Microsoft Technology Licensing, LLC

Junzhe Miao

Dan Shacham

Hong H Tam

Tianhao Lu

Yunpeng Xu

Ted Tomlinson

Gurbir Singh

Tao Xiong

Paul D Bergeron

The disclosed embodiments provide a system for processing data. During operation, the system extracts text windows of varying length from text in one or more content items associated with an entity. Next, the system applies a machine learning model to features for the text windows to produce scores representing the likelihoods that the text windows contain addresses. The system then identifies, based on the scores and validation rules applied to the text windows, one of the text windows as an address for the entity. Finally, the system stores the selected text window as the address for the entity.

Identifying and extracting addresses within content

The disclosed embodiments provide a system that identifies duplicate entities. During operation, the system selects training data for a first machine learning model based on confidence scores representing likelihoods that pairs of entities in an online system are duplicates. Next, the system updates parameters of the first machine learning model based on features and labels in the training data. The system then identifies a first subset of additional pairs of the entities as duplicate entities based on scores generated by the first machine learning model from values of the features for the additional pairs and a first threshold associated with the scores. The system also determines a canonical entity in each of the duplicate entities based on additional features. Finally, the system updates content outputted in a user interface of the online system based on the identified first subset of the additional pairs.

Identifying duplicate entities

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Junzhe Miao