Automated analysis system for modeling online business behavior and detecting outliers
DCFirst Claim
1. A method, comprising:
- identify, by a processing device, events for web sessions, wherein the events comprise network data including webpages, requests, and/or responses sent over a network between a web server and user devices during the web sessions; and
user inputs entered at user devices for interacting with the webpages;
generating, by the processing device, a model from the events;
identifying, by the processing device, outliers against the model; and
generating, by the processing device, reports identifying the events based on a significance of the events to the outliers.
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Abstract
A two-module system is created for automated web activity monitoring. A model is generated and model outliers are identified by the first module of the system. Reports are generated that identify the events based on their significance to the outliers. The model may be automatically and periodically regenerated for different historical time periods of the web sessions. New groups of events may be periodically extracted from new web sessions and applied to the previously generated model by the second module of the system. Model outliers may be identified from the new groups of events. The new events may be analyzed and reported to a web session operator based on their contribution to any identified outliers. Even if no outliers are detected, the new events having a most significant impact on web session operating conditions may be identified and reported in real-time.
25 Citations
21 Claims
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1. A method, comprising:
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identify, by a processing device, events for web sessions, wherein the events comprise network data including webpages, requests, and/or responses sent over a network between a web server and user devices during the web sessions; and
user inputs entered at user devices for interacting with the webpages;generating, by the processing device, a model from the events; identifying, by the processing device, outliers against the model; and generating, by the processing device, reports identifying the events based on a significance of the events to the outliers. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. An apparatus, comprising:
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a monitoring system configured to; capture network data for the web sessions, wherein the network data comprises webpages, requests, and/or responses sent over a network between a web server and user devices during the web sessions; and capture user interface events for the web sessions, wherein the user interface events comprise user inputs entered at the user devices for interacting with the webpages; a memory configured to archive web session events for web sessions, wherein the web session events include the network data and the user interface events; and logic circuitry configured to; extract the web session events from the memory; generate a model for the web sessions from the web session events; and identify how the web session events impact the web sessions based on the model for the web sessions. - View Dependent Claims (13, 14, 15)
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16. A method, comprising:
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receiving network events for a network session from a network monitor, the network events including webpage data transmitted over a network between a web server and a user device during the network session; sending the network events to a session archive; receiving user interface events associated with the network session and entered from the user device, the user interface events including user inputs for interacting with the webpage data; sending the user interface events to the session archive; generating a model for the network session from the network events and the user interface events in the session archive; and using the model to identify how the network events and user interface events impact operation of the network session. - View Dependent Claims (17, 18, 19, 20, 21)
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Specification