Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: A fiber blend comprising a staple fiber formed from cellulose acetate and a binder fiber. The staple fiber has a crimp frequency of 10 to 30 crimps per inch (CPI), a cut length of 55 mm or less, and a non-round cross-sectional shape. The blend can be made into nonwoven webs for heat-bonding and subsequent use as thermal insulation in, e.g., outerwear, bedding, etc. The cellulose acetate fibers provide superior thermal insulation clo value relative to at equivalent loft.

Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: An online system uses rules and/or machine learning models to provide travel related content items to users. The online system may determine when a user is likely to travel and provide the content items in advance of a trip. The online system may also provide content items during a trip that indicate modifications to the user's itinerary, for example, adding a rental car, upgrading a flight ticket, or upgrading a hotel room. Further, the online system may provide a content item after a user has checked out of a hotel that describes a loyalty program of the hotel. In one example, the online system trains machine learning models using feature vectors derived based on trips taken by a population of users of the online system and itinerary information from third parties. The content items may be generated based on information provided from the third parties.

Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: Online system users interact with one or more third party systems, with the online system maintaining an account for each of its users and each third party system maintaining a third party account for each of its users. The online system compares information in a user's account to accessible information in third party accounts and establishes connections between the user's account and o third party accounts based on the comparisons. A connection between the user's account and a third party account includes a confidence level indicating a likelihood of the third party account being associated with the user of the online system corresponding to the account. A third party system may request information from the online system about a user specifying a threshold confidence level, allowing the online system to return information from third party accounts having connections to the user's account with at least the threshold confidence level.

Abstract: Online system users interact with one or more third party systems, with the online system maintaining an account for each of its users and each third party system maintaining a third party account for each of its users. The online system compares information in a user's account to accessible information in third party accounts and establishes connections between the user's account and o third party accounts based on the comparisons. A connection between the user's account and a third party account includes a confidence level indicating a likelihood of the third party account being associated with the user of the online system corresponding to the account. A third party system may request information from the online system about a user specifying a threshold confidence level, allowing the online system to return information from third party accounts having connections to the user's account with at least the threshold confidence level.

Abstract: A method for forming a digital certificate includes receiving contact information associated with the digital certificate. The contact information includes at least a name, a mailing address, and an email address. The method also includes receiving billing information associated with the digital certificate and receiving a Certificate Signing Request (CSR) for the digital certificate. The method further includes receiving a first name for use in forming the digital certificate and receiving a second name for use in forming the digital certificate. Moreover, the method includes receiving an indication of a vendor of web server software, receiving an indication of a service period for the digital certificate, and forming the digital certificate. The first name is stored in a Subject field of the digital certificate and the second name is stored in the SubjectAltName extension of the digital certificate.

Abstract: Embodiments of the present invention relate to systems and methods for determining sets of products which are similar to each other in terms of consumers' wants and needs. Queries are performed on a particular product. Documents relating to the query are received and stored. A dictionary is created from the received documents, whereby the documents, which are text files, are scrubbed of certain data to create a scrubbed text file. Topic modeling is then performed on the cleansed text file. Various methods can be used to perform topic modeling, including, but not limited to, latent semantic analysis, nonnegative matrix factorization, and singular value decomposition.

Abstract: To determine pricing recommendations for goods and service products in a business-to-business environment, a set of transaction data corresponding to a set of products are processed to generate a set of pricing recommendations optimized according to an objective. Furthermore, a set of product segments may be determined, transaction data may be associated with one or more of the product segments and a demand model and associated price elasticity may be formulated for one or more of the product segments based upon the transaction data associated with the segment. Using these formulated price elasticities, pricing recommendations for each product may be determined for each of a set of customers. Using an optimization process, price elasticities are used to determine price dependent entity goals for any combination of products, customers and sets of prices, using a mathematical objective function.

Abstract: Embodiments of the present invention relate to systems and methods for determining sets of products which are similar to each other in terms of consumers' wants and needs. Queries are performed on a particular product. Documents relating to the query are received and stored. A dictionary is created from the received documents, whereby the documents, which are text files, are scrubbed of certain data to create a scrubbed text file. Topic modeling is then performed on the cleansed text file. Various methods can be used to perform topic modeling, including, but not limited to, latent semantic analysis, nonnegative matrix factorization, and singular value decomposition.

Abstract: Methods and apparatus for predicting tire uniformity, preferably a harmonic component of force variation (radial, lateral, or tangential) for a production tire operating at a high speed, and also method and apparatus for manufacturing tires and controlling the manufacturing of tires in response to quality control based on a comparison of a production tire's predicted uniformity versus predetermined criteria. A production tire's predicted tire uniformity is determined by a calculation using a prediction curve with parameters which are determined for the production tire by collecting measurement data for the production tire using a factory floor tire uniformity machine operated at a plurality of intermediate test speeds, and then fitting the prediction curve to the measurement data, preferably using a least squares curve fitting process. Higher speed measurements are optionally given greater weight in the curve fitting process as compared to lower speed measurements.

Abstract: Methods and apparatus for predicting tire uniformity, preferably a harmonic component of force variation (radial, lateral, or tangential) for a production tire operating at a high speed, and also method and apparatus for manufacturing tires and controlling the manufacturing of tires in response to quality control based on a comparison of a production tire's predicted uniformity versus predetermined criteria. A production tire's predicted tire uniformity is determined by a calculation using a prediction curve with parameters which are determined for the production tire by collecting measurement data for the production tire using a factory floor tire uniformity machine operated at a plurality of intermediate test speeds, and then fitting the prediction curve to the measurement data, preferably using a least squares curve fitting process. Higher speed measurements are optionally given greater weight in the curve fitting process as compared to lower speed measurements.