Predicting Churners from the User Base of a Business - A Review (Record no. 10098)
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| fixed length control field | a |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20191116093708.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 191116b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 10501 |
| Author | Saima Jan |
| 245 ## - TITLE STATEMENT | |
| Title | Predicting Churners from the User Base of a Business - A Review |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.6(2), May-Aug |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | New Delhi |
| Name of publisher, distributor, etc. | STM Journals |
| Year | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 8-16p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Customer churn prediction and management is a foremost job aimed by enterprises to maintain cost-effective customers and thus many customer churn prediction models are developed which aim to categorize consumers as non-churners or churners & then retention actions are taken to prevent churners from churning. The data from different companies like Telecommunication Company, financial company, Retail Company etc. can be used to discover valuable patterns which predict the customers’ relationship with the company. From this data customers behavior can be used to predict his loyalty with the company. In this paper different techniques & approaches are discussed given by different researchers to predict churners, so as to apply retention strategies on them. This paper also presents the results that were recorded by various researchers in their research. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 10500 |
| Co-Author | Khan, Afaq Alam |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Noida STM Journals |
| Title | Journal of artificial intelligence research and advances (JoAIRA) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | http://computers.stmjournals.com/index.php?journal=JoAIRA&page=article&op=view&path%5B%5D=2152 |
| 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 |
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| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 16/11/2019 | 2020166 | 16/11/2019 | 16/11/2019 | Articles Abstract Database |