System, method, and computer program product for generation of local content corpus

Abstract

Various methods for generating a content corpus populated with content related to a particular geographic area are provided herein. One example method comprises, for each document in an initial local content corpus, applying a first set of heuristic filters to the raw content of each document, identifying at least a second term, applying a second set of heuristic filters to the raw content of each document, the second set of heuristic filters associated with the second term, iteratively performing the identification of additional terms and application of an additional set of heuristic filters associated with the additional terms until each identifiable term is extracted, determining a level on a geographic containment hierarchy indicative of a location to which each document from the set of documents is local, and for each place in a gazette, and for each document, determining a set of place in a gazette, and for each document, determining a set of points in polygons indicative of its locality.

1 .- 20 . (canceled) 
     
     
         21 . A computer-implemented method, comprising:
 for each of a plurality geographical spaces of interest, identify a set of local content, the set of location content comprised of online resources and websites identified as locally relevant;   perform content polling, utilizing a web crawler, content polling comprising crawling links from local content, and searching by keyword, and identifying new content;   add new content to a local content corpus, the local content corpus comprising a plurality of documents, each document comprised of raw content;   for each document in the local content corpus, apply a first set of heuristic filters to the raw content of each document;   identify, based on the application of the first set of heuristic filters, at least a second term;   apply a second set of heuristic filters to the raw content of each document, the second set of heuristic filters associated with the second term; and   utilize the second term in subsequent content polling as a new keyword.   
     
     
         22 . The computer-implemented method according to  claim 21 , wherein the iterative performance of the identification of additional terms and the application of the additional set of heuristic filters associated with the additional terms is configured to generate a set of local terms referencing at least people, places, and organizations. 
     
     
         23 . The computer-implemented method according to  claim 21 , further comprising:
 determining a presence of geospatial information within a particular document; and   utilizing the geospatial information in conjunction with particular term frequencies to determine to eliminate the document from the initial local content corpus.   
     
     
         24 . The computer-implemented method according to  claim 21 , further comprising:
 for each place in a gazette, generating an initial set of local terms, generating the initial set of local terms comprising: accessing a document, and calculating an initial weighting for at least a portion of the initial set of local terms; and   creating the initial local content corpus utilizing the initial set of local terms, the initial local content corpus containing documents that are semantically related to each other with respect to the place, the local content corpus configured for providing the system with relevant and unranked documents.   
     
     
         25 . The computer-implemented method according to  claim 21 , further comprising:
 for each place in a gazette, and for each document in the set of documents, determine a set of weightings associated with the terms in the document.   
     
     
         26 . The computer-implemented method according to  claim 21 , wherein the first set of heuristics comprises at least a topological filter with respect to the place. 
     
     
         27 . The computer-implemented method according to  claim 21 , further comprising: determine a level on a place hierarchy indicative of a location to which each document from the set of documents is local. 
     
     
         28 . A computer program product comprising at least one non-transitory computer readable medium storing instructions translatable by one or more server machines to perform:
 for each of a plurality geographical spaces of interest, identify a set of local content, the set of location content comprised of online resources and websites identified as locally relevant;   perform content polling, utilizing a web crawler, content polling comprising crawling links from local content, and searching by keyword, and identifying new content;   add new content to a local content corpus, the local content corpus comprising a plurality of documents, each document comprised of raw content;   for each document in the local content corpus, apply a first set of heuristic filters to the raw content of each document;   identify, based on the application of the first set of heuristic filters, at least a second term;   apply a second set of heuristic filters to the raw content of each document, the second set of heuristic filters associated with the second term; and   utilize the second term in subsequent content polling as a new keyword.   
     
     
         29 . The computer program product according to  claim 28 , wherein the iterative performance of the identification of additional terms and the application of the additional set of heuristic filters associated with the additional terms is configured to generate a set of local terms referencing at least people, places, and organizations. 
     
     
         30 . The computer program product according to  claim 28 , wherein the instructions are further translatable by the one or more server machines to perform:
 determining a presence of geospatial information within a particular document; and   utilizing the geospatial information in conjunction with particular term frequencies to determine to eliminate the document from the initial local content corpus.   
     
     
         31 . The computer program product according to  claim 28 , wherein the instructions are further translatable by the one or more server machines to perform:
 for each place in a gazette, generating the initial set of local terms, generating the initial set of local terms comprising: accessing a document, and calculating an initial weighting for at least a portion of the initial set of local terms; and   creating an initial local content corpus utilizing the initial set of local terms, the initial local content corpus containing documents that are semantically related to each other with respect to the place, the local content corpus configured for providing the system with relevant and unranked documents.   
     
     
         32 . The computer program product according to  claim 28 , wherein the instructions are further translatable by the one or more server machines to perform:
 for each place in a gazette, and for each document in the set of documents, determine a set of weightings associated with the terms in the document.   
     
     
         33 . The computer program product according to  claim 28 , wherein the first set of heuristics comprises at least a topological filter with respect to the place. 
     
     
         34 . The computer program product according to  claim 28 , wherein the instructions are further translatable by the one or more server machines to perform:
 determine a level on a place hierarchy indicative of a location to which each document from the set of documents is local.   
     
     
         35 . A system, comprising:
 one or more server machines; and   at least one non-transitory computer readable medium storing instructions translatable by the one or more server machines to perform:   for each of a plurality geographical spaces of interest, identify a set of local content, the set of location content comprised of online resources and websites identified as locally relevant;   perform content polling, utilizing a web crawler, content polling comprising crawling links from local content, and searching by keyword, and identifying new content;   add new content to a local content corpus, the local content corpus comprising a plurality of documents, each document comprised of raw content;   for each document in the local content corpus, apply a first set of heuristic filters to the raw content of each document;   identify, based on the application of the first set of heuristic filters, at least a second term;   apply a second set of heuristic filters to the raw content of each document, the second set of heuristic filters associated with the second term; and   utilize the second term in subsequent content polling as a new keyword.   
     
     
         36 . The system according to  claim 35 , wherein the iterative performance of the identification of additional terms and the application of the additional set of heuristic filters associated with the additional terms is configured to generate a set of local terms referencing at least people, places, and organizations. 
     
     
         37 . The system according to  claim 35 , wherein the instructions are further translatable by the one or more server machines to perform:
 determining a presence of geospatial information within a particular document; and   utilizing the geospatial information in conjunction with particular term frequencies to determine to eliminate the document from an initial local content corpus.   
     
     
         38 . The system according to  claim 35 , wherein the instructions are further translatable by the one or more server machines to perform:
 for each place in a gazette, generating the initial set of local terms, generating the initial set of local terms comprising: accessing a document, and calculating an initial weighting for at least a portion of the initial set of local terms; and   creating the initial local content corpus utilizing the initial set of local terms, the initial local content corpus containing documents that are semantically related to each other with respect to the place, the local content corpus configured for providing the system with relevant and unranked documents.   
     
     
         39 . The system according to  claim 35 , wherein the instructions are further translatable by the one or more server machines to perform:
 for each place in a gazette, and for each document in the set of documents, determine a set of weightings associated with the terms in the document.   
     
     
         40 . The system according to  claim 35 , wherein the first set of heuristics comprises at least a topological filter with respect to the place.