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Google’s Knowledge Graph and the Future of Search

Google recently announced their knowledge graph, a project that they hope can one day expose users to relevant results faster than ever before. This graph connects real people places and things, and was harnessed to produce the Kevin Bacon calculation between individuals. In essence, the graph can convert “strings to things”, with access to “500 million people, places, and things” and an indexes “of over 3.5 billion defining attributes and connections between these items” [1]. Users will be able to choose from a variety of distinct responses to a search query – for example, a search for “Queen” could return a profile of the British monarch, as well as the band. An important idea that Google is addressing is the use of data and the evaluation of the links  between it. Pages which contain “microdata” can contribute to the knowledge surrounding a string search term, and these contain, but are not limited to “Reviews, People, Products, Businesses and organizations, Recipes, Events, Music, and Video” [2].

The idea of a knowledge graph connects directly to the concept of evaluating the validity and authority of links and data. By traversing a graph after associating nodes with search terms, this technology will allow add on technologies that can suggest more associated  topics based upon a variety of strings converted things.

[1] http://techcrunch.com/2011/10/03/google-says-13-of-search-ads-are-now-enhanced-launches-new-formats/

[2]http://searchenginewatch.com/article/2175783/Google-Launches-Knowledge-Graph-First-Step-in-Next-Generation-Search

-4.5 Degrees

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