Defining and Supporting Narrative-driven Recommendation

Toine Bogers, Marijn Koolen

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

23 Citationer (Scopus)
7 Downloads (Pure)

Abstract

Research into recommendation algorithms has made great strides in recent years. However, these algorithms are typically applied in relatively straightforward scenarios: given information about a user's past preferences, what will they like in the future? Recommendation is often more complex: evaluating recommended items never takes place in a vacuum, and it is often a single step in the user's more complex background task. In this paper, we define a specific type of recommendation scenario called narrative-driven recommendation, where the recommendation process is driven by both a log of the user's past transactions as well as a narrative description of their current interest(s). Through an analysis of a set of real-world recommendation narratives from the LibraryThing forums, we demonstrate the uniqueness and richness of this scenario and highlight common patterns and properties of such narratives.
OriginalsprogEngelsk
TitelProceedings of the Eleventh ACM Conference on Recommender Systems : RecSys '17
Antal sider5
ForlagAssociation for Computing Machinery
Publikationsdato27 aug. 2017
Sider238-242
ISBN (Elektronisk)978-1-4503-4652-8
DOI
StatusUdgivet - 27 aug. 2017
BegivenhedRecSys 2017: 11th ACM Conference on Recommender Systems - Como, Italy, Como, Italien
Varighed: 27 aug. 201731 aug. 2017
Konferencens nummer: 11
https://recsys.acm.org/recsys17/

Konference

KonferenceRecSys 2017: 11th ACM Conference on Recommender Systems
Nummer11
LokationComo, Italy
Land/OmrådeItalien
ByComo
Periode27/08/201731/08/2017
Internetadresse

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