Predictive Software – EmTech 2009

The concept of predictive software was unveiled at EmTech 2009 in New Delhi. Here we show what all situations could this software be of great help

Wednesday, April 01, 2009

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At 5 in the morning, the smart phone is beeping and vibrating its lungs out. A mail from the agency is usually not anticipated at this time unless you're working on something important, something classified and of extremely high value. Being a forensics and security expert, a call from the anti-terrorism squad being run by the government isn't surprising anymore for john. After reaching their HQ, he is briefed by a senior officer. This time it's an email message containing what seems like codes compiled in English language and numerals from a source that is bothering the squad. With more than a decade of experience in data mining and analysis, John is now supposed to make sense out of the mail containing this amalgam of words as the mail poses a potential threat to the state.

This might sound like the storyline of the next version of Die Hard or any other out of the world insanely big budgeted Hollywood flick. But at EmTech 2009 held in New Delhi, Srikanth S. Sampara, chief executive of Tuple Technologies gave something similar as an example where the concept of predictive software can come in handy. When using an appropriate model and technique, predictive software can also help in pointing out possible fraudulent cases, such as in the case of insurance claims, said Sampara when asked for a day to day world implementation. But in a case like this, reliability and success rate play a very important role as a fraudulent application being passed as genuine one for sure would bring many insurance companies on their knees begging for bailouts.

Computer scientists are taking advantage of vast databases and sophisticated modeling techniques to create algorithms that help in making correct predictions of changes in financial markets, business opportunities, traffic patterns and even international conflicts. Dr. Lipika Dey who is a senior scientist at the Innovation Labs of Tata Consultancy Services divided data processing into two categories, structured and unstructured both requiring different modeling techniques and levels of complexity. Different models are being tried and tested in order to extract actionable intelligence from enterprise data.

Dr. Lokendra Shastri who is the General Manager at SET Labs, Infosys said that Languages can be ambiguous. Specially in the web age, where short forms and new words are being formed each day, deriving inferences has become more complex. He gave a few examples of simple sentences which could have more than one meaning in different situations. Dr. Shastri has worked on areas of scalable , parallel models of knowledge representation and inference and showed how these play a significant role in data mining and analysis techniques.

Could a predictive software solution warn us about the ongoing financial crisis? The answer to that was probably 'no.' Adding on to his answer, Suresh Satyamurthy, country director of Autonomy Corporation said predictions and enough warnings couldn't be made by thousands of Wallstreet professionals, plus completely relying on such solutions is not the best thing to do when you have so much at stake. Maybe in future we would have solutions so intelligent that will help us in avoiding such situations.

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