Applying AI and ML techniques for customer churn prediction in the telecom industry (Record no. 23298)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250811132914.0 |
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| fixed length control field | 250811b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 27028 |
| Author | Jeya, Mala D. |
| 245 ## - TITLE STATEMENT | |
| Title | Applying AI and ML techniques for customer churn prediction in the telecom industry |
| Remainder of title | : a data-driven decision-making approach |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.16(4), Nov |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Hyderabad |
| Name of publisher, distributor, etc. | IUP Publications |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 7-19p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | The paper delves into the application of artificial intelligence (AI) and machine learning (ML) techniques to predict customer attrition rates and promote data-driven decision making in the telecommunications industry. Using a comprehensive dataset encompassing customer demographics, usage behavior, subscription details, billing information, customer interactions, and historical churn records, the paper proposes a holistic approach to churn prediction. The implementation of cutting-edge AI and ML algorithms enables to meticulously analyze and model this dataset, and develop predictive models that can accurately identify probable churners. The findings illustrate the manner in which AI and ML have revolutionized telecommunications industry, not just in terms of predicting client churn but also in fostering a culture of data-driven decision making. Telecommunications companies can employ these technologies to proactively manage customer attrition, optimize promotional strategies, and elevate overall service quality, ultimately ensuring customer loyalty and achieving sustainable growth in a highly competitive market. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4619 |
| Topical term or geographic name entry element | EXTC Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 27029 |
| Co-Author | Maragathameena, R. |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Hyderabad IUP Publications |
| International Standard Serial Number | 0975-5551 |
| Title | IUP Journal of telecommunications |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://iupindia.in/ViewArticleDetails.asp?ArticleID=7704 |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 11/08/2025 | 2025-1296 | 11/08/2025 | 11/08/2025 | Articles Abstract Database |