Nike, Inc.

Celect, Inc.

Vishal Doshi

Devavrat D Shah

Ying-zong Huang

Vasudha Shivamoggi

Ritesh Madan

Balaji Rengarajan

Joshua Lee

George Chen

Quan Li

Vighnesh Sachidananda

Sai Kiran Burle

Computer-implemented prediction methods, in accordance with various embodiments, involve storing key-value pairs each including a key tuple and an associated value in a data store, building a prediction model associated with at least a subset of the key-value pairs, and in response to receipt of a prediction query that specifies a key tuple, generating a prediction response based on the prediction model that includes a predicted value for the specified key tuple. In one example application, the key tuples each include an operation specifying a purchase and a two-part identifier specifying a customer and a product.

Event prediction

A system for event prediction is configured to ingest at least partially incomplete unstructured data from at least one data source, convert at least a subset of the ingested data into a prediction model in accordance with a received model definition, receive a prediction query, and in response, supply an event prediction based on the prediction model. In some embodiments, ingesting the data involves transforming the unstructured data into a universal structured format in which the data is represented as key-value pairs each comprising a key tuple and an associated value, the key tuple specifying an operation and at least one identifier; the prediction query includes a key tuple specifying an operation and at least one identifier; and the event prediction generated with the prediction model includes a value associated with the key tuple that is missing from the transformed data.

A system includes at least one connector configured to gather at least partially incomplete data from at least one data source. The gathered data is communicated to a model definition module that converts at least a subset of the gathered data into a prediction model in accordance with a received definition. A prediction module receives a prediction query and, in response, supplies an event prediction based on the prediction model.

Methods and apparatus for predicting unknown values given a data set of known values. A prediction engine ingests a variety of data sets. Once the dataset has been ingested, requests for predictions may be presented to the prediction engine. The engine responds with a prediction as well as a confidence score based on the ingested information using a variety of techniques. Some of these techniques identify witness values in the ingested data that are similar to the requested prediction, other techniques compute witness values from ingested data, etc. These witness values are aggregated to yield an answer and a confidence level in a way that permits the user to review the underlying witness values.

Prediction using fusion of heterogeneous unstructured data

Systems and methods for tracking at least one entity. Systems according to various embodiments may include an interface for at least receiving training data representing movements of a plurality of training entities and a query regarding a test entity's movement, a memory, and at least one processor executing instructions stored on the memory to create a plurality of tracks, generate an index of the plurality of tracks, execute the received query, and output a feature value with respect to the test entity.

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Somerville, MA, United States of America

Vishal Doshi