Mining Closed Regular Patterns in Data Streams
نویسندگان
چکیده
منابع مشابه
Incremental Mining of Closed Sequential Patterns in Multiple Data Streams
Sequential pattern mining searches for the relative sequence of events, allowing users to make predictions on discovered sequential patterns. Due to drastically advanced information technology over recent years, data have rapidly changed, growth in data amount has exploded and real-time demand is increasing, leading to the data stream environment. Data in this environment cannot be fully stored...
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Todays, in many modern applications, we search for frequent and repeating patterns in the analyzed data sets. In this search, we look for patterns that frequently appear in data set and mark them as frequent patterns to enable users to make decisions based on these discoveries. Most algorithms presented in the context of data stream mining and frequent pattern detection, work either on uncertai...
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Discovery of complex patterns such as clusters, outliers, and associations from huge volumes of streaming data has been recognized as critical for many application domains. However, little research effort has been made toward detecting patterns within sliding window semantics as required by real-time monitoring tasks, ranging from real time traffic to every window is impractical due to their hi...
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Sequential pattern mining is an active field in the domain of knowledge discovery and has been widely studied for over a decade by data mining researchers. More and more, with the constant progress in hardware and software technologies, real-world applications like network monitoring systems or sensor grids generate huge amount of streaming data. This new data model, seen as a potentially infin...
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There are extensive endeavors toward mining frequent items or itemsets in a single data stream, but rare efforts have been made to explore sequential patterns among literals in different data streams. In this paper, we define a challenging problem of mining frequent sequential patterns across multiple data streams. We propose an efficient algorithm MILE to manage the mining process. The propose...
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ژورنال
عنوان ژورنال: International Journal of Computer Science and Information Technology
سال: 2013
ISSN: 0975-4660,0975-3826
DOI: 10.5121/ijcsit.2013.5114