobile phone call data from a mobile operating ...

17
September 2013 ECML PKDD 2013: Proceedings, Part II, of the European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 8189
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

Call duration analysis is a key issue for understanding underlying patterns of mobile phone users. In this paper, we study to which extent the duration of a call between users can be predicted in a dynamic mobile network. We have collected a mobile phone call data from a mobile operating ...

18
December 2012 ICDM '12: Proceedings of the 2012 IEEE 12th International Conference on Data Mining
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 33

Link prediction and recommendation is a fundamental problem in social network analysis. The key challenge of link prediction comes from the sparsity of networks due to the strong disproportion of links that they have potential to form to links that do form. Most previous work tries to solve the problem ...
Keywords: Social network analysis, Link prediction, Recommendation, Factor graph, Heterogeneous networks



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