W4 – BI

From book:  Analytics, Data Science,  Artificial Intelligence Systems for Decision Support (11th Edition)

Chapter#7

Q#1 – Explain the relationship among data mining, text mining, and sentiment analysis. 

Q#2 – In your own words, define text mining, and discuss its most popular applications. 

Q#3 – What does it mean to induce structure into text-based data? Discuss the alternative ways of inducing structure into them. 

Q#4 – What is the role of NLP in text mining? Discuss the capabilities and limitations of NLP in the context of text mining. 

Exercise# Go to teradatauniversitynetwork.com and find the case study named “eBay Analytics.” Read the case carefully and extend your understanding of it by searching the Internet for additional information, and answer the case questions. 

Internet Exercise: Go to kdnuggets.com. Explore the sections on applications as well as software. Find names of at least three additional packages for data mining and text mining. 

Need one page for  question responses, one for exercise and one for internet exercise, total 3 pages with APA format references (separate) without plagiarism and quality work in next 48 hours.

Originality Report 1/26/22, 12:28 AM

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Student paper

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Internet (3)

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ProQuest document

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ASSIGNMENT WEEK 02

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ASSIGNMENT WEEK 4 1

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Data Mining
Dinesh S. 1

Patil (# 003073698) University of The Cumberlands

Business Intelligence

1

ITS-531-A01

Dr. Abbey Adeleke

1

01/26/2022

Question # 1: 3

Explain the relationship between data mining, text mining, and sentiment analysis. Text mining is a subset of data mining, while sentiment analysis is a subset of sentiment analysis.

Unstructured text files are ideal for data mining because of their flexibility. Whereas sentimental analysis works with sentiments like opinion judgments, data and text mining is a specific form of sentimental analysis that deals with identifying and characterizing terms in the text source. Text mining is applied for sentiment analysis, concept extraction, and behavioral pattern detection. It’s common for text mining to begin by analyzing a large amount of data, and sentiment analysis is used to identify the ex-

pression level in that data.

Question # 2: 4

In your own words, define text mining, and discuss its most popular applications.

Text mining can be described as a data mining procedure that can analyze unstructured textual content to identify any significant and valuable patterns. 5 Using text mining, un- structured or less structured text files can be mined for data. Various data mining algorithms can be used to filter the generated numerical in- dices. Discover text, a cloud-based text analytics service that is an active learning machine, is one of the most popular applications. Promotion- al areas and content mining applications can both benefit from text mining. Text mining can also be used in bioinformatics and biomedicine re-

search projects since it aids in gaining a better knowledge of the material (Wen et al., 2019).

Question # 3: 4 What does it mean to induce structure into text-based data? Discuss the alternative ways of inducing structure into them. The inducing structure involves deciphering unstructured data and rapidly classifying it to provide tangible results. Incorporating design into text-based information can be accomplished in one of four ways: • Classification • Clustering • Mining of association rules • Keeping tabs on

current trends

Question # 4: 4

What is the role of NLP in text mining?

6

Discuss the capabilities and limitations of NLP in the context of text mining.

Text analytics systems rely on natural language processing to make sense of the data they receive. Capabilities: Using NLP, one may “understand” human language and transform it into more easily controllable quantitative and graphical information for any suburbanite computer, such as academic records. This “word tallying” process is an example of NLP in action (Lalwani et al., 2018). Limitations: However, despite the many ad- vantages of Natural Language Processing, it is not without its drawbacks. Contextual words and phrases, as well as homonyms, are included •

Synonyms • Sarcasm and irony • Ambiguity • Mistakes in writing or speaking • Slang and colloquialisms.

7 Exercise#3 – Go to teradatauniversitynetwork.com and find the case study named “eBay Analytics.” Read the case carefully and extend your understanding of it by searching the Internet for additional information and answer the case questions. 8 eBay is a well-known and enormous commercial website for online purchasing and selling things at fixed costs and to the most noteworthy bidder through a closeout framework. Other commanding highlights include: 8 · The high permeability of your stuff because of eBay’s online presence. · More deals without promoting endeavors (vital catchphrases and reasonable cost are an absolute necessity) since eBay has its fans and ordinary pur- chasers who watch classifications. · Sales to sell uncommon things or those whose esteem users don’t know of special reserve funds on trans- portation. eBay merchants think that it’s hard to develop their business because of intense rivalry and the absence of a solid detailing device. In any case, with Putler, an inside and out announcing and investigating answer for eBay, developing business will currently be simple. The in- dependent eBay report simply outlines deals and exchanges, which isn’t sufficient to take users eBay business on the way. If users need to suc-

ceed, users should get to know all through their business, and subsequently, you should adhere to top to bottom announcing consistently.

Internet Exercise# 7: 4

Go to kdnuggets.com. Explore the sections on applications as well as software.

9 Find names of at least three addi- tional packages for data mining and text mining. Data Mining handles organized information-profoundly arranged information, for example, in

data sets or ERP frameworks. Please find below three packages: 1. Sisense 2. Weka

3. KNIME
10 Textminingmanagesunstructuredtext-basedinformation-textthatisn’tpre-characterizedorcoordinatedinanycapacity,forexample,in online media. Please find below three packages: 1. tm

2. Rweka

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12 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3531782
Mining, W. (2021). Data mining. 8 Retrieved February 17, 2021, from https://blogs.opentext.com/whats-the-difference-between-data-mining- and-text-mining/
Sharda, R., Delen, D., & Turban, E. (2020). 8

Analytics, Data Science, & Artificial Intelligence:

13

Systems for Decision Support.

1

In Google Books.

Pearson. 1 https://books.google.com/books/about/Analytics_Data_Science_Artificial_Intell.html?id=u2xTswEACAA J

Wen,A.,Fu,S.,Moon,S.,ElWazir,M.,Rosenbaum,A.,Kaggal,V.C.,…&Fan,J.(2019).14 DesideratafordeliveringNLPtoacceleratehealthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation. NPJ digital medicine, 2(1), 1-7. https://www.nature.com/articles/s41746- 019-0208-8 1

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ASSIGNMENT WEEK 02

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Student paper ASSIGNMENT WEEK 4 1	Original source Week 4 Assignment

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Student paper Patil (# 003073698) University of The Cumberlands

Original source Patil (# 003073698) University of The Cumberlands

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Student paper ITS-531-A01

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3. openNLP

References:Lalwani,T.,Bhalotia,S.,Pal,A.,Rathod,V.,&Bisen,S.(2018).ImplementationofaChatbotSystemusingAIandNLP.11 In- ternational Journal of Innovative Research in Computer Science & Technology (IJIRCST) Volume-6, Issue-3.

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3 Student paper 82%
Student paper Explain the relationship between data mining, text mining, and sentiment analysis. Text mining is a subset of data mining, while sentiment analysis is a subset of sentiment analysis.	Original source Explain relationship between data mining, text mining, and sentiment analy- sis Sentiment analysis is part of text mining which is in turn part of data mining

			4 topcustomwriters 100%
Student paper In your own words, define text mining, and discuss its most popular applications.	Original source In your own words, define text mining, and discuss its most popular applications

5 Student paper 65%
Student paper Using text mining, unstructured or less structured text files can be mined for data.	Original source The application of data mining to unstructured, or less organized, text files is text mining

4 topcustomwriters 100%

Student paper What does it mean to induce structure into text-based data? Discuss the al- ternative ways of inducing structure into them.

Original source What does it mean to induce structure into text-based data Discuss the alter- native ways of inducing structure into them

4 topcustomwriters 100%

Student paper What is the role of NLP in text mining?

Original source What is the role of NLP in text mining

6 myaustralianacademy 100%
Student paper Discuss the capabilities and limitations of NLP in the context of text mining.	Original source Discuss the capabilities and limitations of NLP in the context of text mining

7 Student paper 100%
Student paper Exercise#3 – Go to teradatauniversitynetwork.com and find the case study named “eBay Analytics.” Read the case carefully and extend your understand- ing of it by searching the Internet for additional information and answer the case questions.	Original source Exercise 3) Go to teradatauniversitynetwork.com and find the case study named “eBay Analytics.” Read the case carefully and extend your understand- ing of it by searching the Internet for additional information and answer the case questions

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Originality Report 1/26/22, 12:28 AM

8 Student paper 79%
Student paper eBay is a well-known and enormous commercial website for online purchas- ing and selling things at fixed costs and to the most noteworthy bidder through a closeout framework.	Original source eBay is a very famous and substantial commercial center for purchasing and selling things at both fixed costs and to the most noteworthy bidder through a closeout framework

8 Student paper 89%

Student paper · The high permeability of your stuff because of eBay’s online presence. · More deals without promoting endeavors (vital catchphrases and reasonable cost are an absolute necessity) since eBay has its fans and ordinary pur- chasers who watch classifications. · Sales to sell uncommon things or those whose esteem users don’t know of special reserve funds on transportation. eBay merchants think that it’s hard to develop their business because of in- tense rivalry and the absence of a solid detailing device.

Original source · The high permeability of your things because of eBay’s online presence · More deals without promoting endeavors (vital catchphrases and reasonable cost are an absolute necessity) because eBay has its fans and ordinary pur- chasers who watch classifications (Mining, W · Sales to sell uncommon things or those whose esteem users do not know special reserve funds on trans- portation eBay merchants think it is hard to develop their business because of intense rivalry and the absence of a reliable detailing device

8 Student paper 83%

Student paper In any case, with Putler, an inside and out announcing and investigating an- swer for eBay, developing business will currently be simple. The independent eBay report simply outlines deals and exchanges, which isn’t sufficient to take users eBay business on the way. If users need to succeed, users should get to know all through their business, and subsequently, you should adhere to top to bottom announcing consistently. Internet Exercise# 7:

Original source In any case, with Putler, an inside and out announcing an investigation an- swer for eBay, developing business will currently be simple (Mining, W The independent eBay report gives simply an outline of deals and exchanges, which is not sufficient to take users’ If users need to succeed, users should get to know all through their business, and henceforth, you should adhere to top to bottom announcing consistently (Sharda, R., Delen, D., Turban, E, 2020) Internet Exercise #7

4 topcustomwriters 100%

Student paper Go to kdnuggets.com. Explore the sections on applications as well as software.

Original source Go to kdnuggets.com Explore the sections on applications as well as software

9 smartacademicwriting 100%
Student paper Find names of at least three additional packages for data mining and text mining.	Original source Find names of at least three additional packages for data mining and text mining

10 Student paper 73%

Student paper

Text mining manages unstructured text-based information – text that isn’t pre-characterized or coordinated in any capacity, for example, in online media.

Original source

Data mining handles organized data – exceptionally designed information, for example, in data sets or ERP frameworks – text mining manages unstruc- tured text-based information – text that isn’t pre-characterized or coordinat- ed in any capacity, for example, in online media takes care of

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11 ProQuest document 79%
Student paper International Journal of Innovative Research in Computer Science & Technol- ogy (IJIRCST) Volume-6, Issue-3.	Original source International Journal of Innovative Research in Computer Science & Technol- ogy 3

12 ProQuest document 78%
Student paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3531782	Original source Retrieved from https://papers.ssrn.com/sol3/papers.cfm

	8 Student paper 100%
Student paper Retrieved February 17, 2021, from https://blogs.opentext.com/whats-the-dif- ference-between-data-mining-and-text-mining/ Sharda, R., Delen, D., & Tur- ban, E.	Original source Retrieved February 17, 2021, from https://blogs.opentext.com/whats-the-dif- ference-between-data-mining-and-text-mining/ Sharda, R., Delen, D., Turban, E

8 Student paper 100%

Student paper Analytics, Data Science, & Artificial Intelligence:

Original source Analytics, Data Science, & Artificial Intelligence

13 Student paper 100%
Student paper Systems for Decision Support.	Original source Systems for decision support

1 My paper 100%

Student paper In Google Books.

Original source In Google Books

1 My paper 100%

Student paper https://books.google.com/books/about/Analytics_Data_Science_Artificial_In- tell.html?id=u2xTswEACAA J

Original source https://books.google.com/books/about/Analytics_Data_Science_Artificial_In- tell.html?id=u2xTswEACAA J

14 ProQuest document 100%

Student paper

Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation.

Original source

Desiderata for Delivering NLP to Accelerate Healthcare AI Advancement and a Mayo Clinic NLP-as-a-Service Implementation

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