Techniques for determining relevant electronic content in response to queries is disclosed. According to an exemplary embodiment of the present disclosure, the techniques may be realized as a computer implemented method for determining relevant electronic content in response to a query. The method may comprise: receiving a query from a user device; categorizing the query to identify one or more relevant electronic content sources; formatting the query according to one or more electronic content source specifics for the one or more electronic content sources; transmitting the formatted query to the one or more electronic content sources; merging results in response to the formatted query to the one or more electronic content sources; merging results based at least in part on one or more factors; and formatting the results for delivering to the user device.

A video decoder chipset (200, 300, 400, 500) comprises a video decoder function (210), an upscaler function (230) and a combiner function (240). The video decoder function (210) is configured to (i) decode encoded video data to generate decoded video data at a first level of quality, the encoded video data having been derived by an encoder using first video data at a second, higher level of quality and (ii) output the decoded video data for storage in a memory (220). The upscaler function (230) is configured to (i) obtain the decoded video data from the memory (220) and (ii) upscale the obtained decoded video data to generate second video data at the second level of quality. The combiner function (240) is configured to (i) obtain residual data, the residual data having been derived by the encoder based on the first video data and the second video data, (ii) combine the second video data with the residual data to generate enhanced video data, and (iii) output the enhanced video data.

A video decoder chipset (200, 300, 400, 500) comprises a video decoder function (210), an upscaler function (230) and a combiner function (240). The video decoder function (210) is configured to (i) decode encoded video data to generate decoded video data at a first level of quality, the encoded video data having been derived by an encoder using first video data at a second, higher level of quality and (ii) output the decoded video data for storage in a memory (220). The upscaler function (230) is configured to (i) obtain the decoded video data from the memory (220) and (ii) upscale the obtained decoded video data to generate second video data at the second level of quality. The combiner function (240) is configured to (i) obtain residual data, the residual data having been derived by the encoder based on the first video data and the second video data, (ii) combine the second video data with the residual data to generate enhanced video data, and (iii) output the enhanced video data.

Memristive computation of a cross product is disclosed. One example is a crossbar array of memory elements that include a number of column lines perpendicular to a number of row lines, a memory element located at each intersection of a row line and a column line. A programming voltage is applied at each memory element to change a resistance value to represent a respective entry in a skew symmetric matrix representing a first vector, and an input voltage is applied along each row line to represent a dimensional component of a second vector. Sensors located at each column line measure output voltages along column lines, where the output voltages are generated by applying input voltages received by memory elements located along the row line to resistance values of the respective memory elements. Differential amplifiers collate the output voltages for pairs of sensors to generate dimensional components of the cross product.

Some embodiments of the present invention include a method for identifying duplicate records from a group of records in a database system. The method includes generating a cluster of records from a group of records based on one or more keys; splitting the cluster of records into multiple subsets of records with each subset of records having fewer number of records than the cluster of records, wherein the splitting the cluster of records into multiple subsets of records is based on a number of records in the cluster of records exceeding a threshold; causing duplicate sets of records in each of the subsets of records to be identified, wherein a duplicate set of records includes one or more records, and wherein when a duplicate set of records includes two or more records, the two or more records are duplicates of one another; merging all of the duplicate sets of records identified from the multiple subsets of records forming a first group of duplicate sets of records; and forming a representative set of records based on selecting a representative record from each of the duplicate sets in the first group of duplicate sets of records.

Some embodiments of the present invention include a method for identifying duplicate records from a group of records in a database system. The method includes generating a cluster of records from a group of records based on one or more keys; splitting the cluster of records into multiple subsets of records with each subset of records having fewer number of records than the cluster of records, wherein the splitting the cluster of records into multiple subsets of records is based on a number of records in the cluster of records exceeding a threshold; causing duplicate sets of records in each of the subsets of records to be identified, wherein a duplicate set of records includes one or more records, and wherein when a duplicate set of records includes two or more records, the two or more records are duplicates of one another; merging all of the duplicate sets of records identified from the multiple subsets of records forming a first group of duplicate sets of records; and forming a representative set of records based on selecting a representative record from each of the duplicate sets in the first group of duplicate sets of records.

Some embodiments of the present invention include a system and method for removing duplicate records from a group of records in a database system. The method includes generating a first cluster of records from the group of records, generating a second cluster of records from the group of records, identifying sets of duplicate records in the first cluster of records, and identifying sets of duplicate records in the second cluster of records. The method also includes merging at least two sets of duplicate records associated with both the first cluster and the second cluster of records to form a merged set of duplicate records. The merging is performed based on the at least two sets of duplicate records having a common record. Duplicate records in the group of records may then be removed by removing duplicate records from the merged set of duplicate records.

Techniques are described for managing cookies, including separately managing cookie data associated with different browser tabs. Cookie management includes the isolation of whitelisted cookies from server responses into background storage and then back onto server requests, removing those cookies from the response header and thus from the cookie store. This isolation is managed with the concept of tab ownership between parent and child tabs to maintain isolation separately for each owner (e.g., the parent) and its children. Exposure to client pages is handled by placing those cookies into a keyed location in session storage for every tab where that cookie is to be visible. An event is then triggered for that client page to let it know that session storage has been updated.

A first user request which specifies a target document set wherein a first subset of the documents is flagged by a user. A primary flag table is created for the target document set. A first document subset is created matching the first user request. It is determined whether a number of flagged documents exceeds a first threshold. If so, a secondary flag table is created for the first document subset and flag data corresponding to the first document subset is stored in the secondary flag table. The flag data in the secondary flag table is merged into the primary flag table.

Systems and methods for discovering and/or determining section types for a given document class in a data-driven manner are provided. A modified Bayesian model merging algorithm can be used, along with extending an Analogical Story Merging (ASM) algorithm. The systems and methods can learn the section structure of documents without a pre-existing ontology of sections or time-intensive annotation efforts.