Leveraging Search Algorithms for Smarter E-Commerce

Barbara Starr of Search Engine Land recently wrote, "Innovation velocity in the search world is causing knowledge graphs to become increasingly sophisticated and ubiquitous. In light of that, it is imperative that semantic Web groups and SEO groups maintain a frequent and open communication. The SEO of the future will need to have a strong understanding of how knowledge graphs work — as well as a solid grasp of semantic Web markup — in order to leverage this information for search marketing campaigns. On May 12, 2012, Google launched their knowledge graph, discussing it in a post entitled, Introducing the Knowledge Graph: things, not strings. The title alludes to Google’s continued evolution from a system that understands search queries as groups of keywords ('strings') to one that understands them as references to real entities/concepts/objects ('things')."

She continues, "There are many mechanisms that could potentially be used for mapping search strings to entity results in the knowledge graph, but that is a subject in and of itself. Part of the point of the migration from 'strings' to 'things,' or the semantic search approach, is to make 'things' findable. Much of the information contained in Google’s knowledge graph was originally from dbpedia (the 'graph based' or 'linked data' version of Wikipedia) and from freebase (a consequence of Google’s acquisition of metaweb). I have cited the diagram below, as have others in many cases. As an example of this, let’s look at PubMed, a free database accessing the MEDLine database of life sciences and biomedical topics. PubMed exists within dbpedia’s linked open data diagram below."

Read more and see the example here.

Image: Courtesy Google