SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Churn modeling with probabilistic meta paths-based representation learning · Study

ArticleShelves

ArticleChurn modeling with probabilistic meta paths-based representation learning

Sandra Mitrović2019

OA

Articlegreen2019

Churn modeling with probabilistic meta paths-based representation learning

Sandra Mitrović · Jochen De Weerdt

19 citations·0/0 files stored·Information Processing & Management

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Customer churn and segmentation Recommender Systems and Techniques Advanced Graph Neural Networks

Abstract

No abstract was published for this record.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 19 citations exist upstream.

References

2008Classifying the segmentation of customer value via RFM model and RS theory 2008Social ties and their relevance to churn in mobile telecom networks 2007Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression 2013Social network analysis for customer churn prediction 2012A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data 2015Telco Churn Prediction with Big Data 1994Strategic Database Marketing: The Masterplan for Starting and Managing a Profitable, Customer-Based Marketing Program 2014Improved churn prediction in telecommunication industry by analyzing a large network

Cited by

2022A Counterfactual Modeling Framework for Churn Prediction 2025A comprehensive survey on customer churn analysis studies 2024Factors, Predictability, and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature

Related works

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2019tcc2vec: RFM-informed representation learning on call graphs for churn predictionarticle · 9 shared references 2017Churn Prediction Using Dynamic RFM-Augmented Node2vecother · 8 shared references 2017Scalable RFM-enriched Representation Learning for Churn Predictionother · 7 shared references 2017On the operational efficiency of different feature types for telco Churn predictionarticle · 5 shared references 2023Churn prediction methods based on mutual customer interdependencearticle · 5 shared references 2015Combining Local and Social Network Classifiers to Improve Churn Predictionother · 5 shared references

Details

Year2019

Typearticle

Published2019-06-22

VenueInformation Processing & Management

ISSN-L0020-0271

Languageen

Citations19

Files0 public / 0

ShelfCustomer churn and segmentation

Identifiers

doi10.1016/j.ipm.2019.06.001

openalex_workW2950164091

Links

Imported from OpenAlex (CC0) — nothing here is generated.