How Can You Use NLP In Data Mining

How Can You Use NLP In Data Mining

Introduction to NLP

NLP also known as natural language processing is a branch of artificial intelligence, or machine learning with the help of which the system, computer, or apps can recognize texts, and speeches by seeking the pattern in the text. The other definition for NLP is how the computer can read the natural language in written or speech form and what kind of data can be obtained from the source that has been given to the system. It is a very complex field of computer sciences as the rules that have been made are very complex and very difficult for the system or the model to understand. So, a proper programming language is required, in order to make the system intelligent so that it can understand what type of initial input has been provided to it. In the same way when we want to train the model which can understand the natural languages in the form of natural text and speech a lot of explanations are needed to enter the system so that there is no ambiguity remain left while working on the system. There are different uses of NLP in our daily life which we have observed. These are email filtering, as by the wording inside the email the AI agent can tell the user which email is of great importance and which email has a scam. The other important thing that we have used in our daily lives is autocorrect already installed on our mobile phones. With the help of this, the keypad itself predicts the next possible word or the sentences all of these are primarily based on NLP.

 

Data Mining

While working with artificial intelligence, machine learning, and machine vision. There are a lot of possibilities to have data anomalies, different patterns, and correlations as well. In order to find these factors in a large data set data mining technique has been used. In easier definitions of data mining, it is basically a technique with the help of which we can analyze a data set. The data has been searched, analyzed, and finding the correlation between the different points of a single data set. In this way, the model, system, or machine can itself predict the probable outcome and hence make things easy for the system. Data mining is a powerful tool with the help of which the useful information from discrete data can be obtained, analyzed, and used for our work to get useful outputs. There are different advantages of data mining like it predicts the danger, improves consumer satisfaction and reduces cost as well. Market segmentation, customer acquisition, and targeted customers can also be achieved using this technology. There are two main types of data mining one is predictive data mining and the other one is descriptive data mining. In predictive, the possible future of the model has been defined and it includes regression analysis, prediction analysis, and time series analysis. In the same way, descriptive analysis is the one that gives the turnout and the real-time information of the data that has already been uploaded as a data set. The descriptive analysis has include clustering, summarization, and association rule analysis. 

 

Data Mining and NLP 

While working in data mining we need some algorithms so that we can make the machine able to read the text, follows the pattern, and interpret through the environment which kind of data has been given to the system. This can be possible by using the NLP technique, as with the help of NLP the system can interpret the situation by following the pattern and reading the text and in the end understanding most of the data that has been available in the raw or natural form. Areas of Text MiningWhile working with NLP in DATA mining there are basically different steps involved the first one is a statistical analysis of the data in order to find the correlation between the data, to find the pattern. The second step is artificial intelligence which is the core of this scenario. With the help of AI, the correlation can be observed, data interpolation can be done and finally, machine learning agents are applied to continuously improve the interpretation of the data by giving feedback to the system in various forms. There are different types of mining as well one is text mining in which only text has been obtained from the raw data or in the form of natural language. In the same way, the other one is data mining. Data mining is more or less the same as text mining but in a large form. With the help of data mining, we can extract a complete data set. In data mining, the same pattern is followed as intext mining using NLP in order to extract some useful information from the text which is written in the natural form. 

 

Application of Data Mining and NLP 

Data mining and NLP are the correlated subfields of machine learning and artificial intelligence. There are various applications in which these are used in order to to get better results and output. Some of the applications are as follows. 

  1. Email filtering is the most common application in NLP.
  2. Google search results also use NLP and data mining having a record of the user interests and all that. 
  3. Translation and predictive text also include the algorithms of NLP.
  4. Even the text analytics and smart assistance features in our smart gadgets use NLP. 

Conclusion

In this era of digital transformation and artificial intelligence, more NLP developments will further revolutionize businesses and processes, with surprises around every corner. Thanks to the actionable customer insights offered by NLP and the automation of numerous processes, businesses are assisted in making decisions that provide observable outcomes, and business efficiency is further increased. With the help of Algoscale’s skilled team of professionals, you can get your hands on the most recent NLP advancements and utilize the potential of AI for your company.

 

Also Read: Top 7 NLP Trends Transforming E-commerce and Online Retail in 2021

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