Apparatus, System And Method For A Brand Affinity Engine Using Positive And Negative Mentions And Indexing
An apparatus, system and method of implementing a computerized brand affinity engine. The apparatus, system and method include at least a plurality of computerized access points having accessible thereto a plurality of sites mentioning at least one sponsor, a categorized, hierarchical database of keywords, wherein at least the keywords falling in at least one category of the hierarchy correspond to a sponsor category of the at least one sponsor, and a tracker, wherein the tracker tracks positive ones of the mentions of the at least one sponsor on ones of the plurality of sites and negative ones of the mentions of the at least one sponsor on ones of the plurality of sites, in accordance with positive and negative keywords of the categorized, hierarchical database in the sponsor category, and wherein the tracker issues an rating with regard to the at least one sponsor in accordance with the positive ones and the negative ones of the mentions. An assessment of optimal sponsors for particular markets and/or in particular geographies that additionally increases sponsorship opportunities in particular markets and/or in particular geographies is thereby provided.
1 . A search engine for performing a search for a keyword, comprising:
at least one result responsive to said at least one search created based on at least one RSS feed;
at least one database comprising a plurality of terms by category, wherein at least one of the categories includes the keyword and relational ones of the plurality of terms to the keyword;
a heuristic engine comprising a plurality of rules, wherein said heuristic engine, when executed by at least one computing processor, applies said plurality of rules, in accordance with the relational ones of the plurality of terms, to a networked site to assess the keyword as a primary subject of the RSS feed.
2 . The search engine of claim 1 , wherein the plurality of rules comprises a presence of at least two of the relational ones of plurality of terms proximate to the keyword on the networked site.
3 . The search engine of claim 1 , wherein the plurality of rules comprises a distance of at least two of the relational ones of the plurality of terms from the keyword on the networked site.
4 . The search engine of claim 1 , wherein the plurality of rules comprises a distance of at least two of the relational ones of the plurality of terms and the keyword from a visual center of the networked site.
5 . The search engine of claim 1 , wherein the plurality of rules comprises a distance of at least two of the relational ones of the plurality of terms and the keyword from a visual edge of the networked site.
6 . The search engine of claim 1 , wherein the networked site comprises one of an RSS feed and an internet page.
7 . The search engine of claim 1 , wherein the keyword is indicative of a person.
8 . The search engine of claim 7 , wherein at least one of the relational ones of the plurality of terms comprises a nickname for the person.
9 . The search engine of claim 7 , wherein the person comprises an athlete.
10 . The search engine of claim 1 , wherein the keyword is indicative of a movie.
11 . The search engine of claim 1 , wherein the keyword comprises at least one of a television show, a song, an artist, and an actor.
12 . The search engine of claim 1 , wherein the keyword comprises a good for sale.
13 . The search engine of claim 1 , wherein the keyword comprises a service for sale.
14 . The search engine of claim 1 , further comprising a ratings engine, wherein, upon assessment of the primary subject by said heuristic engine, said ratings engine rates a use of the keyword on the networked site.
15 . The search engine of claim 1 , wherein the relation ones are hierarchical with respect to the keyword.
16 . The search engine of claim 15 , wherein multiple levels of the hierarchy are required by said heuristic engine for the assessment as the primary subject of the networked site.
17 . The search engine of claim 1 , wherein said heuristic engine comprises a learning engine.
18 . A method for assessing a keyword as a primary subject of at least one RSS feed, comprising:
accepting a search input seeking the keyword on ones of the RSS feeds;
locating at least one result responsive to said accepting;
comparing the result with at least known terms associated with the keyword, known distances of the known terms from the keyword, and known locations of the keyword on the feed; and
assessing that the keyword is the primary subject of the feed in accordance with said comparing.
19 . The method of claim 18 , wherein said accepting comprises providing an Internet search engine.
20 . The method of claim 18 , wherein the known terms are hierarchical in the association with the keyword.