Abstract: Embodiments of the present disclosure help content providers maximize the profitability of the online content they produce by providing an accurate, inexpensive, and timely quantitative estimate of the revenue the content is likely to generate. Various embodiments can refine estimates based on real-time or near-real-time data in conjunction with historical pricing data, thereby further improving the accuracy of the revenue predictions. A computer-implemented method according to one embodiment of the present disclosure comprises receiving, by a computer system, information regarding a topic; identifying, by the computer system, a format for content associated with the topic; and determining a score indicative of predicted revenue generated from future content in the identified format associated with the topic, wherein determining the score is based on a revenue model under which revenue from the future content would be generated.

Abstract: Embodiments of the present disclosure help content providers identify popular topics based on Internet search data, as well as to quantify the popularity of content addressing those topics. A computer-implemented method according to one embodiment of the present disclosure comprises receiving search data by a computer system; identifying a category related to at least a portion of the search data; determining, by the computer system and based on the search data, a topic for content associated with the identified category; and determining, by the computer system, a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data and on one or more formats for the content associated with the topic.

Abstract: Embodiments of the present disclosure help content providers identify popular topics based on Internet search data, as well as to quantify the popularity of content addressing those topics. A computer-implemented method according to one embodiment of the present disclosure comprises receiving search data by a computer system; identifying a category related to at least a portion of the search data; determining, by the computer system and based on the search data, a topic for content associated with the identified category; and determining, by the computer system, a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data and on one or more formats for the content associated with the topic.

Abstract: Embodiments of the present disclosure help content providers identify popular topics based on Internet search data, as well as to quantify the popularity of content addressing those topics. A computer-implemented method according to one embodiment of the present disclosure comprises receiving search data by a computer system; identifying a category related to at least a portion of the search data; determining, by the computer system and based on the search data, a topic for content associated with the identified category; and determining, by the computer system, a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data and on one or more formats for the content associated with the topic.

Abstract: Embodiments of the present disclosure help content providers maximize the profitability of the online content they produce by providing an accurate, inexpensive, and timely quantitative estimate of the revenue the content is likely to generate. Various embodiments can refine estimates based on real-time or near-real-time data in conjunction with historical pricing data, thereby further improving the accuracy of the revenue predictions. A computer-implemented method according to one embodiment of the present disclosure comprises receiving, by a computer system, information regarding a topic; identifying, by the computer system, a format for content associated with the topic; and determining a score indicative of predicted revenue generated from future content in the identified format associated with the topic, wherein determining the score is based on a revenue model under which revenue from the future content would be generated.

Abstract: Embodiments of the present disclosure help content providers identify popular topics based on Internet search data, as well as to quantify the popularity of content addressing those topics. A computer-implemented method according to one embodiment of the present disclosure comprises receiving search data by a computer system; identifying a category related to at least a portion of the search data; determining, by the computer system and based on the search data, a topic for content associated with the identified category; and determining, by the computer system, a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data and on one or more formats for the content associated with the topic.

Abstract: A system includes a communication network having any number of separately addressable elements. An analysis device can test packet data paths between these elements by eliciting particular traffic patterns. For example, the analysis device may elicit similar traffic patterns in both forward and reverse communications with a remote element and analyze these communications to detect network misconfigurations.

Abstract: Detecting anomalies includes receiving acceptable traffic from a network associated with a network party. The acceptable traffic is received at an anomaly detector associated with a monitoring party, where the anomaly detector is external to the network. The acceptable traffic is affected by an influencing interaction with anomalous traffic having anomalies. The influencing interaction yields an effect on the acceptable traffic, where the effect indicates the presence of the anomalies. Features of the acceptable traffic are monitored, where a monitored feature is operable to detect the effect. The anomalies are detected in response to the monitoring.

Abstract: Detecting anomalies includes receiving acceptable traffic affected by an influencing interaction with anomalous traffic having anomalies. The influencing interaction yields an effect on the acceptable traffic, where the effect indicates the presence of the anomalies. Features of the acceptable traffic are monitored, where a monitored feature is operable to detect the effect. The anomalies are detected in response to the monitoring.

Abstract: A method for detecting a network anomaly in a network includes collecting management information base (MIB) data from the network at an interval and constructing a time series of the collected data. The method also includes decomposing the time series of the collected data in the wavelet domain, constructing an energy plot based on the time series decomposed in the wavelet domain and analyzing the energy plot to determine a sign of a network anomaly event.

Abstract: A system includes a communication network having any number of separately addressable elements. An analysis device can test packet data paths between these elements by eliciting particular traffic patterns. For example, the analysis device may elicit similar traffic patterns in both forward and reverse communications with a remote element and analyze these communications to detect network misconfigurations.