Filtering Personal Queries from Mixed-Use Query Logs

Autor:	Philippe Desaulniers, Alexis Smirnov, Pablo Ariel Duboué, Ary Fagundes Bressane Neto
Rok vydání:	2014
Předmět:	Working hours Technical support Internal documentation Information retrieval Computer science Privacy policy Principle of maximum entropy InformationSystems_DATABASEMANAGEMENT Filter (signal processing) Private information retrieval Data mining algorithm
Zdroj:	Advances in Artificial Intelligence ISBN: 9783319064826 Canadian Conference on AI
DOI:	10.1007/978-3-319-06483-3_5
Popis:	Queries performed against the open Web during working hours reveal missing content in the internal documentation within an organization. Mining such queries is thus advantageous but it must strictly adhere to privacy policy and meet privacy expectations of the employees. Particularly, we need to filter queries related to non-work activities. We show that, in the case of technical support agents, 78.7% of personal queries can be filtered using a words-as-features Maximum Entropy approach, while losing only 9.3% of the business related queries. Further improvements can be expected when running a data mining algorithm on the queries and when filtering private information from its output.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7b0ae30fd0d1739321852240b6345c8a https://doi.org/10.1007/978-3-319-06483-3_5 Zobrazit plný text záznamu