Abstract: According to some embodiments of the present invention there is provided a computerized method for labeling a cluster of text documents. The method comprises receiving a document cluster and producing automatically multiple document sub-clusters determined by randomly changing some documents. The method applies multiple cluster labeling algorithms on the cluster and on each sub-cluster, to generate ordered lists. The method comprises generating a ranked label list for each cluster labeling algorithm by computing automatically label values, one for each cluster label in the lists of the selected algorithm, and re-ranking the ordered list. The method combines the re-ranked label lists using a label fusing algorithm to produce a fused label list.

Abstract: Personalized tag ranking of images, including identifying within a reference image collection any images that are similar to an input image, identifying within a source image collection any images that have associated tags that are similar to a set of input tags associated with the input image, identifying among the images identified in the reference image collection any images that are similar to the images identified in the source image collection, and calculating a weight for each of a plurality of tag pairs, where each of the tags in each of the tag pairs is associated with a different subset of the images in the reference image collection identified as being similar to the images identified in the source image collection, and ranking the input tags of the input image in accordance with a predefined ranking function as applied to the tag pair weights.

Abstract: Personalized tag ranking of images, including identifying within a reference image collection any images that are similar to an input image, identifying within a source image collection any images that have associated tags that are similar to a set of input tags associated with the input image, identifying among the images identified in the reference image collection any images that are similar to the images identified in the source image collection, and calculating a weight for each of a plurality of tag pairs, where each of the tags in each of the tag pairs is associated with a different subset of the images in the reference image collection identified as being similar to the images identified in the source image collection, and ranking the input tags of the input image in accordance with a predefined ranking function as applied to the tag pair weights.

Abstract: Method, system, and computer program product are provided for sentiment estimation of a web browsing user. The method includes: estimating for pages of a website a sentiment based on background content; receiving a path of pages browsed by a user to a current page; and estimating the user's sentiment to a current page based on the path taken to the current page and the sentiments based on the background content of the visited pages. The method may also include dynamically changing website content provided to the user based on the user's estimated sentiment to a current page.

Abstract: A method and system for prioritising operations on network objects are provided. The method includes gathering Web 2.0 available relationship data on the relationships between network entities, wherein network entities are network users and network objects. The relationship data for a network entity is analysed and a first relative score is determined based on the relationship data. For a network object, a second relative score is determined which is a dynamic score based on user interactions with the network object and formed using the first relative scores of network entities interacting with the object. The method then prioritizes an operation on a network object using the second relative score.

Abstract: A method, system, and computer program product for dynamic generation of products for online recommendation.

Abstract: A device and method for processing information fragments, the method includes: receiving multiple information fragments from multiple communication paths; wherein the each information fragment is associated with a cyclic serial number indicating of a generation time of the information fragment; storing the multiple information fragments in multiple input queues, each input queue being associated with a communication path out of the multiple communication paths; determining whether at least one serial number associated with at least one valid information fragment positioned in a head of one of the multiple input queues is located within a pre-rollout serial number range; mapping, in response to the determination, serial numbers associated with each of the valid information fragment positioned in the heads of the multiple input queues to at least one serial number range that differs from the pre-rollout serial number range; and sending to an output queue information fragment metadata associated with a minimal v

Abstract: Personalized tag ranking of images, including identifying within a reference image collection any images that are similar to an input image, identifying within a source image collection any images that have associated tags that are similar to a set of input tags associated with the input image, identifying among the images identified in the reference image collection any images that are similar to the images identified in the source image collection, and calculating a weight for each of a plurality of tag pairs, where each of the tags in each of the tag pairs is associated with a different subset of the images in the reference image collection identified as being similar to the images identified in the source image collection, and ranking the input tags of the input image in accordance with a predefined ranking function as applied to the tag pair weights.

Abstract: A method and system for prioritising operations on network objects are provided. The method includes gathering Web 2.0 available relationship data on the relationships between network entities, wherein network entities are network users and network objects. The relationship data for a network entity is analysed and a first relative score is determined based on the relationship data. For a network object, a second relative score is determined which is a dynamic score based on user interactions with the network object and formed using the first relative scores of network entities interacting with the object. The method then prioritizes an operation on a network object using the second relative score.

Abstract: A device and method for processing information fragments, the method includes: receiving multiple information fragments from multiple communication paths; wherein the each information fragment is associated with a cyclic serial number indicating of a generation time of the information fragment; storing the multiple information fragments in multiple input queues, each input queue being associated with a communication path out of the multiple communication paths; determining whether at least one serial number associated with at least one valid information fragment positioned in a head of one of the multiple input queues is located within a pre-rollout serial number range; mapping, in response to the determination, serial numbers associated with each of the valid information fragment positioned in the heads of the multiple input queues to at least one serial number range that differs from the pre-rollout serial number range; and sending to an output queue information fragment metadata associated with a minimal v