Conduent Business Services, LLC

William Radford

Julien Perez

Matthias Gallé

James Brinton Henderson

Xavier Carreras

A system and method for dialog state tracking employ an ontology in which a set of values are indexed by slot. A segment of a dialog is processed to detect mentions. Candidate slot values are extracted from the ontology, based on the detected mentions. The candidate slot values are ranked. A dialog state is updated, based on the ranking of the candidate slot values, which may be conditioned on the output of a temporal model, which predicts whether the value of the slot has been instantiated, modified, or is unchanged.

Probabilistic matching for dialog state tracking with limited training data

A method for entity recognition employs document-level entity tags which correspond to mentions appearing in the document, without specifying their locations. A named entity recognition model is trained on features extracted from text samples tagged with document-level entity tags. A text document to be labeled is received, the text document being tagged with at least one document-level entity tag. A document-specific gazetteer is generated, based on the at least one document-level entity tag. The gazetteer includes a set of entries, one entry for each of a set of entity names. For a text sequence of the document, features for tokens of the text sequence are extracted. The features include document-specific features for tokens matching at least a part of the entity name of one of the gazetteer entries. Entity labels are predicted for the tokens in the text sequence with the named entity recognition model, based on the extracted features.

Document-specific gazetteers for named entity recognition

A method for language prediction of a social network post includes generating a social network graph which includes nodes connected by edges. Some of the nodes are user nodes representing users of a social network and some of the nodes are social network post nodes representing social network posts. At least some of the users are authors of social network posts represented by respective social network post nodes. Edges of the graph are associated with respective weights. At least one of the social network post nodes is unlabeled. Language labels are predicted for the at least one unlabeled social network post node which includes propagating language labels through the graph. A language of the social network post is predicted based on the predicted language labels for the social network post node representing that social network post and optionally also based on content-based features.

Growing community of inventors

Grenoble, France

William Radford