Blue Kai, Inc.

Oracle International Corporation

Cisco Technology, Inc.

Omar Tawakol

David Abraham Wiener

Jeffrey Charles Frantz

Fang Fang

Jason Leon Walsh

Raja Bishara Daoud

Lucian Vlad Lita

Tyler Scott

The present disclosure provides a detailed description of techniques used in methods, systems, and computer program products for associating anonymous information with personally identifiable information without sharing any personally identifiable information. A method receives a specification record comprising one or more specified demographic attributes to be used in user record selection operations, the results of which operations include user records that comprise a user identifier and at least some non-personally-identifiable information. A candidate group is formed by applying a set of rules over the retrieved user records to selectively exclude one or more user records that comprise mutually-exclusive characteristics with respect to the other user records in the candidate group. An anonymity measure is calculated over the candidate group to satisfy a threshold of anonymity. If needed to satisfy the threshold of anonymity, additional user records are added to the group before any sharing operations. Anonymity of the users is preserved.

Associating anonymous information with personally identifiable information in a non-identifiable manner

Embodiments are directed towards employing multiple profiles to track identification of users across multiple domains. Multiple application-domain profiles and multiple web-domain profiles may each include a statistical identifier. A profile enrichment store may be generated from the application-domain profiles and web-domain profiles, where each entry in the profile enrichment store may be based on statistical identifiers. The profile enrichment store may be utilized to determine categories associated with a statistical identifier for a request from a client device. A targeted advertisement may be determined based on the determined category and may be provided to the client device. A client caching identifier may be used in a mobile web domain, in combination with the statistical identifier, to track mobile web users. If a request is associated with a profile that includes an affirmative opt-out flag, categories in the profile enrichment store for a corresponding statistical identifier may be cleaned up.

Client caching identification tracking

Embodiments are directed towards collecting, aggregating and indexing unique and non-unique user data from a plurality of users. The result for a query of this indexed aggregation of user data is provided in a plurality of sub-sets of aggregated user data. Each subset of aggregated user data corresponds to a particular portion of the plurality of users. Also, each of these particular portions of the users is set at least large enough to provide general anonymity for the individual users. User data may be collected by one or more user data suppliers and provided to a user data aggregator. In some embodiments, user data may be collected as unique user data, non-unique user data, or any combination thereof. In some embodiments, user data may be aggregated by zip code, expanded zip code, and/or one or more attributes.

Profile noise anonymity for mobile users

The present disclosure provides a detailed description of techniques used in methods, systems, and computer program products for associating anonymous information with personally identifiable information without sharing any personally identifiable information. A method receives a specification record comprising one or more specified demographic attributes to be used in user record selection operations, the results of which operations include user records that comprise a user identifier and at least some non-personally-identifiable information. A candidate group is formed by applying a set of rules over the retrieved user records to exclude one or more user records that comprise mutually-exclusive characteristics with respect to the other user records in the candidate group. An anonymity measure is calculated over the candidate group to satisfy a threshold of anonymity. If needed to satisfy the threshold of anonymity, additional user records are added to the group before any sharing operations. Anonymity of the users is preserved.

In one embodiment, the interactive virtual meeting assistant implements a meeting debrief post-processing operation. For a given meeting that the interactive virtual meeting assistant participated in, a meeting post-processing engine enables one or more participants of the meeting to associate a debrief with the meeting. The debrief may be an audio recording, a video recording, text, or any file. The meeting post-processing engine stores the debrief in data stores and provides access to the debrief via the meeting GUI associated with the meeting. The meeting post-processing engine also processes the debrief to generate tasks to be assigned to participants or other entities and/or schedule reminders to be provided to the participants or other entities. The debrief may be private, such that only the participant who provided the debrief may subsequently access the debrief.

Growing community of inventors

Los Altos, CA, United States of America

Omar Tawakol