Abstract: Systems and methods for defining a custom segment in a set of behavioral data are provided. A described method includes receiving a set of behavioral data associated with a plurality of user devices and identifying multiple cohort groups, each of the cohort groups including one or more of the user devices. The behavioral data includes a behavior metric for each of the user devices and the cohort groups are identified based on the behavior metric for each of the user devices. The method further comprises generating a segmentation interface including a graphical visualization of the multiple cohort groups and causing the segmentation interface to be presented via a user interface device. The method further comprises defining a custom segment of the behavioral data based on a user selection of one or more of the multiple cohort groups via the segmentation interface.

Abstract: Systems and methods for defining a custom segment in a set of behavioral data are provided. A described method includes receiving a set of behavioral data associated with a plurality of user devices and identifying multiple cohort groups, each of the cohort groups including one or more of the user devices. The behavioral data includes a behavior metric for each of the user devices and the cohort groups are identified based on the behavior metric for each of the user devices. The method further comprises generating a segmentation interface including a graphical visualization of the multiple cohort groups and causing the segmentation interface to be presented via a user interface device. The method further comprises defining a custom segment of the behavioral data based on a user selection of one or more of the multiple cohort groups via the segmentation interface.

Abstract: A method and system for cleansing anomalies from sequence-based data at query time. Sequence-based data such as RFID data is loaded into a database. One or more cleansing rules are received at a cleansing rules engine. The cleansing rule engine converts the cleansing rule(s) to a template that includes logic to compensate for anomalies in the sequence-based data. A query to retrieve the sequence-based data is received by a query rewrite engine. The query rewrite engine rewrites the query by applying the template logic. The rewritten query is executed at query time. The result of the rewritten query execution is identical to the result of executing the original query on a data set generated by applying the cleansing rule to all of the sequence-based data.

Abstract: A method for cleansing anomalies from sequence-based data at query time. Sequence-based data such as RFID data is loaded into a database. A cleansing rule is received at a cleansing rules engine. The cleansing rule engine converts the cleansing rule to a template that includes logic to compensate for anomalies in the sequence-based data. A query to retrieve the sequence-based data is received by a query rewrite engine. The query rewrite engine rewrites the query by applying the template logic and an expanded rewrite technique. The rewritten query is executed at query time. The result of the rewritten query execution is identical to the result of executing the original query on a data set generated by applying the cleansing rule to all of the sequence-based data.

Abstract: A method and system for cleansing anomalies from sequence-based data at query time. Sequence-based data such as RFID data is loaded into a database. One or more cleansing rules are received at a cleansing rules engine. The cleansing rule engine converts the cleansing rule(s) to a template that includes logic to compensate for anomalies in the sequence-based data. A query to retrieve the sequence-based data is received by a query rewrite engine. The query rewrite engine rewrites the query by applying the template logic. The rewritten query is executed at query time. The result of the rewritten query execution is identical to the result of executing the original query on a data set generated by applying the cleansing rule to all of the sequence-based data.

Abstract: A method and system for cleansing anomalies from sequence-based data at query time. Sequence-based data such as RFID data is loaded into a database. One or more cleansing rules are received at a cleansing rules engine. The cleansing rule engine converts the cleansing rule(s) to a template that includes logic to compensate for anomalies in the sequence-based data. A query to retrieve the sequence-based data is received by a query rewrite engine. The query rewrite engine rewrites the query by applying the template logic. The rewritten query is executed at query time. The result of the rewritten query execution is identical to the result of executing the original query on a data set generated by applying the cleansing rule to all of the sequence-based data.