Xerox Corporation

Mathieu Chuat

Vincent Devin

Pól Ó Móráin

A system and method provide recommendations for refining training data that includes a training set of digital objects. A submitter labels the digital objects in the training set with labels, which may indicate whether the object is considered positive, neutral, or negative with respect to each of a predefined set of classes. Score vectors are computed by a trained categorizer for each digital object in the labeled training set. From the score vectors, various metrics are computed, such as a representative score vector and distances of score vectors from the representative score vector for a label group, cluster, or category of the categorizer. Based on the computed metrics, heuristics are applied and the training data is evaluated and recommendations may be made to the submitter, such as proposing that mislabeled objects are relabeled. The training data may include unlabeled digital objects, in which case, the recommendations may include suggestions for labeling the unlabeled objects.

Pre-screening training data for classifiers

A system and method for digital object categorization or retrieval are provided. The method includes providing for a selector to be graphically presented to a user. The selector is variably adjustable within a range, by the user, to adjust a level of noise in at least one of digital object categorization and digital object retrieval. The range of the selector is normalized over a set of digital object categories based on scores output by a trained categorizer for each of a set of labeled test objects for each of the set of digital object categories and a label for each of the test objects. Selector position information is received by the system and at least one of digital object categorization and digital object retrieval is performed, based on the selector position information. One or more of the method steps may be performed with a computer processor.

Parameterization of a categorizer for adjusting image categorization and retrieval

A system and method is disclosed for providing usage metrics of digital content. The system includes one or more clients, such as a computer and an audio player device, a usage metrics server and an optional recommendation system, which are connected together by a network, such as the Internet. A consumer or user at a client system, such as the computer, downloads digital content from a content provider. As the client consumes the digital content, a tracking system operating on the client uploads usage data to the usage metrics system. The usage metrics system processes the usage data and stores the processed data in a storage for subsequent retrieval to provide the data to a content provider, the optional recommendation system and/or third party systems.

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Meylan, France

Mathieu Chuat