Through the years, technology has become more a part of how we do business, thanks to recent developments providing more practical applications in a number of industries. Regardless of what business you're running, it can't be denied that online tools are a big help when it comes to connecting with and understanding your audience.
Natural Language Processing (NLP) is a revolution in computing technology that allows computers to understand and interpret human language. It helps humans and computers communicate through analysis of language-based data at high speeds-more than what is possible for humans.
NLP helps computers communicate with humans in their own language and scales other language-related tasks. For example, NLP makes it possible for computers to read text, hear speech, interpret it, measure sentiment and determine which parts are important. It also helps provide structure to big data, which is an extremely massive, complex, and unstructured data source.
It's not a new technology by any means, but the rise of big data has renewed focus on NLP's practical applications in business and education. You might have used it several times already without realizing it since many businesses today rely on NLP to understand what their customers actually say.
Below we show the digital platforms that use NLP to enhance their product or service and how it helps them get a better understanding of their customers.
If you haven't heard of BERT, it's Google's neural network-based technique for NLP and one of the tech giant's biggest leaps forward in the history of Search. BERT stands for Bidirectional Encoder Representations from Transformers and it has helped Google jump from merely interpreting the words people use but also the context under which they are used. By helping Google grasp the subtle nuances of language, NLP allows search algorithms to understand longer, more conversational queries, including those that use prepositions that alter the context significantly.
Google's use of NLP is apparent in its autocomplete feature, wherein the algorithm predicts words or queries as a user types. This makes it easier for mobile users, on which it can be hard to complete queries using a small screen. Google is also adamant that its algorithm presents "predictions," not "suggestions," and further clarifies that the objective of autocomplete is to help predict or complete a search intended by a user instead of suggesting new types of searches.
Google autocomplete predictions rely on the common and trending searches related to what a user intends to search for. Depending on what characters or words a user types into the search bar, Google autocomplete predictions will change. However, Google also removes some predictions that go against their policies, including sexually explicit predictions, hateful speech, predictions related to violence, and dangerous and harmful activity predictions.
Salesforce
Salesforce is another company that uses NLP to handle large amounts of data. Similar to Google and a number of other business sites, Salesforce has its own search engine that can be used to search for certain pages or topics within their website. When searching a function, topic, or product feature, you don't need to enter the whole term, and often, those who are searching aren't familiar with the whole term. The search autocomplete feature in Salesforce allows users to do searches quicker with predictions so they don't have to explore outside the website or platform.
Users can also use a picklist when they enable autocomplete on standard addresses. With this feature enabled, users don't need to enter full addresses; once they enter text on standard address fields, they will be able to see possible matching addresses in a picklist.
Grammarly
Grammarly uses NLP to provide writing enhancement services through its mobile app and browser-based platform. Grammarly combines machine learning with NLP to analyze and interpret the many levels of human language. The company's AI system is sophisticated enough to process data from individual words or characters to grammatical structures of sentences and even full paragraphs.
Grammarly has collected and organized a large collection of sentences that have been labeled so that AI algorithms can better understand them. In other words, Grammarly's AI learns from a database of sentences that have mistakes and those that follow grammatical rules and best practices so that it can fix errors in writing. It also helps detect what linguists refer to as discourse coherence, a typical occurrence wherein a person writes according to natural thought patterns, which often don't follow a logical progression.
Facebook is a company that handles huge amounts of data, and the company interprets that collection of data with the help of NLP to better understand and extract meaningful information. Although Facebook Messenger chatbots use NLP to personalize ads, the company has extended the functionality so that the chatbots can interpret what users type and interact with them.
Facebook Messenger is one of the latest ways that businesses can connect to customers through social media. NLP makes it possible to extend the functionality of these bots so that they're not simply advertising a product or service, but can actually interact with customers and provide a unique experience. Facebook uses this functionality to identify intent, automate replies, collect audience data, and route conversations to a live chat when necessary.
NLP is gradually becoming a necessity when it comes to collecting and understanding big data. In 2020, it has become a trend that shouldn't be overlooked, especially in this always-online, always-connected landscape. The technology available today has made the development of AI-based systems easier, and companies have been taking advantage of it to move their businesses forward. It's also possible to train an AI system to operate the way you like; there are existing platforms online that make this possible.
Even if a company's existing systems don't currently support AI-based systems, there are ways to make AI adapt to current business needs or create an AI-based system that integrates with existing systems and platforms. As businesses race to keep their business models "future-proof," NLP, and AI in general, shows promise as the platform that will help make all this possible.
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