Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Hewlett-packard Company

Emc Corporation

Entit Software LLC

Mohamed E Dekhil

Riddhiman Ghosh

Jerremy Holland

Umeshwar Dayal

Meichun Hsu

Jhilmil Jain

Ming C Hao

Lei Zhang

Christian Rohrdantz

Evan Randy Kirshenbaum

Maria G Castellanos

Jun Li

Keith E Moore

Ronald Brown

Vijay Machiraju

Cheng Chang

Phillip W Love

John Duncan Bankier

Rajesh Shenoy

Thomas Rathbone

Pankaj K Garg

Klaus Wurster

Bao-Yao Zhou

Bing Liu

Martin L Griss

John Cowan

Stuart MacNeil

Eric McCall

An event occurring in a particular geographic region is identified based on disseminated information containing public commentary in the particular geographic region. Attributes that are related to the event are identified, and sentiment words relating to the identified event are extracted from the disseminated information, where the extracted sentiment words are in a local language of the particular geographic region. A sentiment trend visualization is generated that depicts a trend of sentiments of at least a particular one of the identified attributes, wherein the sentiments are based on the sentiment words for at least the particular attribute.

Sentiment trent visualization relating to an event occuring in a particular geographic region

The present disclosure provides a computer-implemented method of acquiring customer insight information in a retail environment. The method includes receiving a product interaction from a mobile device, the product interaction comprising a product identifier corresponding to a product located in the retail environment. The method also includes determining a customer location within the retail environment based on a planned location of the product. The method also includes performing a business action based, at least in part, on the product interaction. The method also includes storing customer insight information corresponding to the product interaction to a data structure.

Acquiring customer insight in a retail environment

A method of capturing intentions within online text comprises with a data mining device (), identifying (block) a number of statements of intention within an online forum (), and with the data mining device (), extracting (block) a number of attributes () from the statements of intention. A system () for extracting intentions expressed within an online forum comprises a data mining device (), a forum server () comprising a number of online forums () communicatively coupled to the data mining device (), in which the data mining device identifies a number of statements of intention within the online forums () and extracts a number of attributes () from the statements of intention.

Capturing intentions within online text

A method comprises receiving, across a network at a computing device, media data. The method further comprises determining to which project associated with a user and hosted on the computing device to save the media data. The method further comprises saving the media data to the project. The project is adapted to store media data of different types.

Projects containing media data of different types

There is provided a computer-implemented method of performing sentiment analysis. An exemplary method comprises performing a first sentiment analysis on microblogging data based on a method using an opinion lexicon. The method also includes training a classifier using training data from the first sentiment analysis. Additionally, the method includes identifying a new opinion term in the microblogging data by performing a statistical test. The new opinion terms are not in the opinion lexicon. The method also includes identifying new microblogging data based on the new opinion term. Further, the method includes performing a second sentiment analysis on the new microblogging data using the classifier.

Performing sentiment analysis on microblogging data, including identifying a new opinion term therein

There is provided a computer-implemented method of performing sentiment analysis. An exemplary method comprises identifying one or more sentences in a microblog. The microblog comprises an entity. The method further includes identifying one or more opinion words in the sentences based on an opinion lexicon. Additionally, the method includes determining, for each of the sentences, an opinion value for the entity. The opinion value is determined based on an opinion value for each of the opinion words in an opinion lexicon.

Performing sentiment analysis

Data records containing user feedback regarding at least one offering are received. From among candidate attributes in the received data records, a subset of attributes that relate to user sentiment regarding the at least one offering is selected, where the selecting is according to selection criteria including frequency of occurrence of the candidate attributes, relative amounts of negative and positive feedback associated with the candidate attributes, and time density of feedback associated with the candidate attributes. A visualization of at least one sentiment characteristic of the selected subset of attributes that relate to user sentiment is presented for display.

Selecting sentiment attributes for visualization

Methods, systems and machine readable medium storing a machine readable program for managing data stored on a contactless flash memory device are disclosed. A compiled version of a hierarchical data model defined using a high level data structure definition language is provided at a host unit. The host unit is operable to run on a host platform. The compiled version of the hierarchical data model is compiled for the host platform. A first representation of a first hierarchical data structure is received from a contactless flash memory device at the host unit via a contactless communication channel. The first hierarchical data structure is a first instantiation of the hierarchical data model. A second representation of the first hierarchical data structure is generated in accordance with the compiled hierarchical data model at the host unit.

Methods and systems for managing data stored on a contactless flash memory device

An exemplary method for providing secure access to resources at shared appliances comprises obtaining an instruction from a first user to send a resource to a secure repository, the resource being associated with a first identifier, receiving a second identifier from a shared appliance, determining a pseudo identity associated with the shared appliance based on the second identifier, granting to the shared appliance permissions associated with the pseudo identity, including a permission to retrieve the resource from the secure repository, receiving the first identifier from a second user at the shared appliance, and enabling the shared appliance to provide the resource to the second user at the shared appliance.

Secure access of resources at shared appliances

System and method for capturing and utilizing consumer purchase intent information comprise obtaining item information, from a user, in a plurality of formats from a plurality of sources, extracting keywords from the item information, organizing item information and keywords in a shopping list, and enabling a display of the shopping list to the user.

Capturing and utilizing consumer purchase intent information

Electronic commerce transaction messages are processed over a network between a client and a server in a highly reliable fashion by establishing a secure or un-secure communications connection between the network client and the network server at an electronic transaction assurance (eTA) system, which is located in a communication path between the network client and the network server. The transaction type is identified in the message and the progress of the transaction is tracked using transaction models. Any failure in the back-end server system or in the network connections is detected and the failure is recovered from using an outcome determination technique. The failure of a node within the eTA system is masked from the network client by formulating an appropriate response and sending it back to the client such that the network client and network server that were using the selected node do not see any interruption in their communications.

Highly available transaction failure detection and recovery for electronic commerce transactions

An auto-discovery system discovers related components of a service operating on a distributed network. This auto-discovery system involves (1) selecting a model of the configuration of the service; (2) determining, from the model, &ldquo;scope hints&rdquo; that limit the possible locations of related components; (3) determining a root component of the service; (4) using scope hints to limit the search, to rapidly find related instances of components contained in the root service component; (5) determining whether a quorum of components comprising a distributed service has been discovered; (6) determining the parent service component of each discovered service component by instance matching; and (7) using the instance match information to determine the discovery tree of components that have the structure of the service map, share a common root component, and define a service group. This auto-discovery system efficiently discovers the components of a wide range of services within a distributed environment. The system limits the scope of searches for components related to previously discovered components. The system determines the relationships between the discovered service components, and matches them into groups of related services. This enables an operational manager of a distributed service to better determine service configurations, expand resource bottlenecks, and improve an end-users' experience.

Method and apparatus auto-discovering components of distributed services

A system for predicting system behavior of a managed system includes a measurement module coupled to the managed system to generate measurement data of the managed system. The measurement data include current measurement data and past measurement data. The past measurement data indicate a problem of the managed system. A pattern classification module is coupled to the measurement module to process the past measurement data into a plurality of representative pattern images, and to select a predictor pattern image that best identifies the problem from the pattern images. A pattern matching module is coupled to the pattern classification module and the measurement module to process the current measurement data into a plurality of pattern images using the same image processing technique that generates the predictor pattern image. The pattern matching module also identifies any pattern image that matches the predictor pattern image to predict the problem. A system for generating a predictor pattern image for predicting system behavior of a managed system is also described.

Predicting system behavior of a managed system using pattern recognition techniques

A system for monitoring system behavior of a managed/instrumented system is described. The system includes a measurement module coupled to the managed system to generate measurement data of the managed system. The measurement data include past measurement data and current measurement data. A store is also provided that stores the past measurement data. A genetic programming module is coupled to the store to evolve the evolved predictor based on the past measurement data and predetermined effectiveness criteria such that the evolved predictor predicts the system behavior of the managed system when supplied with the current measurement data. The genetic programming module genetically manipulates a set of candidate predictors to produce the evolved predictor. A system for generating the evolved predictor is also described.

Growing community of inventors

Santa Clara, CA, United States of America

Mohamed E Dekhil