At&t Intellectual Property I, LP

Pamela Bogdan

Kenneth Shirley

Gary Reser

Alex Rubarkh

Gary Gressel

Nagaraj Sundaresan

Hema Gupta

Mary Hahola Rosell

Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.

Data analytics system and methods for text data

Aspects of the subject disclosure may include, for example, a computer that performs a statistical natural language processing analysis on a plurality of text documents to determine a plurality of topics, creates a proper subset of topics from the plurality of topics, based on user input, maps one or more topics in the proper subset of topics to each document in the plurality of text documents, thereby creating a plurality of topic-document pairs, identifies n-dimensions of bias for each topic-document pair from the text, creates clusters of topics from the proper subset of topics, and generates presentable content depicting each cluster of the clusters of topics according to a corresponding image configuration. The topics and n-dimensions of bias data can be further analyzed with co-collected structured data for statistical relationships. The topics and n-dimensions of bias data can be used for a publisher-subscriber network that uses content-driven routing when delivering raw data and summarized data via the network. Other embodiments are disclosed.

A method of balancing computer resources on a network of computers is provided employing a two-tier network architecture of at least one High Level Collector as a scheduler/load balancing server, and a plurality Low level Collectors which gather task data and execute instructions. Tasks are assigned priority and weight scores and sorted prior to assignment to Low Level Collectors. Also provided is a computer readable medium including instructions, wherein execution of the instructions by at least one computing device balances computer resources on a network of computers.

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Neptune, NJ, United States of America

Pamela Bogdan