Poshmark, Inc.

Kaboodle, Inc.

Glasspoint Solar, Inc.

Manish Chandra

Peter Emery Von Behrens

John Setel O'Donnell

Chiaki Treynor

Dylan Miller Fairbanks

Gautam Michael Golwala

Chetan Pungaliya

Keiron McCammon

Tracy Sun

Hayden Graham Burvill

Nghia Bui

LyAnn Chhay

Thomas Owlett

Adam Farver

Users are matched to items and recommended friends in a social merchandising system. During registration, a user profile is created for a user among a plurality of users in the peer-to-peer marketplace. To calculate a compatibility score, a social genome is determined for the user based on social networking characteristics associated with the user. Also, a merchandise genome is determined for the user based on item characteristics associated with the user. Results are organized into a feed for the user based on the compatibility score and time. Feeds display items of friends, or as influenced by social connections and interactions.

Social merchandising system

Separators and mixers for delivering controlled-quality solar-generated steam over long distances for enhanced oil recovery, and associated systems and methods. A representative method includes heating water to steam at a solar field, separating a liquid fraction from the steam, directing the steam toward a target steam user via a first, steam conduit, and directing the liquid fraction toward the target steam user in parallel with the steam via second, liquid fraction conduit. The method can further include mixing the liquid fraction and the steam before delivering the combined liquid fraction and steam to the target user.

Separators and mixers for delivering controlled-quality solar-generated steam over long distances for enhanced oil recovery, and associated systems and methods

A digital item tracking system drives e-commerce with an order state that is determined based on processing events, shipping events and payment events. When a transaction occurs in a peer-to-peer marketplace the order state is updated as events occur through the point that an order is accepted by a buyer. The order can also cause an exception in which reverse digital item tracking is needed.

Using digital item tracking to drive e-commerce

Virtual shopping parties on a peer-to-peer marketplace are facilitated. A virtual party initiated is reserved by a user of the peer-to-peer marketplace. The virtual party comprises a specific set of items available to a specific set of users during a specific time span. A theme is set for the virtual shopping party dictating parameters for whether an item can be added to the virtual shopping party. The theme also dictates parameters for who can add an item to the virtual shopping party. Invitations are sent for the virtual shopping party to the specific set of users, based on the theme. A customized feed is then presented to each of the set of users that join the virtual shopping party.

Real-time user generated virtual shopping parties

A digital image manager classifies digital images such as digital photographs for efficient retrieval. The digital image manager assigns a when value, a where value, a who value and a why value to digital images. Much of the value assignment process is automated to make digital image management easy for the user. The digital image manager classifies the digital images according to the assigned property values. The user subsequently enter search requests for digital images meeting desired criteria. The digital image manager uses the assigned values to locate and retrieve digital images that satisfy the user's request.

Classification and retrieval of digital photo assets

An extraction manager extracts information from formatted input. The input is annotated with presentation information, and parsed into a set of elements comprising a canonical representation thereof. An information analyzer analyzes the elements in order to glean additional information. An entity extractor determines entities to extract from the input. The entity extractor analyzes elements according to specific entities to be extracted, and creates entity specific observations for analyzed elements. These observations comprise possible values for the relevant entities. A heuristics processor maintains a collection of entity specific heuristics, each comprising a test to help determine the suitability of data as a value for the corresponding entity. The heuristics processor selects heuristics for the entities to be extracted, and tests observations for these entities against the selected heuristics. Responsive to this testing, ordered possible values for entities to extract are determined.

Extracting information from formatted sources

An attribute manager extracts attribute values from formatted data. The attribute manager maintains information concerning a plurality of attributes, such as matching names and values for attributes. Formatted data is parsed into a plurality of elements comprising a canonical representation of the data, independent of the data format. The formatted data can be, for example, a web page, a portable document format document or a word processor document. The attribute manager scans the elements for occurrences of attribute values. Based upon value occurrence distribution and frequency within the data, and maintained information concerning attributes, the attribute manager infers occurrence of specific attributes in the formatted data and assigns the most appropriate occurring values to the specific attributes. In some embodiments, the attribute manager stores attributes and their assigned values, and uses this information to automatically prepare summaries of input data.

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Fremont, CA, United States of America

Manish Chandra