Methods, systems, and media for content ranking using real-time data

Abstract

Methods, systems, and media for content ranking using real-time data are provided. In accordance with some embodiments of the present invention, a method, implemented on a processor, for ranking content is provided. The method can include, among other things: receiving real-time information from a plurality of sources; supplementing the received real-time information with historical information and user influence information; analyzing the supplemented real-time information from the plurality of sources to determine real-time trend information; receiving a plurality of content snippets from a content provider; detecting similarities between each of the plurality of content snippets and the determined real-time trend information; ranking the plurality of content snippets based on the detected similarities; and displaying the ranked plurality of content snippets.

What is claimed is: 
     
         1 . A method for ranking content, the method comprising:
 receiving a request to rank content, wherein the request includes a link to access a plurality of content snippets to be ranked;   receiving real-time information from a plurality of sources;   determining, using a hardware processor, real-time trend information based on the received real-time information;   detecting similarities between each of the plurality of content snippets and the determined real-time trend information;   calculating a similarity score for each of the plurality of content snippets based on the detected similarities with the determined real-time trend information;   ranking the plurality of content snippets based on the calculated similarity score; and   recommending at least one of the plurality of content snippets based on the ranked plurality of content snippets.   
     
     
         2 . The method of  claim 1 , wherein the link to access the plurality of content snippets is a uniform resource locator (URL) of a data feed associated with a content provider. 
     
     
         3 . The method of  claim 2 , wherein the data feed is one of: a Really Simple Syndication (RSS) feed, an Atom feed, an Extensible Markup Language (XML) feed, and data provided in JavaScript Object Notation (JSON) format. 
     
     
         4 . The method of  claim 1 , further comprising supplementing the received real-time information with at least one of: historical information and user influence information. 
     
     
         5 . The method of  claim 4 , wherein the plurality of content snippets are ranked based on the detected similarities with the determined real-time trend information and based on the historical information or the user influence information. 
     
     
         6 . The method of  claim 4 , further comprising generating an index of the determined real-time trend information, wherein a plurality of keywords are extracted from the supplemented real-time information and an association between the plurality of keywords is created to generate the index. 
     
     
         7 . The method of  claim 6 , wherein the similarities between each of the plurality of content snippets and the determined real-time trend information are detected by extracting at least one keyword from each of the plurality of content snippets, calculating a similarity score based on a comparison of the extracted keyword with each trend in the generated index, and aggregating the similarity score for each trend to generate an aggregated similarity score, wherein the plurality of content snippets are ranked based at least in part on the aggregated similarity score. 
     
     
         8 . A system for ranking content, the system comprising:
 a hardware processor that is configured to:
 receive a request to rank content, wherein the request includes a link to access a plurality of content snippets to be ranked; 
 receive real-time information from a plurality of sources; 
 determine real-time trend information based on the received real-time information; 
 detect similarities between each of the plurality of content snippets and the determined real-time trend information; 
 calculate a similarity score for each of the plurality of content snippets based on the detected similarities with the determined real-time trend information; 
 rank the plurality of content snippets based on the calculated similarity score; and 
 recommend at least one of the plurality of content snippets based on the ranked plurality of content snippets. 
   
     
     
         9 . The system of  claim 8 , wherein the link to access the plurality of content snippets is a uniform resource locator (URL) of a data feed associated with a content provider. 
     
     
         10 . The system of  claim 9 , wherein the data feed is one of: a Really Simple Syndication (RSS) feed, an Atom feed, an Extensible Markup Language (XML) feed, and data provided in JavaScript Object Notation (JSON) format. 
     
     
         11 . The system of  claim 8 , wherein the hardware processor is further configured to supplement the received real-time information with at least one of: historical information and user influence information. 
     
     
         12 . The system of  claim 11 , wherein the hardware processor is further configured to rank the plurality of content snippets based on the detected similarities with the determined real-time trend information and based on the historical information or the user influence information. 
     
     
         13 . The system of  claim 11 , wherein the hardware processor is further configured to generate an index of the determined real-time trend information, wherein a plurality of keywords are extracted from the supplemented real-time information and an association between the plurality of keywords is created to generate the index. 
     
     
         14 . The system of  claim 13 , wherein the hardware processor is further configured to detect the similarities between each of the plurality of content snippets and the determined real-time trend information by extracting at least one keyword from each of the plurality of content snippets, calculating a similarity score based on a comparison of the extracted keyword with each trend in the generated index, and aggregating the similarity score for each trend to generate an aggregated similarity score, wherein the plurality of content snippets are ranked based at least in part on the aggregated similarity score. 
     
     
         15 . A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for ranking content, the method comprising:
 receiving a request to rank content, wherein the request includes a link to access a plurality of content snippets to be ranked;   receiving real-time information from a plurality of sources;   determining real-time trend information based on the received real-time information;   detecting similarities between each of the plurality of content snippets and the determined real-time trend information;   calculating a similarity score for each of the plurality of content snippets based on the detected similarities with the determined real-time trend information;   ranking the plurality of content snippets based on the calculated similarity score; and   recommending at least one of the plurality of content snippets based on the ranked plurality of content snippets.   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the link to access the plurality of content snippets is a uniform resource locator (URL) of a data feed associated with a content provider. 
     
     
         17 . The non-transitory computer-readable medium of  claim 16 , wherein the data feed is one of: a Really Simple Syndication (RSS) feed, an Atom feed, an Extensible Markup Language (XML) feed, and data provided in JavaScript Object Notation (JSON) format. 
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein the method further comprises supplementing the received real-time information with at least one of:
 historical information and user influence information.   
     
     
         19 . The non-transitory computer-readable medium of  claim 18 , wherein the method further comprises ranking the plurality of content snippets based on the detected similarities with the determined real-time trend information and based on the historical information or the user influence information. 
     
     
         20 . The non-transitory computer-readable medium of  claim 18 , wherein the method further comprises generating an index of the determined real-time trend information, wherein a plurality of keywords are extracted from the supplemented real-time information and an association between the plurality of keywords is created to generate the index. 
     
     
         21 . The non-transitory computer-readable medium of  claim 20 , wherein the method further comprises detecting the similarities between each of the plurality of content snippets and the determined real-time trend information by extracting at least one keyword from each of the plurality of content snippets, calculating a similarity score based on a comparison of the extracted keyword with each trend in the generated index, and aggregating the similarity score for each trend to generate an aggregated similarity score, wherein the plurality of content snippets are ranked based at least in part on the aggregated similarity score.