Abstract: Character-based n-grams are derived from a domain name in order to classify such domain name in pre-established categories. Domain name character-based n-grams are mapped to vector points in a multidimensional space, where the number of dimensions is the number of different n-grams that can exist for an n-character combination. The relationship between the domain name vector point and the vector points of the various other domain names is used to classify the domain name vector point. The classification system can use statistical methods using relative frequencies of character-based n-grams in various classifications as indicators. A dictionary set of character-based n-grams can be derived from one or more domain names and associated with probability indicating the likelihood that the character-based n-gram is found in a domain name of a given classification. Such probability can be an estimator of a classification of a new domain name having such character-based n-gram.

Abstract: Systems and methods of classifying domain names are disclosed. Character-based n-grams are derived from a domain name in order to classify such domain name in one or more categories. In one aspect, a geometrical approach is used. Domain name character-based n-grams are mapped to vector points in a multidimensional space. The relationship between a domain name vector point and vector points of other domain names is used as an indicator of the classification of the domain name vector point. In another aspect, a statistical approach is used. Relative frequencies of one or more character-based n-grams in various classifications are used as indicators. Each character-based n-gram can be associated with a respective probability that indicates a likelihood that the character-based n-gram is found in a domain name of a given classification. Such a probability can serve as an estimator of a classification of a new domain name having such character-based n-gram.

Abstract: Systems and methods of classifying domain names are disclosed herein. Character-based n-grams are derived from a domain name in order to classify such domain name in one or more pre-established categories. In one aspect, a geometrical approach is used. Domain name character-based n-grams are mapped to vector points in a multidimensional space. In addition, vector points for various other domain names, which belong to a domain name classification, can be mapped multidimensional space. The number of dimensions in the multidimensional space is the number of different n-grams that can exist for an n-character combination. The relationship between the domain name vector point and the vector points of the various other domain names is used as an indicator of the classification of the domain name vector point. In another aspect, the classification system can be configured to utilize statistical methods. Relative frequencies of one or more character-based n-grams in various classifications are used as indicators.

Abstract: Systems and methods of classifying domain names are disclosed herein. Character-based n-grams are derived from a domain name in order to classify such domain name in one or more pre-established categories. In one aspect, a geometrical approach is used. Domain name character-based n-grams are mapped to vector points in a multidimensional space. In addition, vector points for various other domain names, which belong to a domain name classification, can be mapped multidimensional space. The number of dimensions in the multidimensional space is the number of different n-grams that can exist for an n-character combination. The relationship between the domain name vector point and the vector points of the various other domain names is used as an indicator of the classification of the domain name vector point. In another aspect, the classification system can be configured to utilize statistical methods. Relative frequencies of one or more character-based n-grams in various classifications are used as indicators.