Prabhdeep (PD) Singh

Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device… Show more

Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood. Show less

Methods, systems, and computer programs are presented for evaluating the accuracy of predictive systems and quantifiable measures of incremental value. One method provides a scientific solution to test and evaluate predictive systems in a transparent, rigorous, and verifiable way to allow decision-makers to better decide whether to adopt a new predictive system. In one example, objects to be evaluated are assigned to a control group or an experiment group. The testing provides an equal or… Show more

Methods, systems, and computer programs are presented for evaluating the accuracy of predictive systems and quantifiable measures of incremental value. One method provides a scientific solution to test and evaluate predictive systems in a transparent, rigorous, and verifiable way to allow decision-makers to better decide whether to adopt a new predictive system. In one example, objects to be evaluated are assigned to a control group or an experiment group. The testing provides an equal or better distribution of scores in the control group for the scores obtained with the first predictor, but the method aims at maximizing the scores of objects obtained with the second predictor in the experiment group. Since the first scores are evenly distributed in both groups, any result improvements may be attributed to the better accuracy of the second predictor when the results of the experiment group are better than the results of the control group. Show less

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… Show more

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. Show less

A system that analyses content of electronic communications may automatically extract requests or commitments from the electronic communications.

Task routing is a challenging task that includes tradeoffs. For example, a resource routed a task at time A, is not available to perform a different task at the same time. In another example, the time it takes for a resource to perform a task can limit a number of tasks fulfilled by the resource. Consider a resource that takes six minutes to perform a task, it cannot perform a task at a first time and a second task at five minutes after the first time, because it will not be available for… Show more

Task routing is a challenging task that includes tradeoffs. For example, a resource routed a task at time A, is not available to perform a different task at the same time. In another example, the time it takes for a resource to perform a task can limit a number of tasks fulfilled by the resource. Consider a resource that takes six minutes to perform a task, it cannot perform a task at a first time and a second task at five minutes after the first time, because it will not be available for another minute. Thus, the resource will not be available when a new, more important task is to be allocated three minutes after the first task is routed to the resource. Further yet, resources can be scarce and the number of tasks to be performed can be more than the scarce resources can handle. The resources can be insufficient to complete tasks to be performed in such circumstances, creating a task backlog, and thus some prioritization of backlog tasks and new tasks can help alleviate some of these problems. Show less

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;… Show more

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. Show less

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… Show more

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. Show less

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… Show more

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. Show less

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… Show more

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. Show less

A web site for user suggestions of products, services or other information. The Suggestor also submits tags with those suggestions. To the extent subsequent users use the same tags to access or purchase the user suggestion, the suggesting user will be rewarded. The present invention also provides mechanisms for disbursing rewards for "finding-and-buying-thru-tags", ranking suggestions, enabling various privacy preserving communications and deal validation mechanisms among shoppers, Suggestors… Show more

A web site for user suggestions of products, services or other information. The Suggestor also submits tags with those suggestions. To the extent subsequent users use the same tags to access or purchase the user suggestion, the suggesting user will be rewarded. The present invention also provides mechanisms for disbursing rewards for "finding-and-buying-thru-tags", ranking suggestions, enabling various privacy preserving communications and deal validation mechanisms among shoppers, Suggestors and their social networks. Show less