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Because of the by-event state machine approach, events are bursted on independently of each other. This makes this algorithm suitable primarily when the changes in patterns of individual event usage are the area of interest. Cross-burst-levels comparisons of an event are possibleby possibly using the burst 'weight'. However, this algorithm only support batches records by year. In future, it will expended to month, date, hour; even number of year as desired based on user needs.

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Wiki Markup
Since we are focus on scholarly data, the data will be distributed into yearly batches before the burst computation started. Please see Kleinberg \[pg. 14\]. We also replace the missing years with empty batches to make the batches continuously by year. There will no burst for these empty batches. It is possible to add a scaling factor for the batches to month, day, hour; even number of years per batch. However, we need more evaluation on the implementation before it is available. This algorithm was re-implemented in Java based on the origin C implementation.

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Please read the Description section before continue. This burst algorithm is a text based burst detection that provide burst results in heirarchical hierarchical structure. However, it is also capable to detect if the bursts exist by setting the bursting states to 1.

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