Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Gartner recently estimated that the market for AI software will be nearly $134.8 billion, with the market growing by 31.1% in next several years. In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation.
Tag: Sentiment Analysis
If you are an avid reader of technical research or industry journals, you probably know about Natural Language Processing or NLP. If you don’t know about it, you certainly use it every day – whether you know it or not! When you search using Google, you are using natural language and that makes it easier for you to develop a question and get an answer. Ask a question and get an answer. It’s that simple!
But, when it comes to analytics, NLP is typically much more restrictive. Talk all you want about machine learning and natural language processing but the boundaries and restrictions placed on these concepts in a typical analytical solution do not make it as easy as business users might like.
Remember that your business team members are also consumers outside the walls of the office and they use and appreciate the ease of Google searches. Here, a consumer might ask, ‘how many ounces in a pound’, or ‘what is the tallest building in the world’, and they get an immediate answer. THAT is what they want in analytics as well and if you don’t give it to them, they are unlikely to adopt the analytical tools you invested in or to achieve the results you wanted for optimizing resources, improving productivity and, most importantly, engaging in fact-based decision making that will improve the business bottom line.
So, what, if anything can one do about the disconnect between the ease of use of analytics and the typical NLP solution? To answer this question, we first need to understand the difference between standard natural language processing in analytics (AKA Dumb NLP) and context-driven searching using natural language processing (AKA Intuitive NLP).
Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP.
Dumb NLP: The use of NLP in analytics provides the basic foundation to get a user into the details of the data and allow them to choose and filter using columns and filters. It recognizes the data in the column or field but not the context. Much like a text to speech solution, it can read, translate and present the data but it has no real understanding of what the data means. Users often get frustrated when they try to use these tools because they have to wade through the choice of columns, click on menus and sift through scripts and when the NLP query results are presented, they may discover that they did not get what they wanted because they omitted or included some inappropriate data.
Intuitive NLP: Context-driven natural language processing allows the user to think of a question and ask that question in a way that supports human thought, and natural communication. Context-driven NLP ‘understands’ and interprets the question and the user intention so, for example, if a user wants to find sales results for a product sold during the ‘Thanksgiving’ season, they do not have to know the date for a particular year or years. They can simply ask the question. ‘How many donuts were sold in Scottsdale, Arizona during Thanksgiving 2019 and 2018? The system will understand the question and interpret it to provide the right information.
Much like your best friend can understand your intent and respond to a question without your being concise or detailed, context-driven NLP can handle the subtleties and the context without the need for excruciating detail and restrictive programming or scripting.
Ask, ‘What was the best day of bakery sales in Tucson Az last year?’, and the system will know that, a) the ‘best day’ means best day of sales for you, that b) bakery sales means all items that fall within the bakery category in your product portfolio, such as cake, brownies, croissants, cookies, bread etc., c) that Az means Arizona and that d) last year was 2019. Just ask the question…and you will get an answer. It’s that simple.
Context-driven, intuitive NLP provides many opportunities to ask questions and handles many concepts, including,
Synonyms, Phonetics and Abbreviations – Enter question and the system will recognize and process information correcting for spelling errors, abbreviations and related words.
Geography, Places and Persons – Enter a question and allow the system to identify a person or place automatically, and give the answer in context of person or geo location.
Time Series – Enter a question and receive results based on absolute time, or on a range or relative time period.
Rank and Polarity – Enter a question and receive results based on a determination of ‘higher’ or ‘lower’ results.
Aggregation – Enter a question to understand results for averages, minimum, maximum, first, last, sum, counts, etc.
Comparison – Explore how sales or other factors compare from one region, year or variable to another.
Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP by offering tools that users will want to leverage and interacting with users in a way that is meaningful to them. Your business users don’t need have to use or understand sophisticated skills to create a query or ask a question. They don’t have to wade through five or ten steps to create a query. With context-driven NLP, users just have to think of a question and type that question and they will get the answers they need.
Make your business more productive, optimize resources, empower your team members and allow them to make confident, fact-based decisions and to solve problems and get the information they need to do their job – without stress or time-consuming training or procedures! THAT is the difference between using ‘dumb’ NLP and using intuitive (context-driven) NLP in analytics.
Smarten is pleased to announce the launch of its Mobile Application for Smarten Augmented Analytics. This native app has a seamless user interface for a great user experience (UX). Smarten Mobile app is available for iOS and Android. Installation is easy.
Smarten announces the recent certification of its Smarten Augmented Analytics Software product by CERT-IN. CERT-IN, or the Indian Computer Emergency Response Team, is an India government-approved organization for upholding information technology (IT) security, and is a well-renowned application security standard, respected within the technology community. It was initiated in 2004 by the Department of Information Technology for implementing the provisions of the 2008 Information Technology Amendment Act. CERT-IN certification is provided by a CERT Empaneled Security Auditor following a detailed security audit to review all components of the organization network including websites, systems, applications, etc. After completion of the testing procedure, the certificate is provided to show that all requirements were met.
This article should serve as a plea on behalf of the average business user!
Business users are business professionals who have expertise in an industry or market arena or perform a function to support the ongoing operation of the business – professionals who may be front line workers on a production line, finance professionals, sales representatives, non-profit office workers, medical researchers, middle managers, regional managers for retail chains, transportation dispatchers or…well, you get the idea. These team members know their job and they do it well. But, they probably don’t have the technical skills to write a SQL query, or to filter out the columns and fields for an analytical search in order to get the results they need to make a decision.
Smarten is pleased to announce the addition of Sentiment Analysis features and functionality to its innovative, augmented analytics solution. Sentiment Analysis enables businesses with easy-to-use tools that provide insight into what customers, stakeholders and others are thinking, thereby allowing business teams to improve products and services.
Small and medium sized businesses (SMEs) are often challenged to satisfy all the roles and responsibilities in the organization and most team members wear more than one hat. That feeling of being overstretched is typical of growing businesses and, in an increasingly competitive market with businesses fighting for skilled resources, it is difficult to meet budget and scheduling goals and get it all done.
