SharePoint 2013: Analytic Processing component

Analytic Processing component: Analytic processing component now the part of search component. ACP Sends the result to the content processing component to be included in the search result. How many times item have been viewed (by default it store last two week items).Search the item based on what is hot, search by most view count. Historical Information like how many times items has been in all time. Example

• What is hot
• Number of times content is viewed
• Popularity
• Hot topics in distance thread
• My previous search
• Popular result

Analyzes the items how users interact with search result events like number of times user search and click the items. Following are the list of event events.

Search Analyses

1. Link and anchor text analysis: Analysis the link and anchor from the document processing & improve recall position of on the search result.
2. Click Distance: it calculates the actual distance and click from the authrative site from a specific item, that helps the in the search relevancy for a particular site. 
3. Search Clicks: people what items actually click and don’t click in search result to improve the search relevancy. 
4. Deep Link: in search result what information about people actually clicked on a search result dynamically calculate what page in a given sub site is consider as an important page. Result display in a search result as an important shortcut link. 
5. Social tags: When query expression matched with the social tags.
6. Social distance: it calculates first and second level colleague, this information used in the people search, the people is closer to you and your organization chart. 
7. Search Reports : The Search Reports analysis aggregates data and stores the data in the Analytic reporting database where it's used to generate these search reports:
1. Number of queries
2. Top queries
3. Abandoned queries
4. No result queries
5. Query rule usage

Usage Analytic: 

1. Usage count: The Usage counts analysis analyzes events, such as viewed or clicked items. The analysis calculates how many times an item is openedoverall, not just from the search result page, but also, for example, when a document is opened from Word or clicked in a SharePoint library. 
2. Recommendation: The Recommendations analysis creates recommendations between items based on how users have interacted with the items on a site. The analysis uses the same event file as Usage counts, but looks for patterns in the usage. The analysis calculates an item-to-item relationship graph and adds the information to the items in the search index.Example: 
1. Amazon “People who purchased this also purchased”
2. Linkedin “People who viewed this profile also viewed”
3. Facebook “Friends who liked this page also liked ”
3. Activity Rank: Activity Rank biased on the activity rank outside of search. The Activity ranking analysis uses the activity tracking of usage events (the event rate) to influence search relevancy. Items that have high usage activity (clicks or views) typically get a higher activity rank score than less popular items.