natural language processing

1. Addis Ababa University
School of Information Science
Doctor of Philosophy in Information Technology
(Information Systems)
presentation
By Belay Alemayehu
October , 2022
NATURAL LANGUAGE PROCESSING

2. Agenda
• What is NLP
• Components of NLP
• Application of NLP
• Steps in NLP
• NLP techniques
• Areas of my interest
•

3. What is NLP
• is a subfield of linguistics, computer science, and artificial intelligence
concerned with the interactions between computers and human
language, in particular how to program computers to process and
analyze large amounts of natural language data.(Wikipedia)
• strives to build machines that understand and respond to text or
voice data and respond with text or speech of their own in much the
same way humans do.
• Is field of computer science and computational linguistics

4. There are two main phases to NLP
1. Data Preprocessing :- involves preparing and
"cleaning" text data for machines to be able to
analyze it.
2. Algorithm Development can be Rules-based
system or Machine learning-based system

5. Components of NLP
1. Natural language generation is the process of transforming data
into natural language using artificial intelligence. powered by
machine learning and deep learning to turn numbers into natural
language text or speech that humans can understand.
• Chatbots, voice assistants, and AI blog writers
2. Natural language understanding:- is AI that uses computational
models to interpret the meaning behind human language. It
analyzes the data produced by NLP to understand the meaning of
your words and the relationships between concepts.
• mainly used in business application to understand the customer problem in
both speech and text

6. Text mining and NLP
• Text mining is the process of deriving meaning full information from
natural language text
• NLP is a part of computer science and AI which deals with human
language
• Artificial intelligence:- broad discipline of creating intelligent
machines
• Machine learning :- the science of getting computer to act without
being explicitly programmed that can learn from previous experience

7. Application of NLP
• Chatbots a form of artificial intelligence that are programmed to interact with
humans
• Autocomplete in Search Engines tend to guess what you are typing and
automatically complete your sentences
• Language Translator to convert text from one language to other
• Sentiment Analysis to understand how a particular type of user feels about a
particular topic, product, etc
• Grammar Checkers is a very important factor while writing professional reports
for your superiors even assignments for your lecturer
• Email Classification and Filtering promotional Emails that we don’t want to read.
•

8. Steps in NLP
1. Tokenizing :- identification in its place to retain all the essential
2. Stop words :- words which have very little meaning
3. Stemming :-normalize words in to its base form
4. Lemmatization :- group together different inflected form of word
5. Speech tagging :- marks words in the corpus to corresponding part
6. Named entity tagging :- seeks to extract real world entity
7. Chunking :- picking up individual pieces of info and grouping them
into bigger pieces

9. NLP techniques
1. Syntactic analysis Syntactic analysis the arrangement of words in a
sentences in some particular order so that make grammatical sense
1. Lemmatization :- grouping together the different inflected form of words
2. Morphological segment :- dividing word in to individual unit eg availabilities
3. Word segmentation :- dividing word into its component eg space
4. Part of speech tagging :-determining different part of speech for each word
5. Parsing :- under taking grammatical analysis for any sentence
6. Sentences splitting :- finding the sentences boundaries eg .
7. Stemming :- the process of obtaining root word

10. NLP techniques
2. Semantic analysis
1. Named Entity Recognition :-to categorize based on groups org, person
2. Word Sense Disambiguation :- base on context of sentence
3. Natural Language Generation :-use data base to drive semantic intention

11. Area of my interest
• Digital customer service for open source electronical medical records using
Ethiopian local language
• Digital Transformation of Customer Service. In essence, it is
customer service that is provided through digital channels, like
website support, live chat, email, social media and messaging apps.
• As much as technology has improved our lives, for many people
customer service experiences remain unnecessarily frustrating. By
adding new digital silos (e.g. a chatbot), many companies have
created disjointed islands of context, knowledge bases and
automation. However, if digital self-serve and human support are
integrated and aligned to customer expectations and behaviors,
digital customer service can bring significant benefits such as
increased revenue, reduced cost to serve, and higher customer
satisfaction.

12. Thank you
• Question and answer