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This work proposes a method to improve the QoS provided to internet users by website servers. In particular, the goal is to minimize the expected number of browsing steps (clicks), also known as the expected path length, which are required to reach a website page by a community of users. We use Markov chain modeling to represent the transition probabilities from one webpage to another, and the first passage from page to page that can be retrieved from web server logs. The proposed method deletes links among webpages to minimize the expected path length of the website. Three different methods for achieving this goal are examined: (i) a greedy deletion heuristic; (ii) an approximated branch and bound algorithm; and (iii) a cross-entropy metaheuristic. Numerical studies show that the proposed greedy heuristic results in the optimal solution in more than 60% of the tested cases, while in almost 90% of the cases, the obtained solution is within 10% of the optimal solution. Both the approximated branch and bound and the cross-entropy methods achieved optimality in more than 80% of the tested cases; however, this came with a much higher computational cost. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In recent years, with the emergence of big data and online Internet applications, the ability to classify huge amounts of objects in a short time has become extremely important. Such a challenge can be achieved by constructing decision trees (DTs) with a low expected number of tests (ENT). We address this challenge by proposing the 'save favorable general optimal testing algorithm' (SF-GOTA) that guarantees, unlike conventional look-ahead DT algorithms, the construction of DTs with monotonic non-increasing ENT. The proposed algorithm has a lower complexity in comparison to conventional look-ahead algorithms. It can utilize parallel processing to reduce the execution time when needed. Several numerical studies exemplify how the proposed SF-GOTA generates efficient DTs faster than standard look-ahead algorithms, while converging to a DT with a minimum ENT. [ABSTRACT FROM AUTHOR]