Mining Locally Trending High Utility Itemsets

On the two datasets, some patterns having a strong trend were found, which means that the utility of these itemsets was high and increased rapidly in their THUPs.

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sepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(W_{[k,l]}) = winlen, u(X, W_{[k,l]}) \ge minutil, slope(X, W_{[k,l]}) \ge minslope$$\end{document} , indicating an increasing trend (or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$slope(X, W_{[k,l]}) \le maxslope$$\end{document} , indicating a decreasing trend).

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umentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$slope(X, W_{[k,l]}) \le maxslope$$\end{document} , indicating a decreasing trend).

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