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Unmanned Aerial Vehicles (UAVs) are increasingly popular. As a result of the tremendous number of UAVs, especially recreational UAVs, regulation becomes a challenge we are confronted with. Protocol reverse engineering offers a way to understand and regulate the drones effectively. Extracting keywords is an
. Especially as a part of the interest router table, each K-bucket stores a certain number of the peers' information that have high interest similarity. The query can be executed in the appropriate k-bucket by calculating interest similarity and interest keyword. Through mining the latent interest, we found that two peers having
genuinely important logs that lead to serious problems due to the large volume and complexity of log data. We propose a log analysis system for proactive detection of failures. Our key observation is that the abnormality of logs depends on not just the keywords in the messages (e.g. ERROR, FAIL), but generation patterns such
system, classification of keywords by higher ranking of topics has contributed to an active role for the extraction of summarization, the results of summarization ratio in social web is 40%-50%.
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