Kathy J. Liszka

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In this study, we apply data mining tools to generate interesting patterns for predicting box office performance of movies using data collected from multiple social media and web sources including Twitter, YouTube and the IMDb movie database. The prediction is based on decision factors derived from a historical movie database, followers count from Twitter,(More)
Real-time tasks for command and control systems are too large or too complex for one processor to handle. Simply adding more CPUs does not result in a linear increase in performance. Current comparative analysis of parallel algorithms does not accurately reflect the increased cost of scheduling when more processors are added. A case is made that associative(More)
With the growing popularity in using social media to collect data, there is an increasing need to discover ways in which to productively use this data. Our objective is to form an interest profile from tweets and use this to recommend loosely related Reddit threads which the reader is most likely to be interested in. The problem is approached as a genre(More)