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Obtaining accurate models of systems which are prone to failures and breakdowns is a difficult task. In this paper we present a methodology which makes the task of modeling failure prone discrete event systems (DESs) considerably less cumbersome, less error prone, and more user-friendly. The task of obtaining commonly used au-tomata models for DESs is(More)
This paper introduces and analyzes a new approach to query suggestion. After the user issues a query q_0, for every document retrieved in a certain rank range [Theta_1,Theta_2], a query search procedure constructs queries that rank the document high enough for the user to see it. From this set of queries the suggestions to be presented to the user are then(More)
This paper proposes an empirical approach for analyzing the rank distribution of relevant documents in web search. From a methodological point of view a new transaction log analysis method is proposed; the relevance of documents is studied over transaction sessions rather than single transactions. From a practical point of view the paper provides insights(More)
As costs in equipment maintenance have been more and more expensive, equipment maintenance management is of great importance in equipment management in recent years. Firstly, cost of the equipment predictive maintenance model is proposed, which fully utilizes the big data technology. Particularly, the best maintenance cycle and maintenance times can be(More)
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