SmartRecepies: Towards Cooking and Food Shopping Integration via Mobile Recipes Recommender System
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10422759" target="_blank" >RIV/00216208:11320/20:10422759 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1145/3428757.3429096" target="_blank" >https://doi.org/10.1145/3428757.3429096</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3428757.3429096" target="_blank" >10.1145/3428757.3429096</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
SmartRecepies: Towards Cooking and Food Shopping Integration via Mobile Recipes Recommender System
Popis výsledku v původním jazyce
Recommender systems are now part of our daily life more than ever and most users are confronted with some form of recommendation on a daily basis. As users of such systems, we don't need to actively seek for new content, but let it be comfortably recommended to us instead. One of the important parts of our lives that is yet to be covered in this way is the domain of cooking. A traditional dilemma of a person, who is currently in the process of shopping for food is "What else should I buy, so that I can cook something new?" In another words, the person either has to look for novel recipes upfront (which does not have to correspond with available ingredients in the shop), or buy ingredients intuitively (which does not have to correspond with recipes). The main objective of this paper is to bind cooking and shopping activities together via a mobile recipes recommendation application. The application responds on the content of a user's shopping list and strives for calibration of recommended recipes. In an online user study, we also show that calibrated recommendations outperform both diversity enhanced and plain similarity-based recommendations.
Název v anglickém jazyce
SmartRecepies: Towards Cooking and Food Shopping Integration via Mobile Recipes Recommender System
Popis výsledku anglicky
Recommender systems are now part of our daily life more than ever and most users are confronted with some form of recommendation on a daily basis. As users of such systems, we don't need to actively seek for new content, but let it be comfortably recommended to us instead. One of the important parts of our lives that is yet to be covered in this way is the domain of cooking. A traditional dilemma of a person, who is currently in the process of shopping for food is "What else should I buy, so that I can cook something new?" In another words, the person either has to look for novel recipes upfront (which does not have to correspond with available ingredients in the shop), or buy ingredients intuitively (which does not have to correspond with recipes). The main objective of this paper is to bind cooking and shopping activities together via a mobile recipes recommendation application. The application responds on the content of a user's shopping list and strives for calibration of recommended recipes. In an online user study, we also show that calibrated recommendations outperform both diversity enhanced and plain similarity-based recommendations.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/GJ19-22071Y" target="_blank" >GJ19-22071Y: Flexibilní modely pro hledání známé scény v rozsáhlých kolekcích videa</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
iiWAS '20: Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services
ISBN
978-1-4503-8922-8
ISSN
—
e-ISSN
—
Počet stran výsledku
6
Strana od-do
210-215
Název nakladatele
ACM
Místo vydání
New York, USA
Místo konání akce
Chiang Mai Thailand
Datum konání akce
30. 11. 2020
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—