EventAware: A mobile recommender system for events.
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| Title: | EventAware: A mobile recommender system for events. |
|---|---|
| Authors: | Horowitz, Daniel1, Contreras, David1,2 dcontreras@maia.ub.es, Salamó, Maria1 |
| Source: | Pattern Recognition Letters. Apr2018, Vol. 105, p121-134. 14p. |
| Subjects: | Recommender systems, Existence theorems, User interfaces, Natural language processing, Machine learning |
| Abstract: | Developing a recommender system for events raises several issues that are different from other domains. Events rapidly disappear, users’ preferences quickly change over time, and direct feedback does not exist for events that have not taken place. As the recommendations will not be further available, user’s context become a key factor for providing accurate recommendations. In this paper we introduce EventAware, a context-aware mobile recommender system to personalize the agenda of users attending to a congress. In particular, we first introduce the EventAware system, which includes an intuitive user interface with an attractive design to enhance user experience. EventAware incorporates some implicit contextual information, automatically initializes both the user’s profiles with minimal user interaction and the properties of the items and it uses a context-aware tag-based recommender algorithm. We demonstrate its usability through a live-user case-study in one of the biggest events of mobile technology in the world, held in Barcelona. [ABSTRACT FROM AUTHOR] |
| Copyright of Pattern Recognition Letters is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 128983453 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: EventAware: A mobile recommender system for events. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Horowitz%2C+Daniel%22">Horowitz, Daniel</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Contreras%2C+David%22">Contreras, David</searchLink><relatesTo>1,2</relatesTo><i> dcontreras@maia.ub.es</i><br /><searchLink fieldCode="AR" term="%22Salamó%2C+Maria%22">Salamó, Maria</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Pattern+Recognition+Letters%22">Pattern Recognition Letters</searchLink>. Apr2018, Vol. 105, p121-134. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Recommender+systems%22">Recommender systems</searchLink><br /><searchLink fieldCode="DE" term="%22Existence+theorems%22">Existence theorems</searchLink><br /><searchLink fieldCode="DE" term="%22User+interfaces%22">User interfaces</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Developing a recommender system for events raises several issues that are different from other domains. Events rapidly disappear, users’ preferences quickly change over time, and direct feedback does not exist for events that have not taken place. As the recommendations will not be further available, user’s context become a key factor for providing accurate recommendations. In this paper we introduce EventAware, a context-aware mobile recommender system to personalize the agenda of users attending to a congress. In particular, we first introduce the EventAware system, which includes an intuitive user interface with an attractive design to enhance user experience. EventAware incorporates some implicit contextual information, automatically initializes both the user’s profiles with minimal user interaction and the properties of the items and it uses a context-aware tag-based recommender algorithm. We demonstrate its usability through a live-user case-study in one of the biggest events of mobile technology in the world, held in Barcelona. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Pattern Recognition Letters is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.patrec.2017.07.003 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 121 Subjects: – SubjectFull: Recommender systems Type: general – SubjectFull: Existence theorems Type: general – SubjectFull: User interfaces Type: general – SubjectFull: Natural language processing Type: general – SubjectFull: Machine learning Type: general Titles: – TitleFull: EventAware: A mobile recommender system for events. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Horowitz, Daniel – PersonEntity: Name: NameFull: Contreras, David – PersonEntity: Name: NameFull: Salamó, Maria IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 01678655 Numbering: – Type: volume Value: 105 Titles: – TitleFull: Pattern Recognition Letters Type: main |
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