Hipmunk Inc.

Zohaib Ahmed

Adam Julian Goldstein

Eric Palm

Gregory Millam

Alex Quintana

Navin Lal

Zak Lee

Richard Shaffer

Example embodiments provide a system and method for inferring preferences from message metadata and conversations. A networked system receives, over a network, a communication that is a part of a conversation involving one or more users, whereby the networked system is a participant in the conversation. The networked system analyzes the communication including inferring a preference of a user among the one or more users based on metadata in the communication. The networked system triggers a search process based in part on the inferred preference. The networked system then generates and transmits to the user a customized response comprising results of the search process.

Inferring preferences from message metadata and conversations

A machine is configured to access a search phrase or other communicated phrase and deconstruct the accessed phrase into multiple sub-phrases. The machine performs an analysis of n-grams that occur within the sub-phrases, generates a set of potentially different sub-phrases from the n-grams, and selects which data source among multiple available video sources should be accessed for each generated sub-phrase in the generated set. For example, the machine may allocate each generated sub-phrase to a corresponding data source and cause the corresponding data source to execute a query based on its corresponding sub-phrase. Thus, the machine chooses from which data source to obtain partial search results that correspond to each sub-phrase generated based on the analyzed n-grams in the accessed phrase.

Search deconstruction, reconstruction, and allocation

Example embodiments provide a system and method for analyzing conversations and determining whether to participate with a response. A networked system receives, over a network, a communication that is a part of a conversation involving one or more users, whereby the networked system is a participant in the conversation. The networked system analyzes the communication including parsing key terms from the communication. The networked system then identifies a sentiment of a user among the one or more users based on the parsed key terms. Based on the identified sentiment, the networked system determines whether to respond to the communication. In response to a determination to respond, the networked system generates a customized response and transmits the customized response, over the network, to a device of the user. The customized response may comprise questions or a set of options related to the conversation.

Automatic conversation analysis and participation

A machine is configured to perform an example method that causes the machine to parse sub-phrases within a phrase, recognize that a sub-phrase has or can have a geographically specific meaning, and notify a user that the sub-phrase is being processed using the geographically specific meaning. For example, supposing a user has communicated a phrase, the machine builds sub-phrases from the n-grams of the phrase and detects that an n-gram has a geographically specific meaning, thus disambiguating the n-gram. This disambiguation is performed using one or more geographically specific databases of n-grams. The machine determines that a geographical location is relevant to the n-gram, selects a specialized search procedure for the n-gram, and obtains search results using the selected specialized search procedure. The machine may also notify the user that the n-gram or a sub-phrase in which the n-gram appears is being processed using the geographically specific meaning.

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San Francisco, CA, United States of America

Zohaib Ahmed