International Business Machines Corporation

Oracle America, Inc.

Coremetrics, Inc.

Hemanth Puttaswamy

Srinivasa Ogireddy

Charles McGonigal

Russell Salsbury

Mike Niemann

Saritha Guntumadugu

Hamid Bahadori

Sankara Rao Bhogi

Pankaj Jairath

Travis Woodruff

Nipun Batra

Steve Howard

Shalini Muthukrishnan

Recommendations for purchase are made based on customer behavior across multiple sessions. Correlations used for recommendations include: buy-to-buy (cross-session), view-to-view (same-session), view-to-buy (same-session), and abandon-to-buy (same-session) actions. A preview display allows a merchant to adjust recommendation algorithm weightings to achieve a desired result. A closed-loop system is provided with real-time feedback. The recommendations can be based on various segments of other users, including users of the same search engine.

Method and medium for determining whether a target item is related to a candidate affinity item

A system groups the data into sessions to allow tracking and evaluation of individual user behavior. By grouping clicks of a user in a session, the pattern of clicks can be observed, such as which path or pattern of clicks leads to a purchase. In particular, the session data is organized by session, using session transformers or 'sessionizers,' before it is provided for database storage, enabling real-time session based analytics.

Session based web usage reporter

A process for tracking a consumer's behavior based on his or her entries into a number of cybernetic device sources such as personal computers, automated goods and services dispensing kiosks, automated teller machines and cell phones does not depend exclusively upon the presence of cookies implanted into such devices by vendors or upon a consumer's having provided a positive identification form. The process uses a pairing algorithm to comb elements of information from the source device visitation records in search of one or more common characteristics that can be presumptively attributed to a single consumer. Characteristics such as source device identifiers, phone numbers, street addresses or email addresses are each weighted by a weighting factor that is used to identify the consumer and attribute the visitation record and its associated activity to that consumer at a calculated confidence level. The attributed information can analyzed to track that consumer's behavior.

Multi-source consumer behavior tracking system

A system receives a management configuration set defining at least one event to be detected in the application server, and a respective associated action to be taken upon detection of the events. For each of the events to be detected in the application server, the system instantiates an event class to detect the event. For each of the actions to be taken upon detection of the event by the event class, the system instantiates a respective action class to perform that action on behalf of the event class that detects the event. The system operates the instantiated event classes to detect events and to send an event notification to each of the respective action class associated with that event.

Methods and apparatus for remote management and self management of servers

A system that improves the real time presentation of web analytics data to clients. Real time data is improved in one embodiment by using a messaging system that directs the data stream to RAM memory, before it is sent to the database. A separate path is provided for presenting the real time data, which does not require going through the main database. The data is serialized and streamed in batches at an interval which can be set from the order of seconds to minutes. Additionally, the data is aggregated in RAM according to the desired groupings of data, so that the aggregation is pre-computed.

Real time web usage reporter using RAM

Method, medium, and system for determining whether a target item is related to a candidate affinity item

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Fremont, CA, United States of America

Hemanth Puttaswamy