Patent application number | Description | Published |
20110246465 | METHODS AND SYSEMS FOR PERFORMING REAL-TIME RECOMMENDATION PROCESSING - Methods and systems are presented for recommending similar questions to one that a user has entered into a search engine. Previously-entered questions are subject to a clustering algorithm and placed into a hierarchy of clusters, with clusters set within clusters. For each cluster within the hierarchy, a representative vector, based on feature vectors of the items within the cluster, is calculated. A feature vector for the user's question is calculated and used, along with the representative vectors at each level in the hierarchy, to traverse and navigate the cluster hierarchy. When a leaf cluster is found, the items in the leaf cluster, such as the previously-entered questions are returned to the user. A subset of items in the leaf cluster, or items from other leaf clusters within a branch cluster, can be selected based on the number of items desired to be returned. | 10-06-2011 |
20110246520 | METHOD AND SYSTEM FOR PERFORMING AN AUTHORITY ANALYSIS - Methods and systems for automatically determining, from a body of emails, blogs, and other documents, authors of the documents who are authorities on certain subjects, and what those subjects are. An intersection of the semantic footprints of documents by an author are deemed to be the derived skills footprint of the author. The derived skills footprints of many authors are compared with a user's query to determine who is the best person that could respond to the user. | 10-06-2011 |
20110282814 | METHODS AND SYSTEMS FOR IMPLEMENTING A COMPOSITIONAL RECOMMENDER FRAMEWORK - A compositional recommender framework using modular recommendation functions is described. Each modular recommendation function can use a discrete technology, such as using clustering, a database lookup, or other means. A first recommendation function can recommend to a user items, such as books to check out, automobiles to purchase, people to date, etc. Another modular recommendation function can be daisy chained with the first to recommend items that are similar or related to the first recommended items, such as users who have also checked out the same recommended book, trailers that can be towed by the recommended automobiles, or vacations booked by people that were recommended as people to date. The modular recommendation functions can be used to build customized recommendation engines for different industries. | 11-17-2011 |
20130024412 | METHODS AND SYSTEMS FOR USING MAP-REDUCE FOR LARGE-SCALE ANALYSIS OF GRAPH-BASED DATA - Embodiments are described for a method for processing graph data by executing a Markov Clustering algorithm (MCL) to find clusters of vertices of the graph data, organizing the graph data by column by calculating a probability percentage for each column of a similarity matrix of the graph data to produce column data, generating a probability matrix of states of the column data, performing an expansion of the probability matrix by computing a power of the matrix using a Map-Reduce model executed in a processor-based computing device; and organizing the probability matrix into a set of sub-matrices to find the least amount of data needed for the Map-Reduce model given that two lines of data in the matrix are required to compute a single value for the power of the matrix. One of at least two strategies may be used to computing the power of the matrix (matrix square, M | 01-24-2013 |
20130024479 | METHODS AND SYSTEMS FOR PROCESSING LARGE GRAPHS USING DENSITY-BASED PROCESSES USING MAP-REDUCE - Embodiments are directed to a density-based clustering algorithm that decomposes and reformulates the DBSCAN algorithm to facilitate its performance on the Map-Reduce model. The DBSCAN algorithm is reformulated into connectivity problem using a density filter method and a partial connectivity detector. The density-based clustering algorithm uses message passing and edge adding to increase the speed of result merging, it also uses message mining techniques to further decrease the number of iterations to process the input graph. The algorithm is scalable, and can be accelerated by using more machines in a distributed computer network implementing the Map-Reduce program. | 01-24-2013 |
20130085745 | SEMANTIC-BASED APPROACH FOR IDENTIFYING TOPICS IN A CORPUS OF TEXT-BASED ITEMS - A method of identifying topics in a corpus that includes a plurality of text-based items begins by extracting keytext from each of the plurality of text-based items, resulting in sets of keytext. The method continues by processing the keytext sets to generate a respective semantic footprint for each of the text-based items, resulting in a plurality of semantic footprints. The semantic footprints are used to calculate similarity values for the text-based items, wherein the similarity values indicate commonality between pairs of the text-based items. The method continues by clustering the text-based items into a number of topic groups, wherein the clustering is influenced by the similarity values, and by generating a topic heading for each of the number of topic groups, resulting in a number of topic headings. Next, the text-based items are grouped into accessible topic groups associated with the topic headings. | 04-04-2013 |
20130246332 | METHODS AND SYSTEMS FOR IMPLEMENTING A COMPOSITIONAL RECOMMENDER FRAMEWORK - A compositional recommender framework using modular recommendation functions is described. Each modular recommendation function can use a discrete technology, such as using clustering, a database lookup, or other means. A first recommendation function can recommend to a user items, such as books to check out, automobiles to purchase, people to date, etc. Another modular recommendation function can be daisy chained with the first to recommend items that are similar or related to the first recommended items, such as users who have also checked out the same recommended book, trailers that can be towed by the recommended automobiles, or vacations booked by people that were recommended as people to date. The modular recommendation functions can be used to build customized recommendation engines for different industries. | 09-19-2013 |
20160005092 | METHOD AND DEVICE UTILIZING POLYMORPHIC DATA IN E-COMMERCE - An aspect of the present invention includes a protocol for conveying data during an e-commerce session with a polymorphic response, comprising initiating a session with a message from a buyer application to a broker application and a session identifier assigned by the broker application; conducting the session between the buyer application and a supplier application; and concluding the session with a additional message which includes a schema identifier for the additional message, resolvable in a context of a system identifier, and a polymorphic response comprising a type and a version, wherein the polymorphic response includes additional data elements corresponding to values assigned to the type and version. | 01-07-2016 |