Categories: Big DataSemantic Web

ShriGB – A Semantic Financial Search Engine

ShriGB, as the name goes, is about extracting valuable insights (“Shri” – respect) from large/big data (“GB”) . The project is aimed to leverage semantic web & big data technologies to extract meaningful insights from unstructured financial data lying across the web.  The data is mostly present in raw form and is useful to some sections of society although, can be used by different section of people for different reasons.

Lets take a look at following example:

Dabur to set up manufacturing units in Uttaranchal

The above data can mean some of the following:

  1. More jobs are going to be created in Uttaranchal region
  2. This may lead to boost in the real estate business; Anyone planning to get into real estate business can use this news to plan
  3. This may as well be taken up by recruitment consultants to contact Dabur for hiring local talent in Uttaranchal
  4. Additionally, others can use the news to plan their business investments.

However, the data is not currently presented in the form & structure (linked) which can be easily consumed by above mentioned section of society.

This is where ShriGB comes into picture. At present, ShriGB is doing following:

  1. Gathering data from various financial portals from India
  2. Creating ontology/taxonomy on this data
  3. Create structure around the data based on RDF (Resource Description Framework) Triples and store them accordingly
  4. Provide URI to different resources; Take a look at following examples
    • Companies investment information can be retrieved using entity URI such as http://vitalflux.com/investments/entity/<company name>; For example, http://vitalflux.com/investments/entity/infosys
    • Investments in different regions can be retrieved using region URI such as http://vitalflux.com/investments/entity/<region name>; For example, http://vitalflux.com/investments/region/maharashtra
  5. Use Schema.org vocabulary to tag data
  6. Linking data in a structured and meaningful way for easy consumption

 

 

 

 

 

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

Recent Posts

Agentic Reasoning Design Patterns in AI: Examples

In recent years, artificial intelligence (AI) has evolved to include more sophisticated and capable agents,…

1 month ago

LLMs for Adaptive Learning & Personalized Education

Adaptive learning helps in tailoring learning experiences to fit the unique needs of each student.…

1 month ago

Sparse Mixture of Experts (MoE) Models: Examples

With the increasing demand for more powerful machine learning (ML) systems that can handle diverse…

2 months ago

Anxiety Disorder Detection & Machine Learning Techniques

Anxiety is a common mental health condition that affects millions of people around the world.…

2 months ago

Confounder Features & Machine Learning Models: Examples

In machine learning, confounder features or variables can significantly affect the accuracy and validity of…

2 months ago

Credit Card Fraud Detection & Machine Learning

Last updated: 26 Sept, 2024 Credit card fraud detection is a major concern for credit…

2 months ago