Facebook, Inc.

Airbnb, Inc.

Trooly Inc.

Nilesh Nandan Dalvi

Marian Gelu Olteanu

Sarabjit Singh Baveja

Anish Das Sarma

Manish Raghavan

Systems and methods are provided for, are provided for analyzing each of a plurality of documents related to a person to identify content attributes that occur in a dictionary for behavior or personality traits, calculating an initial score for each behavior and personality trait related to the identified content attributes, calculating trait metrics for each behavior or personality trait by combining initial scores for each behavior or personality trait, providing the trait metrics as input to a rule based scoring and machine learning system, obtaining, from the rule based scoring and machine learning system, a trustworthiness score of the person output from the rule based scoring and machine learning system, receiving an indication that a second person trusts the person, creating a relationship between the second person and the person, and adjusting the trustworthiness score of the person based on, at least, a trustworthiness score of the second person.

Determining trustworthiness and compatibility of a person

A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.

Identifying entries in a location store associated with a common physical location

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying documents related to a person, deriving behavior and personality trait metrics from analyzing the documents for information relevant to assessing behavior and personality of the person, and determine a trustworthiness score or compatibility score of the person based on the behavior and personality trait metrics using a scoring system.

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Sunnyale, CA, United States of America

Nilesh Nandan Dalvi