1. Text Analytics on Dataset
#DevConMru

2. Data ScienceBig
Processes and systems to extract knowledge or
insights from data
Large and complex data that has been collected
over several years

3. What is yelp ?

4. Dataset
yelp_academic_dataset_business – Business Information
yelp_academic_dataset_review – User Reviews
Combine the 2 using

5. DEMO

6. Text Analytics Methodologies
Natural Language Processing (NLP)

7. Part 1
Natural
Language
Processing
(NLP)
Microsoft Text Analytics
Sentiment Analysis
Keyword Extraction
Topic Detection
Language Detection

8. DEMO

9. Stemming
Revert the word into its original or root form

10. Stemming
(Results)

11. Common
Words
Removal

12. DEMO

13. Part 2
Natural
Language
Processing
(NLP)
Stanford CoreNLP

14. Part 2
Natural
Language
Processing
(NLP)
Stanford CoreNLP
Part of Speech
POS Tag Description Example
CC coordinating conjunction and
CD cardinal number 1, third
DT determiner the
EX existential there there is
FW foreign word d’hoevre
IN preposition/subordinating conjunction in, of, like
JJ adjective big
JJR adjective, comparative bigger
JJS adjective, superlative biggest

15. DEMO

16. Part 2
Natural
Language
Processing
(NLP)
Stanford CoreNLP

17. Part 2
Natural
Language
Processing
(NLP)
Stanford CoreNLP

18. DEMO

19. Term
Document
Matrix
Describes the frequency of terms that occur in a collection of documents

20. Term
Document
Matrix
Term frequency and weighting
TF-IDF weighting: give higher weight to terms that are
rare

21. Unsupervised
Learning
K-means Clustering
“Art of finding groups in data” – Kaufman, Rousseeuw
• No clear picture of what is within the document
•
• Natural pair of groupings
•
• Simple to run

22. K-means
Clustering

24. DEMO

25. Conclusion
1. Data Manipulation in R
2. Natural Language Processing
3. Machine Learning
4. Visualization

26. Text Analytics on Dataset
Thank you.