Fetching the paper…
Reading the bibliography…
In many industrial applications of big data, the Jaccard Similarity Computation has been widely used to measure the distance between two profiles or sets respectively owned by two users.
Randomized response: A survey technique for eliminating evasive answer bias
Stanley L. Warner · 1965
Earlier work this paper cites.
On the resemblance and containment of documents
Andrei Z. Broder · 1997
Earlier work this paper cites.
Min-wise independent permutations (extended abstract)
Andrei Z. Broder, Moses Charikar, Alan M. Frieze, and Michael Mitzenmacher · 1998
Earlier work this paper cites.
Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources
Bill Dolan, Chris Quirk, and Chris Brockett · 2004
Earlier work this paper cites.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam D. Smith · 2006
Earlier work this paper cites.
Google news personalization: scalable online collaborative filtering
Abhinandan Das, Mayur Datar, Ashutosh Garg, and Shyamsundar Rajaram · 2007
Earlier work this paper cites.
Mechanism design via differential privacy
Frank McSherry and Kunal Talwar · 2007
Earlier work this paper cites.
Privacy integrated queries: an extensible platform for privacy-preserving data analysis
Frank McSherry · 2009
Earlier work this paper cites.
Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions
Kavita Ganesan, ChengXiang Zhai, and Jiawei Han · 2010
Cited alongside, same era.
Private similarity computation in distributed systems: From cryptography to differential privacy
Mohammad Alaggan, Sébastien Gambs, and Anne-Marie Kermarrec · 2011
Cited alongside, same era.
BLIP: non-interactive differentially-private similarity computation on bloom filters
Mohammad Alaggan, Sébastien Gambs, and Anne-Marie Kermarrec · 2012
Cited alongside, same era.
Verified computational differential privacy with applications to smart metering
Gilles Barthe, George Danezis, Benjamin Grégoire, César Kunz, and Santiago Zanella Béguelin · 2013
Cited alongside, same era.
RAPPOR: randomized aggregatable privacy-preserving ordinal response
Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova · 2014
Cited alongside, same era.
Local, private, efficient protocols for succinct histograms
Raef Bassily and Adam D. Smith · 2015
Later among the works it cites.
Conservative or liberal? personalized differential privacy
Zach Jorgensen, Ting Yu, and Graham Cormode · 2015
Later among the works it cites.
How well sentence embeddings capture meaning
Lyndon White, Roberto Togneri, Wei Liu, and Mohammed Bennamoun · 2015
Later among the works it cites.
Privacy-preserving distributed collaborative filtering
Antoine Boutet, Davide Frey, Rachid Guerraoui, Arnaud Jégou, and Anne-Marie Kermarrec · 2016
Later among the works it cites.
Epicrec: Towards practical differentially private framework for personalized recommendation
Yilin Shen and Hongxia Jin · 2016
Later among the works it cites.
Differentially private user data perturbation with multi-level privacy controls
Yilin Shen, Rui Chen, and Hongxia Jin · 2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Preserving differential privacy for similarity measurement in smart environments
Kok-Seng Wong and Myung Ho Kim · 2014
Cited alongside, same era.
Deferentially private tagging recommendation based on topic model
Tianqing Zhu, Gang Li, Wanlei Zhou, Ping Xiong, and Cao Yuan · 2014
Cited alongside, same era.
A firm foundation for private data analysis
Cynthia Dwork
Cited in the paper.
Differential privacy
Cynthia Dwork
Cited in the paper.
Later among the works it cites.
Privacy-preserving topic model for tagging recommender systems
Tianqing Zhu, Gang Li, Wanlei Zhou, Ping Xiong, and Cao Yuan · 2016
Later among the works it cites.