Handbook of research on AI and machine learning applications and implications in customer support and analytics:
"AI and Machine Learning Applications and Implications in Customer Support and Analytics explores various artificial intelligence and machine learning models and methods for business applications, as well as algorithmic approaches for customer support and analytics in a variety of fields and ap...
Saved in:
| Other Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2023.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "AI and Machine Learning Applications and Implications in Customer Support and Analytics explores various artificial intelligence and machine learning models and methods for business applications, as well as algorithmic approaches for customer support and analytics in a variety of fields and applications in the modern data-driven era where data is arriving in greater variety and with more velocity. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, unsupervised learning, deep learning, customer sentiment analysis, customer emotional analysis, natural language processing, data mining, neural networks, ensemble learning, business analytics and analytical geared toward"-- |
| Physical Description: | 29 PDFs (423 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781668471074 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
MARC
| LEADER | 00000nam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-98-IGB-00306191 | ||
| 003 | IGIG | ||
| 005 | 20230516134413.0 | ||
| 006 | m eo d | ||
| 007 | cr bn||||m|||a | ||
| 008 | 230516s2023 pau fob 001 0 eng d | ||
| 020 | |a 9781668471074 |q PDF | ||
| 020 | |z 1668471051 |q hardcover | ||
| 020 | |z 9781668471050 |q print | ||
| 024 | 7 | |a 10.4018/978-1-6684-7105-0 |2 doi | |
| 035 | |a (CaBNVSL)slc00004402 | ||
| 035 | |a (OCoLC)1379307084 | ||
| 040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
| 050 | 4 | |a HF5415.32 |b .H36426 2023e | |
| 082 | 7 | |a 658.8/342028563 |2 23 | |
| 245 | 0 | 0 | |a Handbook of research on AI and machine learning applications and implications in customer support and analytics |c edited by Md Shamim Hossain, Ree Chan Ho, Goran Trajkovski. |
| 246 | 3 | |a Handbook of research on artificial intelligence and machine learning applications and implications in customer support and analytics | |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2023. | |
| 300 | |a 29 PDFs (423 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Section 1. Customer analytics. Chapter 1. Adoption of churn recognition system to predict customer churn: a study with respect to semiconductor supply chain ; Chapter 2. Examining customer behavior towards the use of contextual commerce powered by artificial intelligence ; Chapter 3. Artificial intelligence model for analyzing the buying patterns of customers ; Chapter 4. A pedagogy to support learning analytics: a case for a specific higher education institution ; Chapter 5. The role of machine learning in customer experience ; Chapter 6. Mall customer segmentation engine through clustering analysis -- Section 2. Machine learning for optimization. Chapter 7. Application of machine learning for optimization ; Chapter 8. Approval of artificial intelligence and machine learning models to solve problems in nonlinear active suspension systems ; Chapter 9. Machine learning frameworks in carpooling ; Chapter 10. Smart ATM with tracking of criminals using novel di-pattern and C-LDP (combined local directional pattern) -- Section 3. Predictive analytics. Chapter 11. Restaurant sales prediction using machine learning ; Chapter 12. Big data analytics-based agro advisory system for crop recommendation using spark platform ; Chapter 13. Clearance date prediction using machine learning techniques ; Chapter 14. Predicting healthcare readmissions using artificial intelligence -- Section 4. Artificial intelligence in customer support. Chapter 15. AI and machine learning applications to enhance customer support ; Chapter 16. Customer face-detecting artificial intelligence with people search social site algorithm for product encroachment in supermarkets: business development with customer perspective AI technology ; Chapter 17. User sentiment prediction and analysis for payment app reviews using supervised and unsupervised machine learning approaches ; Chapter 18. Sequence graph-based query Auto-suggestion (SGQAS). | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | |a "AI and Machine Learning Applications and Implications in Customer Support and Analytics explores various artificial intelligence and machine learning models and methods for business applications, as well as algorithmic approaches for customer support and analytics in a variety of fields and applications in the modern data-driven era where data is arriving in greater variety and with more velocity. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, unsupervised learning, deep learning, customer sentiment analysis, customer emotional analysis, natural language processing, data mining, neural networks, ensemble learning, business analytics and analytical geared toward"-- |c Provided by publisher. | ||
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 05/16/2023). | ||
| 650 | 0 | |a Artificial intelligence |x Marketing applications. | |
| 650 | 0 | |a Consumer behavior |x Data processing. | |
| 650 | 0 | |a Consumers |x Research. | |
| 653 | |a Artificial Intelligence. | ||
| 653 | |a Business Analytics. | ||
| 653 | |a Business Intelligence. | ||
| 653 | |a Customer Engagement. | ||
| 653 | |a Customer Sentiment Analysis. | ||
| 653 | |a Data Mining. | ||
| 653 | |a Deep Learning. | ||
| 653 | |a Machine Learning. | ||
| 653 | |a Neural Networks. | ||
| 653 | |a Supervised Learning. | ||
| 700 | 1 | |a Ho, Ree C. |d 1986- |e editor. | |
| 700 | 1 | |a Hossain, Md Shamim |d 1986- |e editor. | |
| 700 | 1 | |a Trajkovski, Goran |d 1972- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 1668471051 |z 9781668471050 |
| 966 | 4 | 0 | |l DE-862 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-7105-0 |3 Volltext |
| 966 | 4 | 0 | |l DE-863 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-7105-0 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-862 | ||
| 049 | |a DE-863 | ||
Record in the Search Index
| DE-BY-FWS_katkey | ZDB-98-IGB-00306191 |
|---|---|
| _version_ | 1826942601526247424 |
| adam_text | |
| any_adam_object | |
| author2 | Ho, Ree C. 1986- Hossain, Md Shamim 1986- Trajkovski, Goran 1972- |
| author2_role | edt edt edt |
| author2_variant | r c h rc rch m s h ms msh g t gt |
| author_facet | Ho, Ree C. 1986- Hossain, Md Shamim 1986- Trajkovski, Goran 1972- |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | H - Social Science |
| callnumber-label | HF5415 |
| callnumber-raw | HF5415.32 .H36426 2023e |
| callnumber-search | HF5415.32 .H36426 2023e |
| callnumber-sort | HF 45415.32 H36426 42023E |
| callnumber-subject | HF - Commerce |
| collection | ZDB-98-IGB |
| contents | Section 1. Customer analytics. Chapter 1. Adoption of churn recognition system to predict customer churn: a study with respect to semiconductor supply chain ; Chapter 2. Examining customer behavior towards the use of contextual commerce powered by artificial intelligence ; Chapter 3. Artificial intelligence model for analyzing the buying patterns of customers ; Chapter 4. A pedagogy to support learning analytics: a case for a specific higher education institution ; Chapter 5. The role of machine learning in customer experience ; Chapter 6. Mall customer segmentation engine through clustering analysis -- Section 2. Machine learning for optimization. Chapter 7. Application of machine learning for optimization ; Chapter 8. Approval of artificial intelligence and machine learning models to solve problems in nonlinear active suspension systems ; Chapter 9. Machine learning frameworks in carpooling ; Chapter 10. Smart ATM with tracking of criminals using novel di-pattern and C-LDP (combined local directional pattern) -- Section 3. Predictive analytics. Chapter 11. Restaurant sales prediction using machine learning ; Chapter 12. Big data analytics-based agro advisory system for crop recommendation using spark platform ; Chapter 13. Clearance date prediction using machine learning techniques ; Chapter 14. Predicting healthcare readmissions using artificial intelligence -- Section 4. Artificial intelligence in customer support. Chapter 15. AI and machine learning applications to enhance customer support ; Chapter 16. Customer face-detecting artificial intelligence with people search social site algorithm for product encroachment in supermarkets: business development with customer perspective AI technology ; Chapter 17. User sentiment prediction and analysis for payment app reviews using supervised and unsupervised machine learning approaches ; Chapter 18. Sequence graph-based query Auto-suggestion (SGQAS). |
| ctrlnum | (CaBNVSL)slc00004402 (OCoLC)1379307084 |
| dewey-full | 658.8/342028563 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
| dewey-raw | 658.8/342028563 |
| dewey-search | 658.8/342028563 |
| dewey-sort | 3658.8 9342028563 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05219nam a2200601 i 4500</leader><controlfield tag="001">ZDB-98-IGB-00306191</controlfield><controlfield tag="003">IGIG</controlfield><controlfield tag="005">20230516134413.0</controlfield><controlfield tag="006">m eo d </controlfield><controlfield tag="007">cr bn||||m|||a</controlfield><controlfield tag="008">230516s2023 pau fob 001 0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781668471074</subfield><subfield code="q">PDF</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">1668471051</subfield><subfield code="q">hardcover</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781668471050</subfield><subfield code="q">print</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/978-1-6684-7105-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaBNVSL)slc00004402</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1379307084</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">CaBNVSL</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="c">CaBNVSL</subfield><subfield code="d">CaBNVSL</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">HF5415.32</subfield><subfield code="b">.H36426 2023e</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">658.8/342028563</subfield><subfield code="2">23</subfield></datafield><datafield tag="245" ind1="0" ind2="0"><subfield code="a">Handbook of research on AI and machine learning applications and implications in customer support and analytics </subfield><subfield code="c">edited by Md Shamim Hossain, Ree Chan Ho, Goran Trajkovski.</subfield></datafield><datafield tag="246" ind1="3" ind2=" "><subfield code="a">Handbook of research on artificial intelligence and machine learning applications and implications in customer support and analytics</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) </subfield><subfield code="b">IGI Global</subfield><subfield code="c">2023.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">29 PDFs (423 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">electronic</subfield><subfield code="2">isbdmedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Section 1. Customer analytics. Chapter 1. Adoption of churn recognition system to predict customer churn: a study with respect to semiconductor supply chain ; Chapter 2. Examining customer behavior towards the use of contextual commerce powered by artificial intelligence ; Chapter 3. Artificial intelligence model for analyzing the buying patterns of customers ; Chapter 4. A pedagogy to support learning analytics: a case for a specific higher education institution ; Chapter 5. The role of machine learning in customer experience ; Chapter 6. Mall customer segmentation engine through clustering analysis -- Section 2. Machine learning for optimization. Chapter 7. Application of machine learning for optimization ; Chapter 8. Approval of artificial intelligence and machine learning models to solve problems in nonlinear active suspension systems ; Chapter 9. Machine learning frameworks in carpooling ; Chapter 10. Smart ATM with tracking of criminals using novel di-pattern and C-LDP (combined local directional pattern) -- Section 3. Predictive analytics. Chapter 11. Restaurant sales prediction using machine learning ; Chapter 12. Big data analytics-based agro advisory system for crop recommendation using spark platform ; Chapter 13. Clearance date prediction using machine learning techniques ; Chapter 14. Predicting healthcare readmissions using artificial intelligence -- Section 4. Artificial intelligence in customer support. Chapter 15. AI and machine learning applications to enhance customer support ; Chapter 16. Customer face-detecting artificial intelligence with people search social site algorithm for product encroachment in supermarkets: business development with customer perspective AI technology ; Chapter 17. User sentiment prediction and analysis for payment app reviews using supervised and unsupervised machine learning approaches ; Chapter 18. Sequence graph-based query Auto-suggestion (SGQAS).</subfield></datafield><datafield tag="506" ind1=" " ind2=" "><subfield code="a">Restricted to subscribers or individual electronic text purchasers.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">"AI and Machine Learning Applications and Implications in Customer Support and Analytics explores various artificial intelligence and machine learning models and methods for business applications, as well as algorithmic approaches for customer support and analytics in a variety of fields and applications in the modern data-driven era where data is arriving in greater variety and with more velocity. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, unsupervised learning, deep learning, customer sentiment analysis, customer emotional analysis, natural language processing, data mining, neural networks, ensemble learning, business analytics and analytical geared toward"--</subfield><subfield code="c">Provided by publisher.</subfield></datafield><datafield tag="530" ind1=" " ind2=" "><subfield code="a">Also available in print.</subfield></datafield><datafield tag="538" ind1=" " ind2=" "><subfield code="a">Mode of access: World Wide Web.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on title screen (IGI Global, viewed 05/16/2023).</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Artificial intelligence</subfield><subfield code="x">Marketing applications.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Consumer behavior</subfield><subfield code="x">Data processing.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Consumers</subfield><subfield code="x">Research.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Artificial Intelligence.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Business Analytics.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Business Intelligence.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Customer Engagement.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Customer Sentiment Analysis.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Data Mining.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Deep Learning.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Machine Learning.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Neural Networks.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Supervised Learning.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ho, Ree C.</subfield><subfield code="d">1986-</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hossain, Md Shamim</subfield><subfield code="d">1986-</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Trajkovski, Goran</subfield><subfield code="d">1972-</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">IGI Global,</subfield><subfield code="e">publisher.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="z">1668471051</subfield><subfield code="z">9781668471050</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-862</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FWS_PDA_IGB</subfield><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-7105-0</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-863</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FWS_PDA_IGB</subfield><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-7105-0</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-98-IGB</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-862</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-98-IGB-00306191 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:36Z |
| institution | BVB |
| isbn | 9781668471074 |
| language | English |
| oclc_num | 1379307084 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 29 PDFs (423 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | IGI Global |
| record_format | marc |
| spelling | Handbook of research on AI and machine learning applications and implications in customer support and analytics edited by Md Shamim Hossain, Ree Chan Ho, Goran Trajkovski. Handbook of research on artificial intelligence and machine learning applications and implications in customer support and analytics Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2023. 29 PDFs (423 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Section 1. Customer analytics. Chapter 1. Adoption of churn recognition system to predict customer churn: a study with respect to semiconductor supply chain ; Chapter 2. Examining customer behavior towards the use of contextual commerce powered by artificial intelligence ; Chapter 3. Artificial intelligence model for analyzing the buying patterns of customers ; Chapter 4. A pedagogy to support learning analytics: a case for a specific higher education institution ; Chapter 5. The role of machine learning in customer experience ; Chapter 6. Mall customer segmentation engine through clustering analysis -- Section 2. Machine learning for optimization. Chapter 7. Application of machine learning for optimization ; Chapter 8. Approval of artificial intelligence and machine learning models to solve problems in nonlinear active suspension systems ; Chapter 9. Machine learning frameworks in carpooling ; Chapter 10. Smart ATM with tracking of criminals using novel di-pattern and C-LDP (combined local directional pattern) -- Section 3. Predictive analytics. Chapter 11. Restaurant sales prediction using machine learning ; Chapter 12. Big data analytics-based agro advisory system for crop recommendation using spark platform ; Chapter 13. Clearance date prediction using machine learning techniques ; Chapter 14. Predicting healthcare readmissions using artificial intelligence -- Section 4. Artificial intelligence in customer support. Chapter 15. AI and machine learning applications to enhance customer support ; Chapter 16. Customer face-detecting artificial intelligence with people search social site algorithm for product encroachment in supermarkets: business development with customer perspective AI technology ; Chapter 17. User sentiment prediction and analysis for payment app reviews using supervised and unsupervised machine learning approaches ; Chapter 18. Sequence graph-based query Auto-suggestion (SGQAS). Restricted to subscribers or individual electronic text purchasers. "AI and Machine Learning Applications and Implications in Customer Support and Analytics explores various artificial intelligence and machine learning models and methods for business applications, as well as algorithmic approaches for customer support and analytics in a variety of fields and applications in the modern data-driven era where data is arriving in greater variety and with more velocity. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, unsupervised learning, deep learning, customer sentiment analysis, customer emotional analysis, natural language processing, data mining, neural networks, ensemble learning, business analytics and analytical geared toward"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 05/16/2023). Artificial intelligence Marketing applications. Consumer behavior Data processing. Consumers Research. Artificial Intelligence. Business Analytics. Business Intelligence. Customer Engagement. Customer Sentiment Analysis. Data Mining. Deep Learning. Machine Learning. Neural Networks. Supervised Learning. Ho, Ree C. 1986- editor. Hossain, Md Shamim 1986- editor. Trajkovski, Goran 1972- editor. IGI Global, publisher. Print version: 1668471051 9781668471050 |
| spellingShingle | Handbook of research on AI and machine learning applications and implications in customer support and analytics Section 1. Customer analytics. Chapter 1. Adoption of churn recognition system to predict customer churn: a study with respect to semiconductor supply chain ; Chapter 2. Examining customer behavior towards the use of contextual commerce powered by artificial intelligence ; Chapter 3. Artificial intelligence model for analyzing the buying patterns of customers ; Chapter 4. A pedagogy to support learning analytics: a case for a specific higher education institution ; Chapter 5. The role of machine learning in customer experience ; Chapter 6. Mall customer segmentation engine through clustering analysis -- Section 2. Machine learning for optimization. Chapter 7. Application of machine learning for optimization ; Chapter 8. Approval of artificial intelligence and machine learning models to solve problems in nonlinear active suspension systems ; Chapter 9. Machine learning frameworks in carpooling ; Chapter 10. Smart ATM with tracking of criminals using novel di-pattern and C-LDP (combined local directional pattern) -- Section 3. Predictive analytics. Chapter 11. Restaurant sales prediction using machine learning ; Chapter 12. Big data analytics-based agro advisory system for crop recommendation using spark platform ; Chapter 13. Clearance date prediction using machine learning techniques ; Chapter 14. Predicting healthcare readmissions using artificial intelligence -- Section 4. Artificial intelligence in customer support. Chapter 15. AI and machine learning applications to enhance customer support ; Chapter 16. Customer face-detecting artificial intelligence with people search social site algorithm for product encroachment in supermarkets: business development with customer perspective AI technology ; Chapter 17. User sentiment prediction and analysis for payment app reviews using supervised and unsupervised machine learning approaches ; Chapter 18. Sequence graph-based query Auto-suggestion (SGQAS). Artificial intelligence Marketing applications. Consumer behavior Data processing. Consumers Research. |
| title | Handbook of research on AI and machine learning applications and implications in customer support and analytics |
| title_alt | Handbook of research on artificial intelligence and machine learning applications and implications in customer support and analytics |
| title_auth | Handbook of research on AI and machine learning applications and implications in customer support and analytics |
| title_exact_search | Handbook of research on AI and machine learning applications and implications in customer support and analytics |
| title_full | Handbook of research on AI and machine learning applications and implications in customer support and analytics edited by Md Shamim Hossain, Ree Chan Ho, Goran Trajkovski. |
| title_fullStr | Handbook of research on AI and machine learning applications and implications in customer support and analytics edited by Md Shamim Hossain, Ree Chan Ho, Goran Trajkovski. |
| title_full_unstemmed | Handbook of research on AI and machine learning applications and implications in customer support and analytics edited by Md Shamim Hossain, Ree Chan Ho, Goran Trajkovski. |
| title_short | Handbook of research on AI and machine learning applications and implications in customer support and analytics |
| title_sort | handbook of research on ai and machine learning applications and implications in customer support and analytics |
| topic | Artificial intelligence Marketing applications. Consumer behavior Data processing. Consumers Research. |
| topic_facet | Artificial intelligence Marketing applications. Consumer behavior Data processing. Consumers Research. |
| work_keys_str_mv | AT horeec handbookofresearchonaiandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT hossainmdshamim handbookofresearchonaiandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT trajkovskigoran handbookofresearchonaiandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT igiglobal handbookofresearchonaiandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT horeec handbookofresearchonartificialintelligenceandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT hossainmdshamim handbookofresearchonartificialintelligenceandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT trajkovskigoran handbookofresearchonartificialintelligenceandmachinelearningapplicationsandimplicationsincustomersupportandanalytics AT igiglobal handbookofresearchonartificialintelligenceandmachinelearningapplicationsandimplicationsincustomersupportandanalytics |