As the data-driven age gives way to an information-driven economy where context is critical to surfacing useful insights from data, taking in relevance feedback from users, especially expert users, will play a major role in driving the benefits. This article explains the concept of a relevance feedback model and why you should care.
Forrester, one of the leading analyst firms, defines Cognitive Search in a recent report¹ as: The new generation of enterprise search that employs AI technologies such as natural language processing and machine learning to ingest, understand, organize, and query digital content from multiple data sources. Here is a shorter version, easy to memorize: Cognitive Search = Search + NLP + AI/ML
Of course, “search” in this equation is not the old keyword search but high-performance search integrating different kinds of analytics. Natural Language Processing (NLP) is not just statistical treatment of languages but comprises deep linguistic and semantic analysis. And AI is not just “sprinkled” on an old search framework but part of an integrated, scalable, end-to-end architecture.
Sinequa has taken part for the 4th consecutive year in Bio IT World Conference & Expo on May 23-25 in Boston. We’ve been delighted to meet with our Biopharma and Life Science customers and partners at the show and share innovative use cases of our solution for the Pharma industry via live demos.
Forces of global competition, narrow margins, higher product development costs, and tenuous exclusivity holds drive organizations to push innovation, seek cost cutting strategies, and go-to-market as quickly as possible. Demands change frequently while regulatory and compliance standards become even more stringent. Organizations must keep up, and the pressure on research and development (R&D) never stops. R&D is the critical driver within the organization, whether within a large aircraft manufacturer or a leading automobile company looking to develop cutting edge products and services or a pharmaceutical company accelerating time-to-market for new drugs or a CPG company reinventing waning products. R&D thrives on information: customer information, expert information, product information, scientific information, market information, and competitive information.
In today’s digital age, leading organizations are looking for better ways to get more out of their data. They are choosing platforms that make every employee more connected, productive, and mobile-without compromising security. As companies adopt Box, providing intuitive information access and advanced search capabilities become increasingly important to end users. Using advanced Natural Language Processing (NLP) and Machine Learning algorithms, Sinequa’s Cognitive Search & Analytics platform enables users to search, analyze and gain valuable insights extracted from Box content repositoriesalong with on-premises enterprise applications, big data and cloud environments.