Cognitive Search: Taking Cognitive Computing to the Next Level

By: Esther Shein| - Leave a comment

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Keyword search is becoming obsolete as a new subset of cognitive computing emerges: cognitive search technology. This innovation makes search more intelligent by delivering the most relevant information to natural-language queries within large data sets.

Gone are the days of the traditional search box with a simple list of results, according to Forrester. Cognitive search technology used within applications will help employees and customers gain the most contextually relevant information when they need it.

Why Cognitive Search Is Needed

Corporate search platforms are no longer sufficient to handle multiple databases with different documentation formats. By the time data is captured, cleansed and tagged, it can lose relevancy. The labor simply can’t match the frequent changes of the customer, market and business activity.

Enterprise IT technology has advanced in recent years, whether it’s the use of big data analytics or cognitive platforms that offer timely insights. Cognitive search patterns empower organizations to effectively understand and use data — or unwieldy data types — in their decision-making.

How the Platforms Work

Cognitive search platforms are also referred to as insight engines. These systems interact with users in a more intuitive way by gaining greater experience with data and user behavior, writes Laurent Fanichet in Search Technologies. They find and merge information related to a topic regardless of origin or format. This advancement is becoming increasingly important as the amount of data that both humans and machines generate grows at an exponential rate.

Businesses want to find out what they don’t know. And while seeking relevant information, they don’t want to be bombarded with an avalanche of results. This is where traditional systems fail.

The information-gathering process can be aided by cognitive tools that search on a concept level as opposed to keywords, writes Sue Feldman, CEO of Synthexis. Cognitive systems, she notes, are very good at uncovering patterns and surprises, and one of their key differentiators is context.

Providing Value Across Industries

Cognitive systems are applicable for use in most industries. In health care, for example, if an individual has a disease, there are standard treatment protocols — regardless of race, sex or age. With a cognitive platform, that person can be matched as a query against information on the disease and side effects from applicable drugs and clinical trials, says Feldman. The system might suggest two or three different treatments, and now there’s another type of context.

One IBM client, a global electric company, found that both customers and employees were frustrated by poor search capabilities in its internal and external websites. The problem was rooted in the fact that the existing search platform lacked flexibility. The company deployed a cognitive-enabled platform to interpret data in different formats across the company’s data repositories. In doing so, it realized more intelligent search functionality and gained a broader view of information in a shorter time frame, thus increasing productivity.

Cognitive systems go beyond simply searching and retrieving results. By incorporating advanced analytics, natural language processing and machine learning techniques, they can help organizations glean insights hidden within their data and win in the digital era by finding the shortest path to the most optimal result.

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About The Author

Esther Shein

Freelance Writer

Esther Shein is a freelance writer and editor specializing in technology, business and education. Her work has appeared in several online and print publications, including Inc., Computerworld, NetworkComputing, InformationWeek, BYTE, CIO, CMO.com and The Boston Globe. She has written thought leadership whitepapers, customer case studies and marketing materials in addition to news and feature articles. Prior to going freelance she was the editor-in-chief of Datamation, an online enterprise technology magazine. She was also a senior writer at eWeek (formerly PC Week) and worked at The Associated Press.

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