Google has filed for an organic search patent, titled Personalization of placed content ordering in search results, to serve organic search results based on user profiles. It integrates user profiling into natural search ranking.
User profiles are gathered from various search activities such as: past searches, user behavior via tracked links as well as sites visited which display Google ads, computers with Google Desktop Search, Google Wi-fi Connection or Sidebar, and Google Toolbar.
Google generates search results in response to a search query with a listed site which satisfies the query being assigned a query score, QueryScore, in accordance with the search query. This query score is then modulated by the site’s PageRank, to generate a generic score, GenericScore, that is expressed as:
GenericScore=QueryScore*PageRank.
GenericScore does not necessarily provide enough information to rate the site well though. They continue by stating:
This generic score may not appropriately reflect document D’s importance to a particular user U if the user’s interests or preferences are dramatically different from that of the random surfer. The relevance of document D to user U can be accurately characterized by a set of profile ranks, based on the correlation between document D’s content and user U’s term-based profile, herein called the TermScore, the correlation between one or more categories associated with document D and user U’s category-based profile, herein called the CategoryScore, and the correlation between the URL and/or host of document D and user U’s link-based profile, herein called the LinkScore. Therefore, document D may be assigned a personalized rank that is a function of both the document’s generic score and the user profile scores.
Using this system can be combined with personal information to provide more relevant results to the user. They gave an example:
Compared with other types of personal information such as a user’s favorite sports or movies that are often time varying, this personal information is more static and more difficult to infer from the user’s search queries and search results, but may be crucial in correctly interpreting certain queries submitted by the user. For example, if a user submits a query containing “Japanese restaurant”, it is very likely that he may be searching for a local Japanese restaurant for dinner. Without knowing the user’s geographical location, it is hard to order the search results so as to bring to the top those items that are most relevant to the user’s true intention. In certain cases, however, it is possible to infer this information. For example, users often select results associated with a specific region corresponding to where they live.