This article presents a data‑driven approach to predict weekly vegetable sales, determine optimal restocking quantities, and set cost‑plus pricing strategies using time‑series analysis, correlation mining, and profit maximization models for supermarkets.
This article outlines a research framework for identifying price‑driving factors, building mathematical models to define reasonable price ranges for individual goods and regions, and evaluating whether Shanghai’s lockdown‑era commodity prices were excessive, ultimately offering policy recommendations for future emergencies.
This presentation details how Beike Rental leverages big data and machine‑learning techniques to detect non‑authentic listings, build a four‑criterion true‑listing model, develop pricing and image‑analysis models, and design a merchant credit scoring system that improves service quality and market efficiency.
This article explains how a knowledge graph for second‑hand e‑commerce is built—from data extraction and entity, attribute, and relation mining to ontology construction, entity alignment, and graph integration—and describes how the resulting graph supports personalized recommendation, search optimization, and statistical or regression‑based pricing models.
