Search Results - data mining

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  1. Combat groups like the Islamic State of Iraq and al-Sham (ISIS) have taken the lives of thousands as they attempt to gain control of more cities. In order to stop ISIS’s oppression and tyranny, it is necessary to determine their method of military operation. Therefore, there is a need to create a model that accurately depicts and simulates th...
    Published: 2/6/2017
    Keywords(s): Data Mining
  2. Analyzing data with high dimensionality, such as that generated by social media, requires complex algorithms. Feature selection reduces the dimensionality by selecting a subset of the most relevant features in high dimensional data. Feature selection methods can be broadly classi´Čüed into supervised methods for labeled data and unsupervised methods ...
    Published: 8/27/2016
  3. The explosive and viral nature of social media creates massive amounts of high-dimensional data. Features such as hashtags, keywords, or slang words are created every day and quickly become popular within a short period of time. However, social media data is not fully structured and its features are usually not predefined. One way to resolve this p...
    Published: 8/27/2016
    Keywords(s): Data Mining, Social Media
  4. Traditional indicators and warnings of cyber-incidents are created based on the results of an intrusion detection system, firewall, anti-virus software, or other related technologies. However, these systems are designed to detect cyber-incidents when an adversary is either conducting reconnaissance of a computer network or when the adversary has co...
    Published: 8/24/2016
  5. Social media services like Twitter have become a prominent source of research data for both academic and corporate applications because of the large amount of data available. Twitter allows researchers to obtain low-cost data samples, but past research has shown the data is not a random distribution and thus, is unrepresentative of the population. ...
    Published: 7/15/2016
  6. Big data analytics uncover hidden patterns, unknown correlations, and other practical information that can be applied to make more accurate predictions and decisions. Current techniques rely on statistics and decision-tree algorithms in order to “mine” useful information from massive data sets that are largely dominated by irrelevant da...
    Published: 12/22/2015
    Inventor(s): Werner Dahm

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