This paper studies the problem of categorical data clustering,
especially for transactional data characterized by high
dimensionality and large volume. Starting from a heuristic method
of increasing the height-to-width ratio of the cluster histogram, we
develop a novel algorithm – CLOPE, which is very fast and
scalable, while being quite effective. We demonstrate the
performance of our algorithm on two real world
文本計算器是一款為經常需要使用計算器的工程項目人士而設計的軟件，該軟件使用簡單、方便。
當需要計算數據時，在窗口中輸入整個表達式（表達式可以是加+、減-、乘*、除/、平方^、括號()，以及數學函數組合），按回車后可自動計算出結果，計算方法一目了然，便于查找計算中可能出現的錯誤。
支持的數學函數：cos(), sin(), tg(), ctg(), abs(), sgn() or sign(), sqrt(), ln(),sh() or sinh(), ch() or cosh(), th() or tanh(),cth() or coth(), heaviside()
Extensively revised for the latest Java (J2SE 5.0) release Deitel Java How to Program, 6/e now includes earlier coverage of objects new and streamlined case studies and OPTIONAL GUI and graphics sections. Now available in a briefer version (ch. 1-10) called Small Java. SafariX version available.
