Searching

How Search Engines Work
Search engines, like Bing and Google, receive hundreds of millions of queries daily. Due to the high, these search engines need to be sure they are efficient and respond to each query within seconds, while also providing the user with relevant information that they can use. In order to stay up-to-date with the content on their search engines, these companies “crawl the web” periodically. [1]

When a document is searched, the search engines process their results over an inverted index using a ranking function that gives each document scores based on their relevance to the query. Documents with the highest score will be listed first. On the, the title ,url and snippet (i.e., two or three sentence summary of the document) information is given and displayed for the user. [1]

Semantic Search
Machine learning technologies are often referred to as “semantic technologies.” These semantic technologies can be enhanced to improve searching on the Web, like semantically targeted advertising, topic recognition, etc. Semantic searching is the idea of using, or exploiting metadata to improve searches on documents. “In the case of search engines, it more explicitly refers to embedding metadata in HTML5.” [2]

Timeline of Semantic Web Adoption:
[2]
 * Yahoo! opens : February 2008
 * Bing acquires Powerset: July 2008
 * Google introduces reviews and aggregate reviews using : May 2009
 * Google introduces specifying an image's license using RDFa: August 2009
 * Google encourages webmasters to "help us make the web better" by using rich snippets: October 2009
 * Google announces use of structured data to describe an organization: March 2010
 * Google announces to go international and for recipes: April 2010
 * Facebook announces open graph protocol based on RDFa: April 2010

Semantic Search and Social Media
With the goal of semantic search being to improve search results by tracking a searchers previous queries and understanding contextual relationships between the search and the terms used, semantic search is changing social media.

Formatting on the web is primarily HTML. This is because the user will have a more visually appealing and enhanced experience. So, webpages are formatted for humans to easily read them, but the structure is not as easy for computers to understand the content. Companies, small and large, utilize the semantic web and semantic searching on social platforms: "'Brands want to know what consumers are saying about them. Using text analytics, an increasing number of services are able to analyze a user's grammar usage and determine the meaning behind his or her mention of a brand or product. In some cases, this may simply mean determining if a user is using a positive or negative tone when discussing a product or service. In other more advanced cases, this could mean determining a user's specific intent behind a statement. Viralheat, for example, aims to pinpoint social media users on the cusp of making purchasing decisions. This type of service enables brands to weed out irrelevant social updates and access those with the most potential return.' [5]" "'Monitoring customer sentiment is a bit obvious, but another use for text analytics in the social realm is for monitoring a brand's messaging consistency. Catlin notes that it's important for a brand to 'sound like it has a common voice and a consensus of opinion in how it communicates to the world.' Historically, it's always been a priority for brands to make sure their messaging was consistent and clean — social media is another channel where this is important. Using semantic technologies, brands are now able to analyze what they've said and whether those messages were consistent. That information can then be used to determine future messaging strategies.' [5]"
 * IStock_000025013656XSmall.jpg]Consumer Sentiment Analysis:
 * Messaging consistency:

This book (available online through the link above) reflects on Web Search, edited by Rene Konig and Miriam Rashch. The introduction below describes how search engines (including social networking sites) are dominant part of our lives on the web today. "'In the span of only a few years, search engines such as Google and Bing have become central infrastructure-like elements of the web. Within milliseconds they offer answers to pretty much all of our questions, providing a remarkably effective access point to the ever-growing ocean of information online. As usual for infrastructures, there is a harsh contrast between the importance they have in our daily lives and the attention we pay them. Just as we expect water running from the tap, electricity coming from the plug, and roads to drive on, we take for granted that there are search engines to give us the information we need.' [3]"