MULTI-MODALITY CLASSIFICATION FOR ONE-CLASS CLASSIFICATION IN SOCIAL NETWORKS
First Claim
1. A classification method comprising:
- for each of a plurality of modalities;
extracting features from objects in a set of objects, the objects comprising electronic mail messages, andgenerating a representation of each object based on its extracted features;
at least one of the plurality of modalities being a social-network modality in which social network features are extracted from a social network implicit in the electronic mail messages;
training a classifier system based on class labels of a subset of the set of objects and on the representations generated for each of the modalities; and
with the trained classifier system, predicting labels for unlabeled objects in the set of objects.
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Accused Products
Abstract
A classification apparatus, method, and computer program product for multi-modality classification are disclosed. For each of a plurality of modalities, the method includes extracting features from objects in a set of objects. The objects include electronic mail messages. A representation of each object for that modality is generated, based on its extracted features. At least one of the plurality of modalities is a social network modality in which social network features are extracted from a social network implicit in the set of electronic mail messages. A classifier system is trained based on class labels of a subset of the set of objects and on the representations generated for each of the modalities. With the trained classifier system, labels are predicted for unlabeled objects in the set of objects.
405 Citations
21 Claims
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1. A classification method comprising:
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for each of a plurality of modalities; extracting features from objects in a set of objects, the objects comprising electronic mail messages, and generating a representation of each object based on its extracted features; at least one of the plurality of modalities being a social-network modality in which social network features are extracted from a social network implicit in the electronic mail messages; training a classifier system based on class labels of a subset of the set of objects and on the representations generated for each of the modalities; and with the trained classifier system, predicting labels for unlabeled objects in the set of objects. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A classification apparatus comprising:
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an input for receiving a set of objects, the objects comprising electronic mail messages, a subset of the objects having class labels; a first feature extractor which extracts text-based features from objects in the set of objects; a second feature extractor which extracts social network-based features from the objects in the set of objects; a classifier system, executed by a computer processor, which predicts labels for unlabeled objects in the set of objects based on the extracted text-based and social network-based features.
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18. A classification method comprising:
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for each of a plurality of modalities; extracting features from objects in a set of objects comprising electronic mail messages, and generating a representation of each object based on its extracted features; training a one-class classifier system based on class labels of a subset of the set of objects and on the representations generated for each of the modalities, the training including, for each of the modalities; based on an initial set of objects positively labeled with respect to the class, generating an initial hypothesis which predicts negative labels for a subset of the unlabeled objects in the set, and iteratively generating a new hypothesis in which a new boundary between representations of objects predicted as having negative labels and representations of objects predicted as having positive labels converges towards an original boundary between the representations of the initial positively labeled objects and the rest of the objects in the set; and with the trained classifier system, predicting labels for unlabeled objects in the set of objects. - View Dependent Claims (19, 20, 21)
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Specification