Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices

Wolfgang Woerndl; Henrik Muehe; Stefan Rothlehner; Korbinian Moegele

doi:10.1007/978-3-642-12607-9_29

Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices

Wolfgang Woerndl, Henrik Muehe, Stefan Rothlehner, Korbinian Moegele

Informatics 11 - Chair of Connected Mobility

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The goal of the work presented in this paper is to design a context-aware recommender system for mobile devices. The approach is based on decentralized, item-based collaborative filtering on Personal Digital Assistants (PDAs). The already implemented system exchanges rating vectors among PDAs, computes local matrices of item similarity and utilizes them to generate recommendations. We then explain how to contextualize this recommender system according to the current time and position of the user. The idea is to use a weighted combination of the collaborative filtering score with a context score function. We are currently working on applying this approach in real world scenarios.

Original language	English
Title of host publication	Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers
Pages	383-392
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-12607-9_29
State	Published - 2010
Event	1st International ICST Conference on Mobile Computing, Applications, and Services, MobiCASE 2009, Held in Conjunction with the 1st Workshop on Innovative Mobile User Interactivity, WIMUI - San Diego, CA, United States Duration: 26 Oct 2009 → 29 Oct 2009

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume	35 LNICST
ISSN (Print)	1867-8211

Conference

Conference	1st International ICST Conference on Mobile Computing, Applications, and Services, MobiCASE 2009, Held in Conjunction with the 1st Workshop on Innovative Mobile User Interactivity, WIMUI
Country/Territory	United States
City	San Diego, CA
Period	26/10/09 → 29/10/09

Keywords

Collaborative filtering
Context
Item-based collaborative filtering
Mobile guides

Access to Document

10.1007/978-3-642-12607-9_29

Cite this

Woerndl, W., Muehe, H., Rothlehner, S., & Moegele, K. (2010). Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices. In Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers (pp. 383-392). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; Vol. 35 LNICST). https://doi.org/10.1007/978-3-642-12607-9_29

Woerndl, Wolfgang ; Muehe, Henrik ; Rothlehner, Stefan et al. / Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices. Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers. 2010. pp. 383-392 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).

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title = "Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices",

abstract = "The goal of the work presented in this paper is to design a context-aware recommender system for mobile devices. The approach is based on decentralized, item-based collaborative filtering on Personal Digital Assistants (PDAs). The already implemented system exchanges rating vectors among PDAs, computes local matrices of item similarity and utilizes them to generate recommendations. We then explain how to contextualize this recommender system according to the current time and position of the user. The idea is to use a weighted combination of the collaborative filtering score with a context score function. We are currently working on applying this approach in real world scenarios.",

keywords = "Collaborative filtering, Context, Item-based collaborative filtering, Mobile guides",

author = "Wolfgang Woerndl and Henrik Muehe and Stefan Rothlehner and Korbinian Moegele",

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note = "1st International ICST Conference on Mobile Computing, Applications, and Services, MobiCASE 2009, Held in Conjunction with the 1st Workshop on Innovative Mobile User Interactivity, WIMUI ; Conference date: 26-10-2009 Through 29-10-2009",

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Woerndl, W, Muehe, H, Rothlehner, S & Moegele, K 2010, Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices. in Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, vol. 35 LNICST, pp. 383-392, 1st International ICST Conference on Mobile Computing, Applications, and Services, MobiCASE 2009, Held in Conjunction with the 1st Workshop on Innovative Mobile User Interactivity, WIMUI, San Diego, CA, United States, 26/10/09. https://doi.org/10.1007/978-3-642-12607-9_29

Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices. / Woerndl, Wolfgang; Muehe, Henrik; Rothlehner, Stefan et al.
Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers. 2010. p. 383-392 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; Vol. 35 LNICST).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Woerndl, Wolfgang

AU - Muehe, Henrik

AU - Rothlehner, Stefan

AU - Moegele, Korbinian

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N2 - The goal of the work presented in this paper is to design a context-aware recommender system for mobile devices. The approach is based on decentralized, item-based collaborative filtering on Personal Digital Assistants (PDAs). The already implemented system exchanges rating vectors among PDAs, computes local matrices of item similarity and utilizes them to generate recommendations. We then explain how to contextualize this recommender system according to the current time and position of the user. The idea is to use a weighted combination of the collaborative filtering score with a context score function. We are currently working on applying this approach in real world scenarios.

AB - The goal of the work presented in this paper is to design a context-aware recommender system for mobile devices. The approach is based on decentralized, item-based collaborative filtering on Personal Digital Assistants (PDAs). The already implemented system exchanges rating vectors among PDAs, computes local matrices of item similarity and utilizes them to generate recommendations. We then explain how to contextualize this recommender system according to the current time and position of the user. The idea is to use a weighted combination of the collaborative filtering score with a context score function. We are currently working on applying this approach in real world scenarios.

KW - Collaborative filtering

KW - Context

KW - Item-based collaborative filtering

KW - Mobile guides

UR - https://www.scopus.com/pages/publications/84885887694

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DO - 10.1007/978-3-642-12607-9_29

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T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering

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BT - Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers

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Y2 - 26 October 2009 through 29 October 2009

ER -

Woerndl W, Muehe H, Rothlehner S, Moegele K. Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices. In Mobile Computing, Applications, and Services - First International ICST Conference, MobiCASE 2009, Revised Selected Papers. 2010. p. 383-392. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering). doi: 10.1007/978-3-642-12607-9_29

Context-aware recommendations in decentralized, item-based collaborative filtering on mobile devices

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Keywords

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