Keyword extraction process with Natural Language Processing

September 13, 2022

The first thing you do when you get up in the morning is open your phone and check your messages. Your mind has been conditioned to avoid WhatsApp communications from individuals and groups you dislike. The message's importance is determined solely by the keywords of persons and group names. 

The same behavior can be replicated via machine learning. In Natural Language Processing  (NLP), this is referred to as keyword extraction. Reading articles or news will therefore be influenced by extracted keywords such as data science, machine learning, artificial intelligence, and so on. Not only does the keyword extraction technique separate the content, but it also saves time on social networking sites. You can decide whether to read the post or the comments depending on their keywords.

In this blog, we will be briefing you on what keyword extraction is, why is it important, how can you do it through NLP, and will discuss its advantages through the end of the blog. 

What is Keyword Extraction

Keyword extraction is a technique that is widely used to extract important information from a sequence of paragraphs or texts. Keyword extraction is a way of extracting the most relevant words and phrases from text input that is automated. It is a text analysis method that extracts the most essential words and expressions from a page automatically. It aids in summarizing the content of a work and identifying major subjects being tackled.

Machine learning artificial intelligence (AI) and natural language processing (NLP) is used in keyword extraction to break down human language so that it can be interpreted and evaluated by machines. It is used to extract keywords from a wide range of material, including conventional documents and business reports, social media comments, internet forums and reviews, news items, and more.

Why is keyword Extraction Important

With keyword extraction, you may quickly locate the most essential terms and phrases in large datasets. And these terms and phrases can provide useful insights into the themes your clients are discussing. Given that more than 80% of the data we generate every day is unstructured - that is, it is not organised in a specified fashion, making it exceedingly difficult to evaluate and process - businesses require automated keyword extraction to help them process and analyse consumer data more efficiently.

Assume you wish to examine thousands of online product reviews. Keyword extraction allows you to quickly filter through a large amount of data and extract the words that best describe each review. As a result, you can easily and immediately identify what your customers are talking about the most, saving your employees hours and hours of manual processing.

Whatever your industry, keyword extraction tools are essential for automatically indexing data, summarising a text, or creating tag clouds with the most representative keywords.

How to Extract Keywords using Natural Language Processing

Natural Language Processing (NLP) is the best option to gain a high-level understanding of the overall tenor of the dataset, then use that understanding to identify more focused lines of inquiry—either to apply to the data itself or to guide the related study. A wide range of free Python NLP modules provides some reasonably simple-to-implement algorithms for uncovering significant aspects of huge datasets.

1. Load the dataset and identify text fields to analyze

First load the data .csv or .tsv file, select the column containing the data you wish to examine, and then you will evaluate the most and least common words in the unprocessed text. These will assist you in identifying any custom stop words that you may choose to include before normalising the text.

2. Create a list of Stop Words

Stop words are regularly used words such as "the," "a," "an," "in," and so on that occur frequently in natural language but do not provide important information about the meaning or subject of a message. The NLTK module provides a list of the most common English stop words, which you can import. One can also provide a list of bespoke stop words based on the text that they are examining. A list of "most often occurring words" provides some good choices for designing the custom stop words list. 

3. Pre-processing the data to get a cleaned and normalized text corpus

Pre-processing entails removing punctuation, tags, and special characters from the text before normalising what remains into identifiable words. Normalization involves "stemming", which eliminates suffixes and prefixes from word roots, and "lemmatization", which maps the remaining root forms (which may or may not be proper words) back to a natural language word. All of these procedures identify a canonical representative for a set of related word forms, allowing us to estimate word frequency independent of morphological (word form) variances.

4. Extract the most frequently occurring keywords and N-grams

We've now arrived at the point where we can build a list of top keywords and n-grams, in this case, two and three-word phrases (bigrams and trigrams). These lists and charts, of course, barely scratch the surface of the information that could be found in this text corpus, but they do point us in the right direction for further investigation. They also provide a high-level summary that partners and stakeholders may easily understand.

5. Extract a list of top TF-IDF terms

The TF-IDF statistic, which stands for "Term Frequency-Inverse Document Frequency," is a numerical statistic that measures how relevant a word is to a document in a collection. The TF-IDF value of a term grows in proportion to the number of times the word appears in a document and is then offset by the number of documents in the corpus that contain the word. This compensates for the fact that some words appear more frequently than others. As a consequence, we have a list of words rated by how significant they are to the corpus as a whole.

Advantages of Keyword Extraction

The benefits of keyword extraction are numerous, but we have narrowed them down to three.

Scalability: You can analyse as much data as you want with automated keyword extraction. Yes, you could manually read texts and identify key terms, but it would take a long time. By automating this work, you will be able to focus on other aspects of your profession. 

Consistent criteria: Keyword extraction operates on the basis of rules and established parameters. Inconsistencies, which are typical in manual text analysis, are avoided. 

Real-time analysis: You can execute real-time keyword extraction on social media postings, customer reviews, surveys, or customer support issues to gain insights into what's being said about your product as it happens and track it over time.


The keyword extraction procedure aids us in discovering crucial terms. It is also useful for subject modelling jobs. With just a few keywords, you can learn a lot about your text data. These keywords can help you decide whether or not to read an article. It is already used in some of the major fields/industries out there. Including Social media monitoring, Brand monitoring, Customer service, Customer feedback, Business intelligence, Search engine optimization (SEO), Product analytics, and Knowledge management.

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Cloud platforms offer fast access to high performance compute and deep learning algorithms, which makes it simpler to start using machine learning models and get early insights into your data. 

Cloud GPUs are better for machine learning because they have lower latency, which is important because the time it takes a neural network to learn from data affects its accuracy. Furthermore, cloud GPUs allow users to take advantage of large-scale training datasets without having to build and maintain their own infrastructure.

On Premises GPUs are better for machine learning if you need high performance or require access to cutting-edge technologies not available in the public cloud. For example, on-premises hardware can be used for deep learning applications that require high memory bandwidth and low latency.

Cloud GPUs: Cloud GPUs are remote data centers where you can rent unused GPU resources. This allows you to run your models on a massive scale, without having to install and manage a local machine learning cluster.

Lower TCO: Cloud GPUs require no upfront investment, making them ideal for companies that are looking to reduce their overall capital expenses. Furthermore, the cost of maintenance and upgrades is also low since it takes place in the cloud rather than on-premises.

Scalability & Flexibility: With cloud-based GPU resources, businesses can scale up or down as needed without any penalty. This ensures that they have the resources they need when demand spikes but also saves them money when there is little or no demand for those resources at all times.

Enhanced Capacity Planning Capabilities: Cloud GPU platforms allow businesses to better plan for future demands by providing estimates of how much processing power will be required in the next 12 months and beyond based on past data points such as workloads run and successes achieved with similar models/algorithms etc... 

Security & Compliance : Since cloud GPUs reside in a remote datacenter separate from your business' core systems, you are ensured peace of mind when it comes to security and compliance matters (eigenvector scanning / firewalls / SELinux etc...) 

Reduced Total Cost Of Ownership (TCO) over time due to pay-as-you-go pricing model which allows you only spend what you actually use vs traditional software licensing models where significant upfront investments are made.

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Impact of the Strong Dollar: Cloud Costs Increasing, Be Indian Buy Indian

Indian SMEs and startups are feeling the effects of the high dollar. These businesses use hyperscalers(MNC Cloud) who cannot modify their rates to account for the changing exchange rate. For certain companies, even a little shift in the currency rate may have a significant effect on their bottom line. Did you know, when the INR-USD exchange rate moved from 60 to 70 in December 2015, it had an impact of around 20% on Digital Innovation?

As the rupee is inching closer to 82 per dollar, the strong dollar has directly impacted the costs of cloud services for Indian businesses. The high cost of storage and computing power, along with bandwidth charges from overseas vendors, has led to a huge increase in the effective rate of these services. This is especially true for startups and SMEs that rely on cloud computing to store and process user data. With the strong dollar continuing to impact the cost of cloud services, it is essential for Indian companies to evaluate their options and adopt local alternatives wherever possible. This blog post will discuss how the strong dollar impacts cloud costs, as well as potential Indian alternatives you can explore in response to this global economic trend. 

What is a Strong Dollar?

A strong US dollar($) is a term used to describe a situation where a US’s currency has appreciated in value compared to other major currencies. This can be due to a variety of factors, including interest rate changes, a country’s current account deficit, and investor sentiment. When a currency appreciates, it means that it is worth more. A strong dollar makes imports more expensive, while making exports cheaper. Strong dollars have been a growing trend in the past couple of years. As the US Federal Reserve continues to hike interest rates, the dollar strengthens further. The rising value of the dollar means that the cost of cloud services, especially from hyperscalers based in the US, will rise as well. 

Increase in Cloud Costs Due to Strong Dollar

Cloud services are essential for modern businesses, as they provide easy access to software, storage, and computing resources. Cloud services are delivered over the internet and are typically charged on a per-use basis. This makes them incredibly convenient for businesses, as they can pay for only the resources they actually use. Cloud computing allows businesses to scale their resources up or down, depending on their current business needs. This makes it suitable for startups, where demand is uncertain, or large enterprises with global operations. Cloud computing is also inherently scalable and allows businesses to quickly react to changing business needs. Cloud computing is a very competitive industry and providers offer attractive prices to attract customers. However, these prices have been impacted by the strong dollar. The dollar has strengthened by 15-20% against the Indian rupee in the last few years. As a result, the costs of services such as storage and bandwidth have increased for Indian companies. Vendors charge their Indian customers in Indian rupees, taking into account the exchange rate. This has resulted in a significant rise in the costs of these services for Indian companies.

Why are Cloud Services Becoming More Expensive?

Cloud services are priced in US dollars. When the dollar is strong, the effective price of services will be higher in Indian rupees, as the cost is not re-adjusted. There are a couple of reasons for this price discrepancy. First, Indian customers will have to pay the same prices as American customers, despite a weaker Indian rupee. Second, vendors have to ensure that they make a profit.

Possible Indian Alternatives to Cloud Services

If you're looking for a cost-effective substitute for services provided by the U.S.-based suppliers, consider E2E Cloud, an Indian cloud service provider. When it comes to cloud services, E2E Cloud provides everything that startups and SMEs could possibly need.

The table below lists some of these services and compares their cost against their US equivalents. 

According to the data in the table above, Indian E2E Cloud Services are much cheaper than their American equivalents. The difference in price between some of these options is substantial. When compared to the prices charged by suppliers in the United States, E2E Cloud's bandwidth costs are surprisingly low. Although not all E2E Cloud services will be noticeably less expensive. Using Indian services, however, has an additional, crucial perk: data sovereignty.


The price of cloud services will rise as the US Dollar appreciates. Indian businesses will need to find ways to counteract the strong dollar's impact on their bottom lines. To do this, one must use E2E Cloud. The availability of E2E Cloud services in INR currency is a bonus on top of the already substantial cost savings. An effective protection against the negative effects of a strong dollar.

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Actions CEOs can take to get the value in Cloud Computing

It is not a new thing to say that a major transition is on the way. The transition in which businesses will rely heavily on cloud infrastructure rather than having their own physical IT structure. All of this is due to the cost savings and increased productivity that cloud technology brings to these businesses. Each technological advancement comes with a certain level of risk. Which must be handled carefully in order to ensure the long-term viability of the technology and the benefits it provides.

And CEOs are the primary motivators and decision-makers in any major shift or technological migration in the organization. In the twenty-first century, which is a data-driven century, it is up to the company's leader to decide what and how his/her organization will perform, overcome the risk and succeed in the coming days.

In this blog, we are going to address a few of the actions that CEOs can take to get value in cloud Computing.

  1. A Coordinated Effort

As the saying goes, the more you avoid the risk, the closer it gets. So, if CEOs and their management teams have yet to take an active part or give the necessary attention that their migration journey to the cloud requires, now is the best time to start top-team support for the cloud enablement required to expedite digital strategy, digitalization of the organization, 

The CEO's position is critical because no one else can mediate between the many stakeholders involved, including the CIO, CTO, CFO, chief human-resources officer (CHRO), chief information security officer (CISO), and business-unit leaders.

The move to cloud computing is a collective-action challenge, requiring a coordinated effort throughout an organization's leadership staff. In other words, it's a question of orchestration, and only CEOs can wield the baton. To accelerate the transition to the cloud, CEOs should ask their CIO and CTO what assistance they require to guide the business on the path.

     2. Enhancing business interactions 

To achieve the speed and agility that cloud platforms offer, regular engagement is required between IT managers and their counterparts in business units and functions, particularly those who control products and competence areas. CEOs must encourage company executives to choose qualified decision-makers to serve as product owners for each business capability.

  1. Be Agile

If your organization wants to benefit from the cloud, your IT department, if it isn't already, must become more agile. This entails more than simply transitioning development teams to agile product models. Agile IT also entails bringing agility to your IT infrastructure and operations by transitioning infrastructure and security teams from reactive, "ticket-driven" operations to proactive models in which scrum teams create application programme interfaces (APIs) that service businesses and developers can consume.

  1. Recruiting new employees 

CIOs and CTOs are currently in the lead due to their outstanding efforts in the aftermath of the epidemic. The CEOs must ensure that these executives maintain their momentum while they conduct the cloud transformation. 

Also, Cloud technology necessitates the hire of a highly skilled team of engineers, who are few in number but extremely expensive. As a result, it is envisaged that the CHRO's normal hiring procedures will need to be adjusted in order to attract the proper expertise. Company CEOs may facilitate this by appropriate involvement since this will be critical in deciding the success of the cloud transition.

  1. Model of Business Sustainability 

Funding is a critical component of shifting to the cloud. You will be creating various changes in your sector, from changing the way you now do business to utilizing new infrastructure. As a result, you'll have to spend on infrastructure, tools, and technologies. As CEO, you must develop a business strategy that ensures that every investment provides a satisfactory return on investment for your company. Then, evaluate your investments in order to optimise business development and value.

  1. Taking risks into consideration 

Risk is inherent in all aspects of corporate technology. Companies must be aware of the risks associated with cloud adoption in order to reduce security, resilience, and compliance problems. This includes, among other things, engaging in comprehensive talks about the appropriate procedures for matching risk appetite with technological environment decisions. Getting the business to take the correct risk tone will necessitate special attention from the CEO.

It's easy to allow concerns about security, resilience, and compliance to stall a cloud operation. Instead of allowing risks to derail progress, CEOs should insist on a realistic risk appetite that represents the company plan, while situating cloud computing risks within the context of current on-premises computing risks and demanding choices for risk mitigation in the cloud.


In conclusion, the benefits of cloud computing may be obtained through a high-level approach. A smooth collaboration between the CEO, CIO, and CTO may transform a digital transformation journey into a profitable avenue for the company.

CEOs must consider long-term cloud computing strategy and ensure that the organization is provided with the funding and resources for cloud adoption. The right communication is critical in cloud migration: employees should get these communications from C-suite executives in order to build confidence and guarantee adherence to governance requirements. Simply installing the cloud will not provide value for a company. Higher-level executives (particularly the CEO) must take the lead in the digital transformation path.

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