Using Implicit Preference Relations to Improve Content Based Recommending

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F15%3A10314898" target="_blank" >RIV/00216208:11320/15:10314898 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-27729-5_1" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-27729-5_1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-27729-5_1" target="_blank" >10.1007/978-3-319-27729-5_1</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using Implicit Preference Relations to Improve Content Based Recommending

Popis výsledku v původním jazyce

Our work is generally focused on recommending for small or medium-sized e-commerce portals, where we are facing scarcity of explicit feedback, low user loyalty, short visit times or low number of visited objects. In this paper, we present a novel approach to use specific user behavior as implicit feedback, forming binary relations between objects. Our hypothesis is that if user select some object from the list of displayed objects, it is an expression of his/her binary preference between selected and other shown objects. These relations are expanded based on content-based similarity of objects forming partial ordering of objects. Using these relations, it is possible to alter any list of recommended objects or create one from scratch. We have conductedseveral off-line experiments with real user data from a Czech e-commerce site with keyword based VSM and SimCat recommenders. Experiments confirmed competitiveness of our method, however on-line A/B testing should be conducted in the fut

Název v anglickém jazyce

Using Implicit Preference Relations to Improve Content Based Recommending

Popis výsledku anglicky

Our work is generally focused on recommending for small or medium-sized e-commerce portals, where we are facing scarcity of explicit feedback, low user loyalty, short visit times or low number of visited objects. In this paper, we present a novel approach to use specific user behavior as implicit feedback, forming binary relations between objects. Our hypothesis is that if user select some object from the list of displayed objects, it is an expression of his/her binary preference between selected and other shown objects. These relations are expanded based on content-based similarity of objects forming partial ordering of objects. Using these relations, it is possible to alter any list of recommended objects or create one from scratch. We have conductedseveral off-line experiments with real user data from a Czech e-commerce site with keyword based VSM and SimCat recommenders. Experiments confirmed competitiveness of our method, however on-line A/B testing should be conducted in the fut

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

E-Commerce and Web Technologies, 16th International Conference on Electronic Commerce and Web Technologies, EC-Web 2015, Valencia, Spain, September 2015, Revised Selected Papers

ISBN

978-3-319-27728-8

ISSN

1865-1348

e-ISSN

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Počet stran výsledku

14

Strana od-do

3-16

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Valencia, Spain

Datum konání akce

1. 9. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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