METHOD AND SYSTEM TO DETECT AND INTERRUPT A ROBOT DATA AGGREGATOR ABILITY TO ACCESS A WEBSITE
First Claim
1. A computer-based method to detect and block a robot data aggregator from accessing a website, the method comprising:
- analyzing business operations and session data associated with using a website, the session data being collected from a session history log of user sessions, including human user sessions and robot user sessions, that use the business operations while accessing and/or navigating the website;
defining, based on the analyzing, a set of important features of the collected session data from the user sessions, a feature value for each feature in the set of important features being extractable from each user session;
extracting a feature value for each feature in the set of important features from the session data collected from each user session;
classifying the session data collected from each user session as being with a human user or a robot user; and
generating training user session data, the training user session data comprising;
collected session data from each user session in the session history log;
extracted feature values from the collected session data from each user session; and
a classifier flag value indicating that the extracted feature values are from a user session with a human user or a robot user.
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Abstract
An information processing system, a computer readable storage medium, and a method to detect and block a robot data aggregator from accessing a website. A method includes defining a set of important features of business operations associated with users using a website. A feature value for each important feature is extracted from collected session data of a user session using the website. A user classifier classifies the user session as being with a human user or a robot user. Based on the classifying, access to the website by a robot user is blocked. Training user session data is also generated from the collected user session data thereby the user classifier learns and improves accuracy and reliability in detecting the type of user in a user session.
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Citations
19 Claims
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1. A computer-based method to detect and block a robot data aggregator from accessing a website, the method comprising:
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analyzing business operations and session data associated with using a website, the session data being collected from a session history log of user sessions, including human user sessions and robot user sessions, that use the business operations while accessing and/or navigating the website; defining, based on the analyzing, a set of important features of the collected session data from the user sessions, a feature value for each feature in the set of important features being extractable from each user session; extracting a feature value for each feature in the set of important features from the session data collected from each user session; classifying the session data collected from each user session as being with a human user or a robot user; and generating training user session data, the training user session data comprising; collected session data from each user session in the session history log; extracted feature values from the collected session data from each user session; and a classifier flag value indicating that the extracted feature values are from a user session with a human user or a robot user. - View Dependent Claims (2, 3, 4, 5)
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6. A method, with an information processing system, to detect and block a robot data aggregator from accessing a website, the method comprising:
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defining a set of important features of business operations and session data associated with using a website, the session data being collected from user sessions, including human user sessions and robot user sessions, that use the business operations while accessing and/or navigating the website, a feature value for each feature in the set of important features being extractable from each user session; monitoring user sessions that use the business operations while accessing and/or navigating the website, and collecting user session data from each user session; extracting a feature value for each feature in the set of important features from the session data collected from a user session; classifying with a user classifier the session data collected from each user session as being with a human user or a robot user, the user classifier comprising a model of behaviors of important business operations using the website based on training user session data that is stored in a training user session data repository in a memory, the model including a set of decision rules that the user classifier follows to determine a type of user of a user session as either a human user or a robot user; blocking, based on the classifying, access to the website by a robot user that has been determined from the collected user session data to have accessed and/or navigated business operations while using the website; and generating, based on the classifying, training user session data from the collected user session data, the training user session data comprising; collected session data from the user session; extracted feature values from the collected session data; and a classifier flag value, assigned to the extracted feature values by the user classifier, indicating that the extracted feature values are from a user session with a human user or a robot user. - View Dependent Claims (7, 8, 9, 10)
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11. A website information processing system comprising:
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memory; a network interface for interfacing the website information processing system with one or more web communication networks; a web server for providing business operations to users of a website while accessing and/or navigating the website during user sessions; a user classifier for classifying users of the website as either human users or robot users; and a processor, communicatively coupled with the memory, the network interface, the web server, and the user classifier, the processor, responsive to computer instructions, performing a method to detect and block a robot data aggregator from accessing the website, the method comprising; defining a set of important features of business operations and session data associated with using the website, the session data being collected from user sessions, including human user sessions and robot user sessions, that use the business operations while accessing and/or navigating the website, a feature value for each feature in the set of important features being extractable from each user session; monitoring user sessions that use the business operations while accessing and/or navigating the website, and collecting user session data from each user session; extracting a feature value for each feature in the set of important features from the session data collected from a user session; classifying with the user classifier the session data collected from each user session as being with a human user or a robot user, the user classifier comprising a model of behaviors of important business operations using the website based on training user session data that is stored in a training user session data repository in the memory, the model including a set of decision rules that the user classifier follows to determine a type of user of a user session as either a human user or a robot user; blocking, based on the classifying, access to the website by a robot user that has been determined from the collected user session data to have accessed and/or navigated business operations while using the website; and generating, based on the classifying, training user session data from the collected user session data, the training user session data comprising; collected session data from the user session; extracted feature values from the collected session data; and a classifier flag value, assigned to the extracted feature values by the user classifier, indicating that the extracted feature values are from a user session with a human user or a robot user. - View Dependent Claims (12, 13, 14, 15)
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16. A computer readable storage medium, comprising computer instructions which, responsive to being executed by a processor, cause the processor to perform operations to detect and block a robot data aggregator from accessing a website, the operations comprising:
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defining a set of important features of business operations and session data associated with using a website, the session data being collected from user sessions, including human user sessions and robot user sessions, that use the business operations while accessing and/or navigating the website, a feature value for each feature in the set of important features being extractable from each user session; monitoring user sessions that use the business operations while accessing and/or navigating the website, and collecting user session data from each user session; extracting a feature value for each feature in the set of important features from the session data collected from a user session; classifying with a user classifier the session data collected from each user session as being with a human user or a robot user, the user classifier comprising a model of behaviors of important business operations using the website based on training user session data that is stored in a training user session data repository in a memory, the model including a set of decision rules that the user classifier follows to determine a type of user of a user session as either a human user or a robot user; blocking, based on the classifying, access to the website by a robot user that has been determined from the collected user session data to have accessed and/or navigated business operations while using the website; and generating, based on the classifying, training user session data from the collected user session data, the training user session data comprising; collected session data from the user session; extracted feature values from the collected session data; and a classifier flag value, assigned to the extracted feature values by the user classifier, indicating that the extracted feature values are from a user session with a human user or a robot user. - View Dependent Claims (17, 18, 19)
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Specification