The constant evolution of software aims at simplifying actions in life. NLP (Natural Language Processing), ML (Machine Learning) and AI (Artificial Intelligence) are sophisticated but still useful approaches to perform text analysis to shape the world of business. The web offers such an amount of data today that it would be impracticable for us to analyze and process it manually. The above mentioned tools automate tasks and save time, with the immediate output of relevant information in consumers` insights.
A keyword extractor is an ML tool that draws keywords and important information from text data. Organizations have automatic access to emails, social media posts, online reviews, survey results, etc.etc., and draw key data about a brand, a product or a service. Extracted data is provided as single or compound words and sentences as well. Such information helps businesses to comprehend what is being talked about in the market, and such details as company names, competitors, phone numbers, locations and email addresses.
You are certainly concerned about your business growth, and then you want to focus on the issues mentioned most frequently in the web. You can either assign your teams the hard and time consuming labor of processing data, or connect a keyword extractor to your customer service desk and output automated summary of data, to identify what consumers are saying, what they like or dislike, their preferences as promoters or detractors.
There is a useful suite of platforms at your service: Wordsfinder Extractor API, Relevant Words Extractor API, Relevant Expressions Extractor API, Keyword Extractor API and Key Chunk Extractor API. In an interesting combination of applications, they perform text analysis to deliver the most accurate information from insights.
You just generate a keyword extraction model from open-source libraries, and find a way to process text data in a simplified way. You merely automate the necessary coding to use those libraries, or use low code models, or no code models, that allow laymen without expertise to perform keyword extraction at a click. This set of APIs defines an efficient mechanism to analyze text with the chance to tailor them to your requirements. They provide ready-to-use extraction models or you can build one yourself. This latter alternative is recommended, as tagging is important to obtain more accurate data for your business.
How To Create A Keyword Extractor
You just sign up to Keyword Extractor API and follow the sequenced steps. First you choose a model as an Extractor or as a Classifier. You select Extractor and import your text data, or just import your data directly from an app with reviews. Next you select the columns you wish to train your keyword extractor with. Then you create your desired tags, on the basis of your needs and interests (e.g. features or issues); the keyword extractor will use them as boxes to classify data.
The next step is to train your model. This is the key for accuracy and efficiency. You just sort words and/or phrases and combine them with your tags. Your model will be trained from the combinations you make, will gain confidence and will begin to predict by itself. It is recommended to tag a considerable number of texts for the model to reach the expected accuracy and confidence.
Finally put your model to the test and see how it works. You can eventually continue to train it if the information you get is not accurate enough. When the model is trained to your satisfaction and your business`s needs, just run it connecting it with the API. You will immediately get instant insights.
Find the relevance of text data. Learn which issues are more often mentioned. Make the most of social media interactions, surveys, emails and judgements…your business will benefit from the decisions you make and the improvements you perform following what the market thinks and feels.