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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Lucene-P2: A Distributed Platform for Privacy-Preserving Text-based Search
Nitish Uplavikar1, Brad Malin2, Wei Jiang1
1Department of Electrical Engineering and Computer Science at University of Missouri-Columbia.
Abstract:
Information retrieval (IR) plays an essential role in daily life. However, currently deployed IR technologies, e.g., Apache Lucene - open-source search software, are insufficient when the information is protected or deemed to be private. For example, submitting a query to a publicly available search engine (e.g., Bing or Google) requires disclosing potentially delicate facts (e.g., thoughts about abortion), as well as the websites the user considers interesting. Similarly, when a private database contains sensitive information needed by the user, it cannot be searched freely. Over the past decade, various approaches, generally referred to as private information retrieval, have been proposed to obfuscate queries and responses, but they are limited in that the retrieved information is inadequate to compute relevancy. To address such limitations, this paper introduces the necessary techniques to build Lucene-P2 that allows one party to discover whether a second party harbors any relevant textual information without either party disclosing any information.
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