Graph Search is a natural language search engine introduced by Facebook in 2013 that aims to answer user queries with relevant information rather than just returning links. It uses a graph database model where entities like users, pages, posts are represented as nodes and their connections as edges. This allows it to understand relationships between entities and power semantic searches. The architecture includes components for entity recognition, semantic parsing, and ranking results based on their relevance to the query using algorithms like N-shortest path and EdgeRank.

1. Graph Search

2. Outline
Introduction to Graph Search
Traditional Search Engine
Graph Search Concept
Natural Language Search
Architecture of Natural Language Interface
Ranking Search Results

3. What is Graph Search ?
• Graph Search is a semantic search engine introduced by
Facebook in March 2013.
• It is designed to give answers to user natural language queries
rather than a list of links.
• Can be used for,
– Find more of the people, places and things you’re looking for.
– Discover new connections based on what others have shared with you
on Facebook.

4. • The Graph Search engine is built upon highly structured data
in the form of a graph, representing hundreds of types of
nodes and thousands of types of edges.
• Facebook's technology for finding people and things that are
socially connected.
What is Graph Search ?

5. Traditional Search Engine [PPS]
• Search using Keywords.
• Adding Typeahead features.
• Nearby Tagging within Posts.
• Location Tagging of photos and Post
• But, keyword-based system has not been the best choice.
• For example, “friends Facebook” can mean “friends on
Facebook,” “friends who work at Facebook Inc.,” or “friends
who like Facebook the Page.”.

6. Graph Search Concept
• The Facebook graph is the collection of entities and their
relationships on Facebook.
• Entities are the nodes and the relationships are the edges.
• Every user, page, place, photo, post, etc. are nodes in the
graph.
• Edges between nodes represent friendships, check-ins, tags,
relationships, ownership, attributes, etc.

7. Nodes and Edges

8. Designing a Graph Search System
PPS and Typeahead
• Search entities based on their metadata.
• Using entity name (title).
Graph Search
• Extended capabilities to search based on the
relationship between entities.
• Search over the edges between the corresponding
nodes, Using natural language as input for queries.

9. Natural Language Search
Entity recognition and resolution
Lexical analysis
Semantic parsing

10. Architecture of Natural Language Interface

11. Ranking Search Results
• Graph Search uses a variation of the N-shortest path algorithm, an
extension of Dijkstra’s algorithm, to solve the problem of finding the top K
best parse trees.
• “EdgeRank” is the
name commonly
given to the
algorithm that
Facebook uses to
determine what
articles should be
displayed in a user's
News Feed.

12. Message From Graph Search Developers

13. References
• http://whatisgraphsearch.com/
• https://www.facebook.com/notes/facebook-
engineering/
• http://searchengineland.com/
• https://www.facebook.com/about/graphsearch/privacy
• http://www.socialmediaexaminer.com/facebook-
graph-search-review/

14. Presented by :
Chaitali Patel
Thank You..!!