Content-Restricted Boltzmann Machines for Diet Recommendation

Title

Content-Restricted Boltzmann Machines for Diet Recommendation

Creator

Deshmukh V.M.; Shukla S.

Description

Nowadays, society is leading towards an unhealthy and inactive and lifestyle. Recent studies show the rapid growth of people suffering from diseases caused due to unhealthy lifestyles and diet. Considering this, recognizing the right type and amount of food to eat with a suitable exercise set is essential to obtain good health. The proposed work develops a framework to recommend the proper diet plans for thyroid patients, and medical experts validate results. The experiments results illustrate that the proposed Content-Restricted Boltzmann Machines (Content-RBM) produces more relevant recommendations with content-based information. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-290, pp. 114-121.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Content-based features; Diet and exercise plans; Recommender system; Restricted Boltzmann Machines; Thyroid disease

Coverage

Deshmukh V.M., New Horizon College of Engineering, Bengaluru, India; Shukla S., Christ University, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981164485-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-16-4486-3_12

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115076578&doi=10.1007%2f978-981-16-4486-3_12&partnerID=40&md5=489760b3bb558236031b34cc69a568e8