Socialized healthcare service recommendation using deep learning

ORCID Identifiers

0000-0002-6921-7369

Document Type

Article

Source of Publication

Neural Computing and Applications

Publication Date

10-1-2018

Abstract

© 2018, The Natural Computing Applications Forum. Socialized recommender system recommends reliable healthcare services for users. Ratings are predicted on the healthcare services by merging recommendations given by users who has social relations with the active users. However, existing works did not consider the influence of distrust between users. They recommend items only based on the trust relations between users. We therefore propose a novel deep learning-based socialized healthcare service recommender model, which recommends healthcare services with recommendations given by recommenders with both trust relations and distrust relations with the active users. The influences of recommenders, considering both the node information and the structure information, are merged via the deep learning model. Experimental results show that the proposed model outperforms the existing works on prediction accuracy and prediction coverage simultaneously, even for cold start users or users with very sparse trust relations. It is also computational less expensive.

ISSN

0941-0643

Publisher

Springer London

Volume

30

Issue

7

First Page

2071

Last Page

2082

Disciplines

Computer Sciences

Keywords

Deep learning, Healthcare service, Service recommendation, Socialized recommendation

Scopus ID

85045058169

Indexed in Scopus

yes

Open Access

no

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