Microsoft Technology Licensing, LLC

Jayaram Nm Nanduri

Shoou-Jiun Wang

Eric J Horvitz

Alexander G Gounares

Jason Garms

Mary P Czerwinski

Nikhil Kothari

Brett David Brewer

Milind V Mahajan

Melissa Wood Dunn

Cezary Antoni Marcjan

Karim Taji Farouki

Timothy David Sharpe

Hung-Chih Yang

Darrell Leroy Blegen

Anand Ravindra Oka

Yuting Jia

Ram P Sunkara

Mohan Varthakavi

Yung-Wen Liu

Murali Krishna Manjunath

Ming-Yu Fan

Adam Reinhardt

Ram Prasad Sunkara

Various device attributes associated with a current event may be obtained. Similarity metrics may be determined that indicate a degree of similarity between the device attributes that are associated with the current event and stored device attributes that are associated with previous events and previously created fuzzy device identifiers. A fuzzy device identifier may be assigned to the current event based at least in part on a comparison of the similarity metrics with a threshold. If none of the similarity metrics compare favorably with the threshold, then a new fuzzy device identifier may be created for the current event. However, if at least one of the similarity metrics compares favorably with the threshold, then the previously created fuzzy device identifier whose stored device attributes are most similar to the device attributes that are associated with the current event may be assigned to the current event.

Facilitating device fingerprinting through assignment of fuzzy device identifiers

Training risk determination models based on a set of labeled data transactions. A first set of labeled data transactions that have been labeled during a review process is accessed. A first risk determination model is trained using the first set of labeled data transactions. A first risk score for data transactions of a set of unlabeled data transactions is determined using the first risk determination model. Data transactions in the set of unlabeled data transactions are newly labeled based on the first risk score. The newly labeled data transactions are added to a second set of labeled data transactions that include the first set of labeled data transactions. A second risk determination model is trained using at least the second set of labeled data transactions. A second risk score is determined for subsequently received data transactions and these data transactions are rejected or approved based on the second risk score.

Using semi-supervised label procreation to train a risk determination model

Concepts and technologies are described herein for multi-mode text input. In accordance with the concepts and technologies disclosed herein, content is received. The content can include one or more input indicators. The input indicators can indicate that user input can be used in conjunction with consumption or use of the content. The application is configured to analyze the content to determine context associated with the content and/or the client device executing the application. The application also is configured to determine, based upon the content and/or the contextual information, which input device to use to obtain input associated with use or consumption of the content. Input captured with the input device can be converted to text and used during use or consumption of the content.

Multi-mode text input

The claimed subject matter relates to an architecture that can mitigate privacy concerns in connection with ad targeting or data collection. In particular, architecture can be included in a personal mobile communication device such as a cell phone. During communication transactions between the host device and a peer device, shared information can be extracted either from content included in the communication or from metadata. Based upon the shared information, a social graph maintained on the host device can be updated. In addition, the host device can receive a large set of ads and select or tailor a custom ad from the set based upon the social graph.

Privacy-centric ad models that leverage social graphs

Growing community of inventors

Issaquah, WA, United States of America

Jayaram Nm Nanduri