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MobHinter: epidemic collaborative filtering and self-organization in mobile ad-hoc networks

Published: 23 October 2008 Publication History

Abstract

We focus on collaborative filtering dealing with self-organizing communities, host mobility, wireless access, and ad-hoc communications. In such a domain, knowledge representation and users profiling can be hard; remote servers can be often unreachable due to client mobility; and feedback ratings collected during random connections to other users' ad-hoc devices can be useless, because of natural differences between human beings. Our approach is based on so called Affinity Networks, and on a novel system, called MobHinter, that epidemically spreads recommendations through spontaneous similarities between users. Main results of our study are two fold: firstly, we show how to reach comparable recommendation accuracies in the mobile domain as well as in a complete knowledge scenario; secondly, we propose epidemic collaborative strategies that can reduce rapidly and realistically the cold start problem.

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cover image ACM Conferences
RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems
October 2008
348 pages
ISBN:9781605580937
DOI:10.1145/1454008
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 October 2008

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Author Tags

  1. ad-hoc networks
  2. recommender systems
  3. social collaborative filtering

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RecSys08: ACM Conference on Recommender Systems
October 23 - 25, 2008
Lausanne, Switzerland

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Overall Acceptance Rate 254 of 1,295 submissions, 20%

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  • (2023)Distributed Data Minimization for Decentralized Collaborative Filtering SystemsProceedings of the 24th International Conference on Distributed Computing and Networking10.1145/3571306.3571400(140-149)Online publication date: 4-Jan-2023
  • (2022)Evolving Bipartite Model Reveals the Bounded Weights in Mobile Social NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2020.301763021:3(971-985)Online publication date: 1-Mar-2022
  • (2021)A Comparative Study of CF And NCF In Children's Book Recommender System2021 3rd International Workshop on Artificial Intelligence and Education (WAIE)10.1109/WAIE54146.2021.00017(43-47)Online publication date: Nov-2021
  • (2020)Classification and Comparison of Web Recommendation Systems used in Online Business2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM)10.1109/ICCAKM46823.2020.9051511(471-480)Online publication date: Jan-2020
  • (2020)Handling Sparsity in Cross-Domain Recommendation Systems: ReviewMicro-Electronics and Telecommunication Engineering10.1007/978-981-15-2329-8_17(163-174)Online publication date: 3-Apr-2020
  • (2019)On gossip-based information dissemination in pervasive recommender systemsProceedings of the 13th ACM Conference on Recommender Systems10.1145/3298689.3347067(442-446)Online publication date: 10-Sep-2019
  • (2018)Integrating Traditional Stores and e-Commerce into a Multi-tiered Recommender System Architecture Supported by IoTInternet and Distributed Computing Systems10.1007/978-3-319-97795-9_5(50-62)Online publication date: 24-Jul-2018
  • (2016)A distributed and multi-tiered software architecture for assessing e-Commerce recommendationsConcurrency and Computation: Practice & Experience10.1002/cpe.379828:18(4507-4531)Online publication date: 25-Dec-2016
  • (2014)Information-Theoretic Term Selection for New Item RecommendationProceedings of the 21st International Symposium on String Processing and Information Retrieval - Volume 879910.1007/978-3-319-11918-2_23(236-243)Online publication date: 20-Oct-2014
  • (2014)Managing Privacy in the Internet of Things: DocCloud, a Use CaseAdvanced Research in Data Privacy10.1007/978-3-319-09885-2_24(443-463)Online publication date: 22-Aug-2014
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