Related papers: Optimizing Web Sites for Customer Retention
In today's competitive scenario in corporate world, "Customer Retention" strategy in Customer Relationship Management (CRM) is an increasingly pressed issue. Data mining techniques play a vital role in better CRM. This paper attempts to…
Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies in this information age. Data mining technologies extract hidden…
The increasing use of synthetic data from the public Internet has enhanced data usage efficiency in large language model (LLM) training. However, the potential threat of model collapse remains insufficiently explored. Existing studies…
This paper presents an integrated framework that combines traditional network optimization models with large language models (LLMs) to deliver interactive, explainable, and role-aware decision support for supply chain planning. The proposed…
Large recommendation models (LRMs) are fundamental to the multi-billion dollar online advertising industry, processing massive datasets of hundreds of billions of examples before transitioning to continuous online training to adapt to…
Personalization is being applied to great extend in many systems. This paper presents a multi-dimensional user data model and its application in web search. Online and Offline activities of the user are tracked for creating the user model.…
Click-through rate (CTR) prediction aims to predict the probability that the user will click an item, which has been one of the key tasks in online recommender and advertising systems. In such systems, rich user behavior (viz. long- and…
Businesses heavily rely on data sourced from various channels like news articles, financial reports, and consumer reviews to drive their operations, enabling informed decision-making and identifying opportunities. However, traditional…
Cross-Domain Sequential Recommendation (CDSR) aims to mine and transfer users' sequential preferences across different domains to alleviate the long-standing cold-start issue. Traditional CDSR models capture collaborative information…
Online advertisement is the main source of revenue for Internet business. Advertisers are typically ranked according to a score that takes into account their bids and potential click-through rates(eCTR). Generally, the likelihood that a…
Recommending the right products is the central problem in recommender systems, but the right products should also be recommended at the right time to meet the demands of users, so as to maximize their values. Users' demands, implying strong…
Healthcare organization is implementing Customer Relationship Management (CRM) as a strategy for managing interactions with patients involving technology to organize, automate, and coordinate business processes. Web-based CRM provides…
It is of high interest for a company to identify customers expected to bring the largest profit in the upcoming period. Knowing as much as possible about each customer is crucial for such predictions. However, their demographic data,…
This paper aims to determine how the LMS Web portal application reshapes the learner experience through the developed E-Learning Management System using Data Mining Algorithm. The methodology that the researchers used is descriptive…
In recent years, many industries have utilized machine learning (ML) models in their systems. Ideally, ML models should be trained on and applied to data from the same distributions. However, the data evolves over time in many application…
Recently, peoples awareness of online purchases has significantly risen. This has given rise to online retail platforms and the need for a better understanding of customer purchasing behaviour. Retail companies are pressed with the need to…
For a successful business, engaging in an effective campaign is a key task for marketers. Most previous studies used various mathematical models to segment customers without considering the correlation between customer segmentation and a…
Training Learning-to-Rank models for e-commerce product search ranking can be challenging due to the lack of a gold standard of ranking relevance. In this paper, we decompose ranking relevance into content-based and engagement-based…
Generating accurate and reliable sales forecasts is crucial in the E-commerce business. The current state-of-the-art techniques are typically univariate methods, which produce forecasts considering only the historical sales data of a single…
How to manage various data in a unified way is a significant research topic in the field of databases. To address this problem, researchers have proposed multi-model databases to support multiple data models in a uniform platform with a…