When you hear the term “Natural Language Generation," what comes to mind?
For most people, it’s probably something like the automatic text that is generated by a website when you fill out an online form. Maybe you’ve noticed how that text often uses words and phrases that are not exactly what you typed into the form—it is different. Wondering how it happens?
In this post, we’ll discuss natural language generation or NLG, how it works, and how it can be applied to your business to help set you apart from the pack.
So let’s get started!
What is NLG
Natural language generation (NLG) involves the creation of a computer program that can automatically generate text based on digital input. It’s a relatively new field but is already being utilized in many areas of business. However, its significant potential has yet to be fully realized.
There are two main types of NLG: statistical and rule-based.
Statistical approaches use statistical models to generate sentences that are similar to human-written sentences, while rule-based approaches use rules to generate sentences that follow a certain structure.
Statistical approaches can be further broken down into neural network methods and machine learning methods. Neural networks are modeled after human brains, and they’re able to learn from their mistakes as they go along. Machine learning methods have been used for some time in computer science, but recently they’ve become popular for NLG.
Rule-based approaches are also split into two categories: linguistically inspired rules and grammatical rules. Linguistic rules are based on the structure of natural languages, while grammatical rules are based on grammatical structures.
There are two main components of NLG: natural language processing (NLP) and natural language generation (NLG). NLP is the process by which computers can understand human language. This process usually involves converting text into structured data using statistical models, word-spotting algorithms, and rule-based systems. The results of this process are then used in NLG, for creating text based on the structured data produced by NLP.
NLG can be used for many purposes, from creating documents and reports to summarizing information and composing emails.
To create NLG, you first need to create a model that describes the rules for how the system should generate text. The model will take into account various factors like the context of the sentence and its subject matter. Once this model has been created, it can be used to generate new sentences based on what is known about the subject matter.
Natural language generation use cases for business
- Customer Service
Customer service is an industry that has been revolutionized by natural language generation. Now, instead of having to manually reply to hundreds of tickets per day, companies can use NLP to automatically respond to customers with personalized messages. This helps companies save time and money while also improving the customer experience.
- Content Marketing
Content marketing is a great way for businesses to reach new customers, but it can be very time-consuming and expensive if you have to write all of your own content. With NLP, you can create high-quality content in minutes or hours instead of days or months! You can also use NLP to personalize your content so that each person who reads it receives a message that feels tailored just for them.
- Technical Documentation
Technical documentation is another use case for natural language generation: instead of having employees spend hours writing manuals about how your product works (and then spending even more time editing those manuals), you can have NLP write them automatically for you! This will not only save you time and money but also help make sure that all of your documentation is accurate and up-to-date with every change incorporated.
- Email Marketing
One of the best ways to reach customers is through email marketing, but it takes time and effort to execute an effective email campaign—and even more time and effort if your database isn’t up-to-date or accurate! Natural language generation can be used to create emails automatically based on user data from your database, which will save you both time and money while increasing engagement with your customers at the same time!
- Generating Reports
One of the most common uses for NLG is generating reports. This can be done by collecting data from a variety of sources and then using that data to create a report in a human-readable format. For example, if you were running an online clothing store and wanted to generate reports about your sales during Black Friday weekend, you could gather data from your website’s analytics and use NLG to create a report with all the pertinent information about sales. You might want to include things like: how many people visited your website, which items sold most quickly, what time of day had the most traffic, etc.
Limitations of natural language generation
Natural language generation (NLG) has inherent limitations. The first is that NLG cannot creatively produce a document without reference to text from existing documents. This means that NLG is not very useful for creating documents that have never been written before.
Second, NLG cannot understand the context of what it writes. So sentences may be produced that are irrelevant or incomplete, so human editing is required. For example, if you were to ask a natural language generator “What did you do today?", it would likely answer such as: “I ate breakfast at 10:00 this morning." The reason why this happens is that the software lacks context and knowledge about what happened before or after the event being described took place; therefore it cannot produce a more complete sentence (such as “I ate breakfast at 10:00 this morning after taking my dog outside").
Thirdly, effective NLG systems typically require large quantities of data for training models. It is difficult for them to learn complex concepts or recognize patterns within sentences without sufficient data available for training.
Despite its limitations, natural language generation has proven to be a very effective tool for modern organizations to deliver more timely, comprehensive, and personalized service to prospects and customers. NLG has also produced significant results in automating and optimizing business operations.
How to get started
- The first step in implementing natural language generation within your business is to identify the opportunity. Do you want to be able to respond to customer inquiries without having to hire dozens of customer service reps? Would you like your website to answer questions and provide information without requiring human intervention?
- Once you’ve identified the opportunity, then it’s time to decide what kind of solution best suits your needs. Are you looking for rules-based NLG, or do you want something more NLP-based?
- Once decided, it’s time to start looking for a technology partner that can help implement the solution. Your technology partner should be able to help you build a strategy, design a quick, easy way to deploy your NLG solution, train your employees on using it, and troubleshoot any issues that come up during or post-deployment.
Natural language generation has already been shown to be a great tool to automate processes anywhere that text needs to be created and the use of this technology is only becoming more widespread by the day. Today, NLG is powering business through operational task automation, faster and higher volume content creation, and comprehensive marketing campaigns and brand storytelling saving thousands of hours of employee time, in product and service promotion, customer service, and product support. NLG helps increase business revenue while decreasing production costs, thus providing a significant positive impact on the bottom line.
If you have a NLG project in mind or want expert advice on how to deploy NLG in your business, email us at firstname.lastname@example.org. Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with Intellect2TM. IntellectDataTM develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellectdata.com.
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