Link Prediction for Temporal Heterogeneous Networks Based on the Information Lifecycle

Jiaping Cao, Jichao Li () and Jiang Jiang
Additional contact information
Jiaping Cao: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Jichao Li: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Jiang Jiang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Mathematics, 2023, vol. 11, issue 16, 1-17

Abstract: Link prediction for temporal heterogeneous networks is an important task in the field of network science, and it has a wide range of real-world applications. Traditional link prediction methods are mainly based on static homogeneous networks, which do not distinguish between different types of nodes in the real world and do not account for network structure evolution over time. To address these issues, in this paper, we study the link prediction problem in temporal heterogeneous networks and propose a link prediction method for temporal heterogeneous networks (LP-THN) based on the information lifecycle, which is an end-to-end encoder–decoder structure. The information lifecycle accounts for the active, decay and stable states of edges. Specifically, we first introduce the meta-path augmented residual information matrix to preserve the structure evolution mechanism and semantics in HINs, using it as input to the encoder to obtain a low-dimensional embedding representation of the nodes. Finally, the link prediction problem is considered a binary classification problem, and the decoder is utilized for link prediction. Our prediction process accounts for both network structure and semantic changes using meta-path augmented residual information matrix perturbations. Our experiments demonstrate that LP-THN outperforms other baselines in both prediction effectiveness and prediction efficiency.

Keywords: temporal heterogeneous networks; link prediction; information lifecycle; meta-path (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/16/3541/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/16/3541/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:16:p:3541-:d:1218602

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().