Blockchain-based recommender systems: Applications, challenges and future opportunities
<p dir="ltr">Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , , , , , , , |
| منشور في: |
2022
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| _version_ | 1864513553309892608 |
|---|---|
| author | Yassine Himeur (14158821) |
| author2 | Aya Sayed (14779249) Abdullah Alsalemi (6951986) Faycal Bensaali (12427401) Abbes Amira (6952001) Iraklis Varlamis (9288743) Magdalini Eirinaki (17148400) Christos Sardianos (8297297) George Dimitrakopoulos (16855419) |
| author2_role | author author author author author author author author |
| author_facet | Yassine Himeur (14158821) Aya Sayed (14779249) Abdullah Alsalemi (6951986) Faycal Bensaali (12427401) Abbes Amira (6952001) Iraklis Varlamis (9288743) Magdalini Eirinaki (17148400) Christos Sardianos (8297297) George Dimitrakopoulos (16855419) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yassine Himeur (14158821) Aya Sayed (14779249) Abdullah Alsalemi (6951986) Faycal Bensaali (12427401) Abbes Amira (6952001) Iraklis Varlamis (9288743) Magdalini Eirinaki (17148400) Christos Sardianos (8297297) George Dimitrakopoulos (16855419) |
| dc.date.none.fl_str_mv | 2022-02-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.cosrev.2021.100439 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Blockchain-based_recommender_systems_Applications_challenges_and_future_opportunities/24311905 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Cybersecurity and privacy Distributed computing and systems software Machine learning Recommender systems Blockchain Security and privacy preservation Decentralized and collaborative recommender systems Big data and machine learning Scalability |
| dc.title.none.fl_str_mv | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include sensitive information, yet most recommender systems are focusing on the models’ accuracy and ignore issues related to security and the users’ privacy. Despite the efforts to overcome these problems using different risk reduction techniques, none of them has been completely successful in ensuring cryptographic security and protection of the users’ private information. To bridge this gap, the blockchain technology is presented as a promising strategy to promote security and privacy preservation in recommender systems, not only because of its security and privacy salient features, but also due to its resilience, adaptability, fault tolerance and trust characteristics. This paper presents a holistic review of blockchain-based recommender systems covering challenges, open issues and solutions. Accordingly, a well-designed taxonomy is introduced to describe the security and privacy challenges, overview existing frameworks and discuss their applications and benefits when using blockchain before indicating opportunities for future research.</p><h2>Other Information</h2><p dir="ltr">Published in: Computer Science Review<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.cosrev.2021.100439" target="_blank">https://dx.doi.org/10.1016/j.cosrev.2021.100439</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_227f7b4b539a3bbdfadec60cebf4cda5 |
| identifier_str_mv | 10.1016/j.cosrev.2021.100439 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24311905 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Blockchain-based recommender systems: Applications, challenges and future opportunitiesYassine Himeur (14158821)Aya Sayed (14779249)Abdullah Alsalemi (6951986)Faycal Bensaali (12427401)Abbes Amira (6952001)Iraklis Varlamis (9288743)Magdalini Eirinaki (17148400)Christos Sardianos (8297297)George Dimitrakopoulos (16855419)Information and computing sciencesCybersecurity and privacyDistributed computing and systems softwareMachine learningRecommender systemsBlockchainSecurity and privacy preservationDecentralized and collaborative recommender systemsBig data and machine learningScalability<p dir="ltr">Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include sensitive information, yet most recommender systems are focusing on the models’ accuracy and ignore issues related to security and the users’ privacy. Despite the efforts to overcome these problems using different risk reduction techniques, none of them has been completely successful in ensuring cryptographic security and protection of the users’ private information. To bridge this gap, the blockchain technology is presented as a promising strategy to promote security and privacy preservation in recommender systems, not only because of its security and privacy salient features, but also due to its resilience, adaptability, fault tolerance and trust characteristics. This paper presents a holistic review of blockchain-based recommender systems covering challenges, open issues and solutions. Accordingly, a well-designed taxonomy is introduced to describe the security and privacy challenges, overview existing frameworks and discuss their applications and benefits when using blockchain before indicating opportunities for future research.</p><h2>Other Information</h2><p dir="ltr">Published in: Computer Science Review<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.cosrev.2021.100439" target="_blank">https://dx.doi.org/10.1016/j.cosrev.2021.100439</a></p>2022-02-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.cosrev.2021.100439https://figshare.com/articles/journal_contribution/Blockchain-based_recommender_systems_Applications_challenges_and_future_opportunities/24311905CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/243119052022-02-01T00:00:00Z |
| spellingShingle | Blockchain-based recommender systems: Applications, challenges and future opportunities Yassine Himeur (14158821) Information and computing sciences Cybersecurity and privacy Distributed computing and systems software Machine learning Recommender systems Blockchain Security and privacy preservation Decentralized and collaborative recommender systems Big data and machine learning Scalability |
| status_str | publishedVersion |
| title | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| title_full | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| title_fullStr | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| title_full_unstemmed | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| title_short | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| title_sort | Blockchain-based recommender systems: Applications, challenges and future opportunities |
| topic | Information and computing sciences Cybersecurity and privacy Distributed computing and systems software Machine learning Recommender systems Blockchain Security and privacy preservation Decentralized and collaborative recommender systems Big data and machine learning Scalability |