Abstract: An event detection system is configured to access a repository that contains a collection of media content. The media content may for example include images, videos, audio clips, and the like, wherein the media content comprises features that include: tags (e.g., hashtags or other similar mechanisms to label and sort content); captions that comprises one or more words or phrases; continuous numerical values; geolocation data (e.g., geo-hash, check-in data, coordinates); as well as temporal data (e.g., timestamps).

Abstract: An event detection system is configured to access a repository that contains a collection of media content. The media content may for example include images, videos, audio clips, and the like, wherein the media content comprises features that include: tags (e.g., hashtags or other similar mechanisms to label and sort content); captions that comprises one or more words or phrases; continuous numerical values; geolocation data (e.g., geo-hash, check-in data, coordinates); as well as temporal data (e.g., timestamps).

Abstract: An event detection system is configured to access a repository that contains a collection of media content. The media content may for example include images, videos, audio clips, and the like, wherein the media content comprises features that include: tags (e.g., hashtags or other similar mechanisms to label and sort content); captions that comprises one or more words or phrases; continuous numerical values; geolocation data (e.g., geo-hash, check-in data, coordinates); as well as temporal data (e.g., timestamps).

Abstract: An event detection system is configured to access a repository that contains a collection of media content. The media content may for example include images, videos, audio clips, and the like, wherein the media content comprises features that include: tags (e.g., hashtags or other similar mechanisms to label and sort content); captions that comprises one or more words or phrases; continuous numerical values; geolocation data (e.g., geo-hash, check-in data, coordinates); as well as temporal data (e.g., timestamps).

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to a Term Weight Engine that defines a pairing comprising a user profile text section paired with a job post text section. The Term Weight Engine learns a pairing weight indicating an extent that a similarity of text in the pairing predicts a relevance of a respective job posting to a given user profile. The Term Weight Engine learns a global weight for a term(s). The Term Weight Engine calculates a similarity score of the pairing as between a first user profile of a target member account and a first job posting. Based on identifying the term appears in the pairing as between a first user profile of a target member account and a first job posting, the Term Weight Engine applies the global weight to the similarity score to generate a prediction indicating whether the target member account will apply to the first job posting.