In the world of internet, there is a lot of business information, but 80% of this information is unstructured i.e. unorganized, and it is expected to increase to 93% by 2020 due to constant use of social media, emails, documents, photos, videos, etc. This unstructured information gives a lot of information about your customers, your customer’s brand perceptions, your competitors, and much more. People share their positive and negative experiences regarding a product and provide feedback. This information in the form of online reviews, in turn, shapes the views of other people who proactively seek such information before purchasing a product. They give reviews about different products they have used. This impacts the views of other people regarding this product. First thing people see before buying a product or service is the online reviews.
We will see how the Review Inspector analyzes the sentiment of these reviews so that business owners can align their strategies with customer demand. Review Inspector does Sentiment Analysis as well as POS Tagging of reviews.
Sentiment Analysis informs whether the sentiment of the review is positive, negative or neutral.
You can input a sentence of your choice and gauge the underlying sentiment.
POS Tagging (Part Of Speech Tagging) is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition and its context.
To solve the problem, we use DLTK.ai. Let’s see how DLTK works:
First, we need to create a project in the DLTK Console.
In DLTK Console, we can build a model in two ways:
If you want to develop a model using SDK, just copy the API key from DLTK Console.
To install python SDK, use following command:
pip install dltk_ai
Description
You can access the services provided by enabling API for DLTK language. DLTK provides DltkAiClient where you have to pass your API KEY as an argument.
import dltk_ai c = dltk_ai.DltkAiClient("YOUR API KEY")
Description
import dltk_ai c = dltk_ai.DltkAiClient("YOUR API KEY")Response:
import dltk_ai c = dltk_ai.DltkAiClient("YOUR API KEY")
Description
sentence = client.sentiment_analysis("The rooftop cafeteria of hotel was great.")Response :
response { 'x': 230, 'y': 290, 'width': 90, 'height': 90, 'ratio': 0 }
Description
sentence = client.sentiment_analysis("The rooftop cafeteria of hotel was great.")Response :
{ 'text': "The rooftop cafeteria of hotel was great.", 'polarity': 3, 'emotion': 'POSITIVE', 'msg': None }
Description
sentence = client.pos_tagger("The stay was great")Response :
{ { 'text': 'The stay was great', 'result': {'The': 'DT', 'was': 'VBD', 'great': 'JJ', 'stay': 'NN'}, 'msg': None } }
Review Inspector is just a small application of Dltk Language. We can extend the use case such as:
Analyzing the sentiment of comments for our social media posts.
We can also use it for faster customer support by filtering negative sentiments in forums by keeping them as a high priority.
Prof. Sanjay Verma is area chair for aligning IT Business at IIM-A and has been mentoring fortunate few on developing great IT products for business.
Dr. Sanjay Verma holds his doctorate in space of Artificial Intelligence and is mentoring CIOs of variety of businesses. Government has appointed him as Independent director for one of India’s largest Public sector bank.
Mr. Sada Iyer played pivotal role in establishing HPE in India. He redefined Service Integration space in India. Sada is considered encyclopaedia of Banking across the globe and has lead globally BFSI division in world class firms like HPE and Oracle.
Sada has been sounding board to several banking and Insurance policy makers.
Experienced in Internal Audits, Risk Management , Corporate Governance and Business Advisory Services. He is a Certified Internal Auditor from The Institute of Internal Auditors, (USA), Certified Information Systems Auditor from ISACA (USA) , Certified Fraud Examiner from Association of Certified Fraud Examiners, (USA) & Specializes in Organizational Transformation, Risk Management and Corporate Governance.
Prof. K.C. John established Qualcomm in India. He is associated to World Economic Forum’s Sustainability Chapter. He has demonstrated a massive success in startup space by establishing successful firms back to back.
Currently he is on advisory board at Qubit AI and mentoring startups associated to Great Lakes Institute of Management and considered finest Professor to impart leadership lessons to Chief Executives.
Highly’ experienced in Research & Development, Strong knowledge Systems, product development, interpretation of National & International standards. Identifying product requirements / risks. Can solve any mechanical & electrical problems related to product development. Very Good at learning new things & implementing. Have 3 international patents.
Skilled in Product Management, AI/ML/DL,Domain expertise in various domains,Design and Lead AI COE, Skilled AI Trainer, Designing courses, Graduated Business Analytics professional from ISB.
Professional Chartered Accountant with experience in both Audit and Finance.