International Business Machines Corporation

Tealeaf Technology, Inc.

Acoustic, L.p.

Robert I Wenig

Travis Spence Powell

Manoj Punjabi

Nadav Caspi

Wolf Herda

Kirk R Saathoff

Ashwin Singhania

Mikhail Borisovich Kozine

Albert F Gettier

John Dawes

Gerard Dietrich

John Berkley

Al Gettier

Paul Austin

Ted Knudsen

Geoff Townsend

Ted B Knudsen

A privacy processing system may use privacy rules to filter sensitive personal information from web session data. The privacy processing system may generate privacy profiles or privacy metadata that identifies how often the privacy rules are called, how often the privacy rules successfully complete actions, and the processing time required to execute the privacy rules. The privacy profiles may be used to detect irregularities in the privacy filtering process that may be associated with a variety of privacy filtering and web session problems.

Method and apparatus for generating privacy profiles

A monitoring system intelligently captures Document Object Model (DOM) events. The DOM events may provide state information that may not usually be captured during a web session. To reduce processing bandwidth, content identifiers may be used to represent some DOM events. Checkpoints may be identified during the web session and a current state of the webpage may be captured to provide replay synchronization. Different data may be captured based on a sequence and timing of the DOM events during the original web session. Data exchanged with third party websites also may be selectively captured to provide a more through simulation of the original web session.

Method and apparatus for intelligent capture of document object model events

A monitoring system captures the behavior of distributed applications and also provides a framework for augmenting functionality of the application in response to user interactions and different states of the application and network. Network events exchanged between an application and an application server are captured and the local client events on the client device are also selectively captured. The different disparate network events and client events are then combined together during a replay operation to simulate the user experience during the previous application session.

Dynamically configurable session agent

Web session events are captured during different web sessions. A segmentation model is generated based on a number of occurrences of the web session events for different time stamp periods. The segmentation model plots a segmentation graph that may identify differences between the web session events with respect to time factors. The segmentation model may use the whole dataset of event occurrences as an input without any preliminary data segmentation or discrimination. The model can associate the web session events with the different geographic locations, reveal possible reasons for customer experience difference for the users from different locations and provide statistically sound explanation of this difference. The model is scalable and may work with big data acquired by web-based commerce sites with wide international customer base.

Method and apparatus for customer experience segmentation based on a web session event variation

A user interface event monitor captures user interface events executed by a client during a network session. A network session monitor captures network data exchanged between the client and a web application during the network session. A replay device identifies control events in the network session that require execution before replaying associated user interface events. Replay of the user interface events are delayed by the replay device until the associated control events have been fully executed.

Replaying captured network interactions

A method of a server system communicating with a client system. The method includes a passive system monitoring network traffic between the client-server system. The server sending a page response including an agent, e.g., a Javascript that becomes operable on the client system. The agent monitors events on the client side, e.g., DOM events, and communicates these to the server side. A set of rules that define prescribed user events are maintained by the passive system and applied to the monitored network traffic to determine whether a prescribed user event occurred. Responsive to the prescribed user event occurring, an asynchronous message is generated and sent to the agent in response to a received DOM event message, the asynchronous message comprising a command to be executed by the agent to alter the users web application flow at the client in a manner that is substantially transparent to the web application.

Method and system for communication between a client system and a server system

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.

Automated analysis system for modeling online business behavior and detecting outliers

A test system uses an instrumented browser to identify events that were not successfully captured during a client web session. The identified events can be used to modify a capture system that captures the client web session. Alternatively, the test system may generate replay rules that are used by a replay system to infer the missed events while replaying of the previously captured client web session. The events can include changes to Document Object Models (DOMs) for web pages used during the web sessions. The DOMs can be used to identify significant web session events and force replay sessions into the correct states.

System identifying and inferring web session events

Network data associated with a network session is captured at a first location. The network data includes, but is not limited to, web page data transmitted over a network between a web server and a user terminal. User interface events associated with the same network session are separately captured at a second user terminal location. The user interface events include, but are not limited to, user inputs for interacting with the web page data. Both the captured network data and the separately captured user interface events are then used for analyzing the network session.

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San Francisco, CA, United States of America

Robert I Wenig