State-of-the-art important passage retrieval methods obtain very good results, but do not take into account privacy issues. In this paper, we present a privacy preserving method that relies on creating secure representations of documents. Our approach allows for third parties to retrieve important passages from documents without learning anything regarding their content. We use a hashing scheme known as Secure Binary Embeddings to convert a key phrase and bag-of-words representation to bit strings in a way that allows the computation of approximate distances, instead of exact ones. Experiments show that our secure system yield similar results to its non-private counterpart on both clean text and noisy speech recognized text.
@article{arxiv.1407.5416,
title = {Privacy-Preserving Important Passage Retrieval},
author = {Luis Marujo and José Portêlo and David Martins de Matos and João P. Neto and Anatole Gershman and Jaime Carbonell and Isabel Trancoso and Bhiksha Raj},
journal= {arXiv preprint arXiv:1407.5416},
year = {2016}
}
Comments
Secure Passage Retrieval, Important Passage Retrieval, KP-Centrality, Secure Binary Embeddings, Data Privacy, Automatic Key Phrase Extraction, Proceedings of SIGIR 2014 Workshop Privacy-Preserving IR: When Information Retrieval Meets Privacy and Security