Graph analytics is used in wide range of applications such a

Graph analytics is used in wide range of applications such as World Wide Web data mining, Overlay-based distributed systems management, e-commerce retailers (e.g., Amazon), Map application (e.g., Google maps, MapQuest), and Social networks (Facebook, Twitter, LinkedIn). It is analysis and extraction of information from large data graphs to make predictions, find patterns and enhance understanding.

What do you think?

Solution

Yes, in today’s date Graph analytics has became a need. The amount of data is huge obtained from social networking websites Twitter, Facebook, Linkedin, e-commerce websites like Amazon, real estate websites. So, due to huge data size, it is not possible to manually look at the data for extracting information. Graph analytics algorithms are used for extracting information from such data.

For example I will talk about few Data mining algorithms which are useful.

1)Apriori algorithm takes a transactional database, containing list of transactions at some stores/ecommerce websites and each transaction contains the list of items purchased together by a user. Apriori Algorithms is used to find the sets of items which are commonly purchased together. So, if a customer purchases a particular item, we can predict “what other items he might be interested in purchasing?”. So, Apriori algorithm can improve advertising methods.

2) On E-commerce websites if we search particular items and did not purchased that item, then we receive emails from the e-commerce website about that item or other items which are similar to our interests. This is achieved using data mining.

Similarly Graph analytics is used in social networking websites as well. There is a feature which shows us the list of people which we may want to connect. This feature is developed based on graph algorithms using the principle that people who are friends of my friend may possibly be friends of mine.

Graph analytics is been used in many other applications in our daily life.