Abstract:
An apparatus for identification of an input data against one or more learned signals is provided. The apparatus comprising a number of computational cores, each core comprises properties having at least some statistical independency from other of the computational, the properties being set independently of each other core, each core being able to independently produce an output indicating recognition of a previously learned signal, the apparatus being further configured to process the produced outputs from the number of computational cores and determining an identification of the input data based the produced outputs.
Abstract:
A method and server for analyzing a multimedia content item are provided. The method comprises receiving a multimedia content item; extracting from the multimedia content item a plurality of multimedia elements; generating at least one signature for each of the plurality of multimedia elements; for each of the plurality of multimedia elements, querying a deep-content-classification (DCC) system to identify at least one concept that matches one of the plurality of multimedia elements, wherein querying is performed using the at least one signature generated for the multimedia elements and wherein an unidentified multimedia content element does not have a matching concept; generating a context for the multimedia content item using matching concepts; and characterizing each unidentified multimedia element using the generating context and signatures of the matching concepts.
Abstract:
A method for reducing an amount of storage required for maintaining a large-scale collection of multimedia data elements by unsupervised clustering of multimedia data elements. The method comprises processing the multimedia data elements in the large-scale collection to generate a first cluster of multimedia data elements; storing the first cluster in a storage unit; repeating the generation of a new cluster from the first cluster and un-clustered multimedia elements in the large-scale collection until a single cluster is reached; and storing the new cluster generated at each iteration in the storage unit, wherein a N-th cluster generated at the N-th iteration is stored in the storage unit, wherein the amount of storage required to store the N-th cluster is less than an amount of storage of the large-scale collection, thereby the unsupervised clustering enables reducing the storage amount required to store the multimedia data elements in the large-scale collection.
Abstract:
A method and system for profiling interests of users based on multimedia content analysis and creating users' profiles respective thereof is provided. The method comprises receiving a tracking information gathered with respect to an interaction of a user with at least one multimedia element displayed on a user node; determining a user impression respective of at least one multimedia content element using the received tracking information; generating at least one signature for the at least one multimedia element; determining at least a concept of the at least one multimedia element using the at least one generated signature, wherein an interest of the user is determined respective of the concept; creating a user profile to include at least the user interest; and storing the user profile in a data warehouse.
Abstract:
A system and method for identification of inappropriate multimedia content elements are provided. The method includes receiving a request to identify a multimedia content element from a user device; generating at least one signature respective of the received multimedia content element; matching between the at least one of generated signature respective of the multimedia content element and at least one signature of each concept designated as inappropriate; determining whether a match is identified between the at least one of signature generated respective of the multimedia content element and the at least one signature of an inappropriate concept; and preventing the display on a user device of the multimedia content element, upon identification of a match.
Abstract:
A system and method for providing recommendations based on current user interests. The method includes identifying at least one current variable, wherein each current variable is associated with a user device or a user; determining, based on the identified at least one current variable, at least one current user interest of a user profile, the user profile including at least one contextual insight, wherein each contextual insight is based on at least one signature for at least one multimedia content element associated with the user; searching for at least one multimedia content element that matches the at least one current user interest; and causing a display of the at least one matching content item as a recommendation.
Abstract:
A system and method for generating personalized multimedia content element clusters. The method includes determining, based on at least one interest, at least one personalized concept, wherein each personalized concept represents one of the at least one user interest; obtaining at least one multimedia content element related to a user; generating at least one signature for the at least one multimedia content element, each generated signature representing at least a portion of the at least one multimedia content element; determining, based on the generated at least one signature, at least one multimedia content element cluster, wherein each cluster includes a plurality of multimedia content elements sharing a common concept of the at least one personalized concept; and creating at least one personalized multimedia content element cluster by adding, to each determined cluster, at least one of the at least one multimedia content element sharing the common concept of the cluster.
Abstract:
A method and system for generating concept structures and taxonomies based on received multimedia data elements (MMDEs) are provided. The method comprises receiving at least one MMDE; generating at least one signature for the at least one received MMDE; matching the at least one generated signature to a plurality of clusters to find at least one matching cluster; associating the at least one generated signature with each of the at least one matching cluster; and analyzing the at least one generated signature with respect to a signature reduced cluster (SRC) of each of the at least one matching cluster to generate a taxonomy, wherein the taxonomy relates to the at least one received MMDE and an MMDE respective of each of the at least one matching cluster.
Abstract:
A method and system for searching for mobile applications using a multimedia content element are provided. The system comprises receiving an input search query including the multimedia content element; generating at least one signature for the at least one multimedia content element; generating a textual query using at least the one generated signature; querying at least one application distribution platform using the generated textual search query; analyzing search results returned responsive to the textual query to determine relevancy of mobile applications designated in the search results to the multimedia content element; and causing the display of mobile applications on a user device submitting the input search query.
Abstract:
A system and method for determining a potential match candidate based on a social linking graph. The method includes: analyzing at least one multimedia content element (MMCE) to identify a first entity and a second entity in each MMCE, where the first entity is among a plurality of entities indicated by a social pattern associated with a third entity, wherein the first entity and the second entity in each MMCE are identified by generating at least one signature based on the MMCE and matching the generated at least one signature to signatures of a plurality of concepts, wherein each concept is a collection of signatures representing an entity and metadata describing the entity; and identifying the second entity as a potential match candidate for the third entity, wherein the second entity is not associated with the social pattern.