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Homepage Augmentation by Predicting Links in Heterogenous Networks

Published: 17 October 2018 Publication History

Abstract

Scholars' homepages are important places to show personal research interest and academic achievement through the Web. However, according to our observation, only a small portion of scholars update their publications and related events on their homepages in time. In this paper, we propose a homepage augmentation technique, which automatically shows the newest academic events related to a scholar on his/her homepage. Specifically, we model the relations between homepages and the events collected from the Web as a complex heterogenous network, and propose an Embedding-based Heterogenous random Walk algorithm, namely EHWalk, to predict the links between homepages and events. Compared with existing embedding-based link prediction algorithms, EHWalk supports more efficient modeling of complex heterogenous relations in a dynamically changing network, which helps link the massive new updated events to homepages precisely and efficiently. Comprehensive experiments on a real-world dataset are conducted and the results show that our algorithm can achieve both good effectiveness and efficiency for real-world deployment.

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cover image ACM Conferences
CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management
October 2018
2362 pages
ISBN:9781450360142
DOI:10.1145/3269206
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 17 October 2018

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Author Tags

  1. embedding
  2. heterogenous networks
  3. homepage augmentation

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  • Short-paper

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  • NSFC
  • CAS Key Lab of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, 100190, Beijing
  • Science and Technology Program of Guangdong Province, China

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CIKM '18
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CIKM '18 Paper Acceptance Rate 147 of 826 submissions, 18%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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