Abstract: Methods and systems are provided herein for collecting web browser click events across a plurality of web sites from a data collection agent (DCA), as a click-stream, at a data collection server (DCS) to record and provide user on-line activity, filtering the user online activity to include activity from a time period prior to a sale from the sales transaction data and identifying one or more shopping touch-points based on the filtered user online activity and the sales transaction data. Further, an engagement index, an influence index, and an opportunity index is calculated. A digital touch-points facility may perform the identifying and calculating.

Abstract: Methods and systems are provided herein for collecting web browser click events across a plurality of web sites from a data collection agent (DCA), as a click-stream, at a data collection server (DCS) to record and provide user on-line activity, filtering the user online activity to include activity from a time period prior to a sale from the sales transaction data and identifying one or more shopping touch-points based on the filtered user online activity and the sales transaction data. Further, an engagement index, an influence index, and an opportunity index is calculated. A digital touch-points facility may perform the identifying and calculating.

Abstract: A computer-implemented method for hotspot mitigation in object-based file systems may include 1) identifying a storage system including a plurality of storage devices, 2) identifying an object stored on a storage device within the plurality of storage devices, 3) identifying a level of demand to access the object, 4) creating, based at least in part on the level of demand, at least one sparse object to represent the object on at least one alternate storage device in the plurality of storage devices, and 5) fulfilling at least one read attempt to read from the object via the sparse object. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: This disclosure concerns a hybrid method for estimating Internet traffic including determining a fraction of a target population consisting of users displaying an identified characteristic by analysis of a census-based measurement of internet traffic for at least one website and receiving their clickstream data. The method also includes identifying a fraction of the group of participants that share the one or more characteristics, determining a behavioral composition by scaling the fraction of the group of participants by the fraction of the target population, and producing, at the host processing facility, an estimate of the target population's activity with respect to at least a part of the Internet that includes the at least one website by scaling the clickstream data for the subset of the group of participants by applying a weight based on the behavioral composition and the relative size of the target population.

Abstract: Methods and systems are provided herein for collecting web browser click events across a plurality of web sites from a data collection agent (DCA), as a click-stream, at a data collection server (DCS) to record and provide user on-line activity, filtering the user online activity to include activity from a time period prior to a sale from the sales transaction data and identifying one or more shopping touch-points based on the filtered user online activity and the sales transaction data. Further, an engagement index, an influence index, and an opportunity index is calculated. A digital touch-points facility may perform the identifying and calculating.

Abstract: A combined hash table/bucket trie technique facilitates fast, deterministic, memory-efficient exact match look-ups on extremely large tables. A limited number of hash keys which collide on the same location can be stored in the hash table. If further keys collide on the same location, a bucket trie is formed, the colliding keys are stored in the trie, and trie traversal information is stored in the hash table. Regardless of the number of buckets in the trie, an input key need only be compared with the keys in one bucket to detect a stored key identical to the input key or conclude that no stored key is identical to the input key.