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Natural Language Processing

Natural language processing (NLP) is a subsidiary of artificial intelligence (AI) in which natural human language can be processed and understood by machines so as to enable actionable insights to be performed on data that might have previously been unusable due to its ‘casual’ nature – for example, colloquially written language or heavily accented speech.

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    Many companies possess an abundance of textual data that is not properly utilized. In most cases this data can be extremely valuable, yet hard to digest due to its structure. With the power of NLP and Machine Learning, extracting information and finding answers from textual data becomes possible. Those that make the best use of their data will find themselves opening doors to exciting opportunities.

    Objective Logo Mark

    Husam Quteineh

    KTP Associate, Objective

    Take advantage of NLP in your business

    In simple terms, NLP is used to help computers overcome the ambiguity of English or other languages since much data is in the form of informally written and spoken formats such as emails and social media communication, so NLP helps computers understand, decipher, and turn it into meaningful information.

    It can often be frustrating having access to lots of textual (unstructured) data yet being unable to achieve any meaningful insights from it. You know that it can be used to help make business decisions, but you don’t know how you can use this information: this is where natural language processing comes in.

    Our NLP consultants, alongside the rest of our data analytics team, can help you gather meaningful insights from your data to help with decision making.

    What Can Natural Language Processing Do for You?

    Think of the forms of unstructured data you have access to: emails, social media and reviews, enquiry forms, case studies and search phrases amongst others – the likelihood is you have access to large amounts of varied data sources written and spoken in all sorts of ways.

    So how can you make best use of this type of data?

    Natural language processing applies a structure to unstructured data allowing you to query it efficiently and effectively. Text retrieval, document classification, text summarisation and sentiment analysis are just a few examples of what bespoke NLP can do for your business.

    Other examples of NLP in action include chatbots, email bots, social media monitoring, virtual digital assistants, predictive typing, spelling and grammar checkers, email spam detection, auto complete, and much more.

    What Are Some Examples of NLP In Use?

    Chances are you’ve used NLP in your everyday interactions with computers and the internet. Here are some uses:

    Digital assistants – when you talk to your Siri equipped Apple device or your Amazon Echo, NLP tech is at work as your device deciphers your words and implements your instructions.

    Chatbots – when you interact with website chatboxes, chances are you’re communicating with a chatbot that uses NLP as part of its AI armoury to respond either verbally or via the written word.

    Chatbots are becoming ever more sophisticated in that they can do more than just help with basic information provision; they can interact in more depth to the point where some users may be surprised they’re dealing with effectively a machine using natural language processing and not a real person.

    Translation – natural language processing enables communication barriers to be overcome so people can talk to each other in any language just about anywhere in the world, and understand written matter such as technical manuals in different languages.

    Google Translate, perhaps the best known translation platform, is used by 500 million people each day to help them communicate in over 100 languages ranging from basic phrases to conducting full conversations.

    Text retrieval – as simple as it sounds. A good example of this would be a search function within a website where webpages are indexed to enable and improve search features and capabilities.

    Text summarisation – the process of shortening content in order to create a summary of the major points. For example, you may have long form blogs but want a more concise version of them to put on social platforms. Using NLP, text summarisation would be able to do this for you.

    Sentiment analysis – a method of understanding whether a block of text has positive or negative connotations.

    An example of using this in action would be analysing the sentiment of contact form replies. Manually going through thousands of contact forms is a time consuming and tedious task.

    NLP enables most of this work to be automated leaving your staff with more time to work on more important tasks since sentiment analysis enables nuances of language to be detected – previously tech would find it near impossible to work with this type of written text so meaning humans would be tied up doing it.

    By performing natural language processing statistical analysis, you can provide valuable information for decision making processes. This analysis could give answers to questions such as which, why, and what services or products need improvements.

    Other remarkable NLP achievements – the tech has life-enhancing capabilities such as helping people unable to communicate verbally to do so; for example, enabling sign language used by the deaf and hard of hearing to be understood by those unfamiliar with it.

    How to Implement Natural Language Processing

    Working with you to understand your business, we at Objective IT can help you define desired outcomes and show you how natural language processing can help achieve them. It’s possible you can, with our help, put previously unusable data to valuable use to help you achieve your business objectives.

    Algorithms can be built upon training sets of data which can then be applied to the rest of your data sets. By understanding basic characteristics of how language within your data conforms, algorithms can be designed to specifically suit the type of data you collect, how it is written or spoken, and further tweaked as the data set expands so making them more accurate.

    If you have any questions regarding natural language processing, or wish to implement NLP into your data strategy, get in touch so we can help you make the most of all your data in furthering your business by meeting your objectives.