skip to main content
10.1145/1866919.1866934acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
short-paper

A framework for privacy-conducive recommendations

Published: 04 October 2010 Publication History

Abstract

Recommendations and advertisements based on consumer behavior patterns are increasingly prevalent, yet carry significant privacy concerns. We propose an easily implemented alternative framework in which publicly available Web data is mined to discover product preference associations.

References

[1]
}}Alterian. http://www.alterian.com/.
[2]
}}Amazon's Best-Selling Digital Cameras. http://www.amazon.com/s/qid=1264719942/ref=sr_pg_1?ie=UTF8&rs=281052&bbn=281052&rh=n%3A502394%2Cn%3A281052.
[3]
}}Amazon's Product Advertising API. http://docs.amazonwebservices.com/AWSECommerceService/latest/DG/.
[4]
}}Google AJAX Search API. http://code.google.com/apis/ajaxsearch/.
[5]
}}Google Result Count Varies. http://code.google.com/p/google-ajax-apis/issues/detail?id=32.
[6]
}}IMDB. http://www.imdb.com/.
[7]
}}IMDB Plot Keywords for "Avatar". http://www.imdb.com/title/tt0499549/keywords.
[8]
}}Netflix Dataset. http://www.netflixprize.com//download.
[9]
}}Yahoo! Movies. http://movies.yahoo.com/.
[10]
}}Yahoo! Web Search API. http://developer.yahoo.com/search/web/.
[11]
}}R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo. Fast discovery of association rules. pages 307--328, 1996.
[12]
}}R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In VLDB '94: Proceedings of the 20th International Conference on Very Large Data Bases, pages 487--499, San Francisco, CA, USA, 1994. Morgan Kaufmann Publishers Inc.
[13]
}}J. Canny. Collaborative Filtering with privacy. In SP '02: Proceedings of the 2002 IEEE Symposium on Security and Privacy, page 45, Washington, DC, USA, 2002. IEEE Computer Society.
[14]
}}R. Chow, P. Golle, and J. Staddon. Detecting privacy leaks using corpus-based association rules. In KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 893--901, New York, NY, USA, 2008. ACM.
[15]
}}R. Chow and J. Staddon. A Framework for Privacy-Conducive Recommendations. http://docs.google.com/a/jessicastaddon.com/viewer?a=v&pid=sites&srcid=amVzc2ljYXN0YWRkb24uY29tfGhvbWV8Z3g6MjY3M2JkZGRhZGEzOTQxZQ.
[16]
}}S. Guha, B. Cheng, A. Reznichenko, H. Haddadi, and P. Francis. Privad: Rearchitecting online advertising for privacy. In Technical Report, Max Planck Institute for Software Systems, 2009.
[17]
}}R. F. J. Claessens, C. Diaz and B. Preneel. A secure and privacy-preserving web banner system for targeted advertising. In Electronic Commerce Research, 2003.
[18]
}}A. Juels. Targeted advertising... and privacy too. In CT-RSA 2001: Proceedings of the 2001 Conference on Topics in Cryptology, pages 408--424, London, UK, 2001. Springer-Verlag.
[19]
}}R. Paul. Privacy advocates want regulation of behavioral advertising. In Ars Technica, 2009.
[20]
}}H. Polat and W. Du. Privacy-preserving collaborative Filtering using randomized perturbation techniques. In ICDM '03: Proceedings of the Third IEEE International Conference on Data Mining, page 625, Washington, DC, USA, 2003. IEEE Computer Society.
[21]
}}R. Shokri, P. Pedarsani, G. Theodorakopoulos, and J.-P. Hubaux. Preserving privacy in collaborative filtering through distributed aggregation of offine profiles. In RecSys '09: Proceedings of the third ACM conference on Recommender systems, pages 157--164, New York, NY, USA, 2009. ACM.
[22]
}}V. Toubiana, A. Narayanan, D. Boneh, H. Nissenbaum, and S. Barocas. Adnostic: Privacy preserving targeted advertising. In NDSS, 2010.
[23]
}}P. D. Turney. Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL. In EMCL '01: Proceedings of the 12th European Conference on Machine Learning, pages 491--502, London, UK, 2001. Springer-Verlag.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
WPES '10: Proceedings of the 9th annual ACM workshop on Privacy in the electronic society
October 2010
136 pages
ISBN:9781450300964
DOI:10.1145/1866919
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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 October 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. privacy
  2. search engines
  3. web mining

Qualifiers

  • Short-paper

Conference

CCS '10
Sponsor:

Acceptance Rates

Overall Acceptance Rate 106 of 355 submissions, 30%

Upcoming Conference

CCS '25

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 215
    Total Downloads
  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media