## 2 Literature Review
### Industrial Enterprise Applications That Work with Natural Langue Processing  
The following applications are the most frequent use by companies to enhance better customer understanding of their products and services no matter their country of origin and language. Most of the applications use one or two aspects of NLP. Some of the text editors directly depend on the NLP system for easy access. **Unified communications as a service (UCaaS). ** This is an enterprise communication system where all communications are streamlined via cloud delivery to allow the industry to become more flexible with its human-financial resources and expenditure. Examples of (Uaas) are mobile systems apps (video, audios, SMS, and chat) and virtual apps (Ms Teams, Zoom, Skype, YouTube, WebEx). **Cloud Base Communication Systems**. This is a communication system that allows organizations to host their infrastructure in the cloud or off-site. With this system, multiple locations host the industry server. With multiple server location systems, it is easier to back up, protect, free-up space, and run proper on-premises resource management. Three-dimensional printing is one example where documents are printed and shared remotely. Gmail also operates in the same manner. **Semantic text analytics applications for business. ** Semantic text analysis helps organizations with the interpretation of the text meaning and extraction of critical information from unstructured data. Semantic text analysis enhances machine learning tools that are very important for natural language processing components which in turn boost decision-making and improve the overall customer experience. Semantics text analysis techniques. 1. Semantic classification (Topic classification, Sentiment analysis, and Intent classification). 2. Semantic extraction. (Keyword extraction and Entity extraction). **Types of semantics broadly used nowadays. **  
* Google's semantic algorithm-Hummingbird
* Cdisccount's semantic analysis of customer reviews
* IBM's Watson conversation service
* Automated ticketing support  
**Smart translation applications for business. ** The following applications are the most frequent use by companies to enhance better customer understanding of their products are services no matter their country of origin and language. Most of the applications use one or two aspects of NLP. * **Google Cloud Translation. ** This type of translator lets you dynamically translate between languages using a pre-trained and custom Machine Learning model based on your content needs and requirements. * **Microsoft Translator. ** This is a smart translation application readily available for Windows, iOS, and Android. Microsoft Translator helps users translate text, images, screenshots, and voices. Microsoft Translator is available in more than 60 languages. * **Linguee Translator. ** This is a web-based application service launched in 2009 that helps users to translate singular words. Linguee shows users a diverse, bilingual pair of words and sentences that are used in online publications. The application is available on Windows, iOS, and Android. * **Babylon Translation application. ** This application is one of the number one translation and dictionary software globally used. The application is supported by Windows, Android, Mac, and iOS. It also translates to more than 77 languages. * **iTranslate Translation application**. This is an app built for all types of systems such as Windows, iOS, Mac, Google Play, and Kindle Fire. This app is a straightforward software that can translate anything by just typing words, text, and voice-to-voice speech. **Document converters applications for business. ** The following are iOS and Android apps that can help users convert any files into PDFs. From Word, Excel, PowerPoint, and JPEG. * **iLovePDF**. This is a PDF editor and reader that is 100% free for use. iLovePDF works on both iOS and Android. iLovePDF supports 25 languages and with up to 10 free converters every day for single system software. * **PDF Converter Ultimate.