Have you heard of Cognitive Search?

Digitalization has revolutionized the way businesses operate. Today, in order to stay competitive, it is highly imperative for organizations to transform themselves. As organizations expand and scale up to greater heights, the need to process and analyze larger amounts of data is also increasing. As per a report by IDC, by 2025, collective data size in the world would surge to a staggering 175 zettabyte.

So, what is cognitive search?

To understand this, let’s roll back a little. Back in the 90s and early 00’s, internet search was largely based on web directories and hyperlinks. These were a collection of websites, sorted and arranged in categories. Remember Yahoo! Directory? It was the company’s first offering in 1994 and was quite popular until web directories started losing their essence owing to internet burst. Web directories couldn’t catch up to increasing internet consumption and also needed manual intervention — which made them obsolete. This is when ‘search engines’ took over. Google Search Engine is by far the most widely used search engine in the world. You type ‘cute cats’ on search bar and there you are — thousands and thousands of resources with cute cats for you!

With technology continually evolving and having to offer us something better, the term ‘cognitive search’ came into existence. Technology has come a long way from traditional key-word based searches. Cognitive search is an advanced version of enterprise search that uses various facets of artificial intelligence such as NLP (Natural Language Processing) and complex algorithms. Cognitive technology is not just limited to search capabilities, it also includes computer vision, machine learning, speech recognition and NLP among others. Forrester defines cognitive search as –

‘A new generation of enterprise search solutions that employ AI technologies such as natural language processing and machine learning to ingest, understand, organize, and query digital content from multiple data sources.’

Why cognitive search?

As per industry reports, a lot of time is spent in searching and locating the right information by employees, having wasted at least 20% of their daily working hours. Issues such as duplication of efforts, missing files, security compromise and reduced collaboration are somethings which we all have faced sometime or the other. Content management today is one of the top priorities of organizations, with 95% of the businesses identifying unstructured data as a major challenge. While majority of the employers have tried offering their employees seamless ways of performing daily operations via Cloud technology, a streamlined way of searching relevant information is still amiss. Cognitive search enables you to extract the exact information that you need from large data sources. It has the ability to understand a query just as humans and offer search results accordingly.

At the heart of cognitive search lies the NLP — Natural Language Processing and Machine Learning, that basically understand and makes sense out of unstructured data in the form of texts, videos and audio files. It involves data extraction, language translation and sentiment analysis. Some of the real-world examples of NLP include:

· Language translation feature on smartphones

· Siri and Alexa speech recognition

· Auto classification of your Google mails into one of these categories — Primary, Social and Promotions

· Auto correct feature on our smart phones

Machine learning is training the systems to learn based on patterns, through algorithms. This helps in improving the relevancy of search results. Some of most widely used algorithms today include:

· Clustering — refers to classifying or categorizing things. This is an unsupervised learning method where references from datasets are drawn. For example, filtering of spam mails.

· Prediction — refers to predicting a value depending on past or current data points. Like, how would be the weather for tomorrow?

· Combinatorics — determining the best combination of choices of paths among a finite set of options. Example — which is shortest route to office or home?

With cognitive search, you can get relevant results from tonnes of diverse and complex data sources. Given the rapid advancements in the field of artificial intelligence, increasing number of companies are foraying into cognitive technologies. Microsoft launched Project Cortex in Nov 2019, that uses advanced AI, offering its users the capability to auto analyse docs, meetings and videos. Quickly following the lead were Amazon’s Kendra and IBM’s Watson Explorer pivoting on indexing and relevant search result capabilities.

The potential for cognitive technologies has just started to unravel and there lies ample opportunities and possibilities for us to see. Every organization in present times is underpinned by data and cognitive search offers such organizations a new generation of search elements. i/o Software is one such brand that is introducing its umbrella solution — ioMoVo to the market. ioMoVo is a data exchange and storage solution also offering digital asset management for one’s personal and business needs.



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