Abstract: A method to predict churn includes obtaining static features representative of a customer of a service, obtaining time series features representative of the customers interaction with the service, using a deep neural network to process the static features, using a recurrent neural network to process the time series features; and combining outputs from the deep neural network and the recurrent neural network to predict likelihood of customer churn.

Abstract: A processing unit can operate a first recurrent computational model (RCM) to provide first state information and a predicted result value. The processing unit can operating a first network computational model (NCM) to provide respective expectation values of a plurality of actions based at least in part on the first state information. The processing unit can provide an indication of at least one of the plurality of actions, and receive a reference result value, e.g., via a communications interface. The processing unit can train the first RCM based at least in part on the predicted result value and the reference result value to provide a second RCM, and can train the first NCM based at least in part on the first state information and the at least one of the plurality of actions to provide a second NCM.

Abstract: A deep learning network is trained to automatically analyze enterprise data. Raw data from one or more global data sources is received, and a specific training dataset that includes data exemplary of the enterprise data is also received. The raw data from the global data sources is used to pre-train the deep learning network to predict the results of a specific enterprise outcome scenario. The specific training dataset is then used to further train the deep learning network to predict the results of a specific enterprise outcome scenario. Alternately, the raw data from the global data sources may be automatically mined to identify semantic relationships there-within, and the identified semantic relationships may be used to pre-train the deep learning network to predict the results of a specific enterprise outcome scenario.

Abstract: A processing unit can acquire datasets from respective data sources, each having a respective unique data domain. The processing unit can determine values of a plurality of features based on the plurality of datasets. The processing unit can modify input-specific parameters or history parameters of a computational model based on the values of the features. In some examples, the processing unit can determine an estimated value of a target feature based at least in part on the modified computational model and values of one or more reference features. In some examples, the computational model can include neural networks for several input sets. An output layer of at least one of the neural networks can be connected to the respective hidden layer(s) of one or more other(s) of the neural networks. In some examples, the neural networks can be operated to provide transformed feature value(s) for respective times.

Abstract: A method of extracting knowledge comprising: initiating a search application; displaying a user search interface; receiving input parameters via the search interface; identifying a query type based on received input parameters; formulating a database query based on the received input parameters; transmitting the database query to a database, the database being in communication with a file archive indexer for indexing a file archive for storing files and data regarding the files; obtaining database query results from the database, the database storing the user activity data and actual content accessed by the user; providing database query results to a result analyzer module; and displaying search result analyzer module results to a user.

Abstract: A system that analyses content of electronic communications may automatically detect requests or commitments from the electronic communications. In one example process, a processor may identify a request or a commitment in the content of the electronic message; based, at least in part, on the request or the commitment, determine an informal contract; and execute one or more actions to manage the informal contract, the one or more actions based, at least in part, on the request or the commitment.

Abstract: A system that analyses content of electronic communications may automatically extract requests or commitments from the electronic communications. In one example process, a processing component may analyze the content to determine one or more meanings of the content; query content of one or more data sources that is related to the electronic communications; and based, at least in part, on (i) the one or more meanings of the content and (ii) the content of the one or more data sources, automatically identify and extract a request or commitment from the content. Multiple actions may follow from initial recognition and extraction, including confirmation and refinement of the description of the request or commitment, and actions that assist one or more of the senders, recipients, or others to track and address the request or commitment, including the creation of additional messages, reminders, appointments, or to-do lists.

Abstract: A system and method which allow for connecting users with people of interest based on preferences and current location. The system allows users to connect when on board of the same transportation means such as an airplane. A wireless network is provided which is connected to a server including profile information of different users. The server makes the profile of a given user available for viewing by others depending on a number of factors including the current preferences of the given user (whether they allow other users to contact them or not at the given moment) and/or depending on the presence of a match between the profiles and preferences of the users. Using the current system, users may chat in real time using mobile phones over the wireless network. A method is also described which allow for managing and securing the access of one user to another based on each user's current location.

Abstract: Described herein are various technologies pertaining to performing an operation relative to tabular data based upon voice input. An ASR system includes a language model that is customized based upon content of the tabular data. The ASR system receives a voice signal that is representative of speech of a user. The ASR system creates a transcription of the voice signal based upon the ASR being customized with the content of the tabular data. The operation relative to the tabular data is performed based upon the transcription of the voice signal.

Abstract: A method of extracting knowledge comprising: initiating a search application; displaying a user search interface; receiving input parameters via the search interface; identifying a query type based on received input parameters; formulating a database query based on the received input parameters; transmitting the database query to a database, the database being in communication with a file archive indexer for indexing a file archive for storing files and data regarding the files; obtaining database query results from the database, the database storing the user activity data and actual content accessed by the user; providing database query results to a result analyzer module; and displaying search result analyzer module results to a user.

Abstract: A method of timing and recording user activity in a knowledge archival and recollection system, the method comprising: configuring an activity tracking module; logging into the knowledge archival and recollection system; prompting the user with a task identifier input interface upon opening an application user interface; initiating a timer upon input into the input interface; stopping the timer upon inactive application interface; and storing timer data into a database server.

Abstract: A computer implemented method of recording user activity in a knowledge archival and recollection system, comprising: initiating a network browser plug-in on detecting that a network browser has been opened; providing at least one file to a user from the network; transmitting and storing at least one file to a file archive using a file transfer protocol; gathering user activity data for each said at least one file accessed; associating user activity data to each related file; transmitting and storing user activity data to a database server using a database connection protocol; and indexing each file.

Abstract: A method of recording user activity of a user on a comprising the steps of providing a file to a user from a network; transmitting and storing the file to a file archive; gathering user activity data for each file accessed; associating user activity data with each file accessed; and transmitting and storing user activity data; categorizing user activity data; ranking user activity data; compressing/decompressing user activity data; removing redundant data from file archive; collecting file enhancement data, associating the file enhancement data with a file being currently accessed by the user, and transmitting the file enhancement data; storing the actual content accessed by the user and the file enhancement data as stored material; indexing the stored material; receiving a command, including input parameters, for conducting a search of the stored material, the input parameters including keyword and file enhancement data from the user; generating a customizable user activity report.

Abstract: A computer implemented method of recording user activity in a knowledge archival and recollection system, comprising: initiating a network browser plug-in on detecting that a network browser has been opened; providing at least one file to a user from the network; transmitting and storing at least one file to a file archive using a file transfer protocol; gathering user activity data for each said at least one file accessed; associating user activity data to each related file; transmitting and storing user activity data to a database server using a database connection protocol; and indexing each file.

Abstract: A knowledge archival and recollection system accessible by a user, comprising: a data acquisition module in communication with a database server, a file archive and a database connectivity module; a data presentation module in communication with a report module and a search module; a timing module in communication with the database server; an automatic billing module in communication with a report module and database server; a messenger monitor module in communication with the database server, and the file archive; a database connectivity module in communication with the data acquisition module, the file archive, the database server, the report module, the search module, the automatic billing module, the timing module and the messenger monitor module; the system gathers user activity data and files accessed by user through the data acquisition module and archives the data and files on the database server and file archive for retrieval by each user.

Abstract: The synchronous semantic processing technique described herein provides the level of completeness of a document in real-time as a user is creating or editing the document and provides recommendations to the user to increase the level of completeness. In one embodiment, the level of completeness of a medical document, and the state of the components of the document that are used to determine level, are used to make recommendations to a user (e.g., a physician) to provide additional information for the components that determine the level, thereby increasing the level. The level of medical documentation can be represented by an Evaluation and Management (E&M) coding level, which is a U.S. standard defined to evaluate how comprehensive a medical document is. The E&M level is used to determine the completeness of the medical document and to make recommendations to the user to improve the quality and the completeness of the document.

Abstract: A method of extracting knowledge comprising: initiating a search application; displaying a user search interface; receiving input parameters via the search interface; identifying a query type based on received input parameters; formulating a database query based on the received input parameters; transmitting the database query to a database, the database being in communication with a file archive indexer for indexing a file archive for storing files and data regarding the files; obtaining database query results from the database, the database storing the user activity data and actual content accessed by the user; providing database query results to a result analyzer module; and displaying search result analyzer module results to a user.

Abstract: A method of extracting knowledge from a knowledge archival and recollection system, comprising the steps of: recognizing a user actuation; initiating a search application; displaying a user search interface; receiving input parameters via the search interface; identifying a query type based on the received input parameters; formulating a database query based on the received input parameters; transmitting the database query to a database; obtaining database query results from the database; providing the database query results to a result analyzer module; and displaying search result analyzer module results to a user.

Abstract: A computer implemented method of recording user activity in a knowledge archival and recollection system, comprising: initiating a network browser plug-in on detecting that a network browser has been opened; providing at least one file to a user from the network; transmitting and storing at least one file to a file archive using a file transfer protocol; gathering user activity data for each said at least one file accessed; associating user activity data to each related file; transmitting and storing user activity data to a database server using a database connection protocol; and indexing each file.

Abstract: The present invention generally relates to data acquisition, analysis, and management system for professionals and organizations of all sizes across many different industries. Specifically, the present invention provides systems and methods for tracking, billing, logging, reporting, archiving, searching, and mining on- and off-line user interactions. Not only does the present invention provide methods that simplify business and/or academic research activities, but provides an easy way to build and manage a scalable and secure e-library system. The present invention includes a unique log, report, search, and annotation engines, plus personalization and customization features. Sophisticated data acquisition, analysis, and management modules are hidden behind a simple toolbar embedded in the Network browser on a client computer.