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SENA-Recommendation is a professional recommendation solution that provides optimized scenario-based recommended lists and visualization data by using a massive data set based on Big Data Platform.
SENA-Recommendation helps enterprises to satisfy their customers by examining their preferences, and helps end-customers to make better choices by providing personalized recommendations based on their purchase history.

Why SENA - Recommendation?

SENA - Recommendation

SENA-Recommendation provides fast big data processing based on Hadoop platform.

SENA - Recommendation

02. SENA-Recommendation maximizes the recommendation accuracy by using Hybrid Algorithms.

Recommended method for using high-level analysis

  • Period of product purchase
    • Average period of purchase for each product by individual
    • Recent period of purchase for each product by individual
    • Standard deviation of period of purchase for each product by individual
    • Period of purchase in consideration of volume, etc
  • Personal preference for products
    • CF(Collaborative filtering) algorithm used
  • Purchase forecasting model
    • Regression analysis algorithm used - Age groups, levels and purchase records utilized
    • Seasonal sales volume and sales volume in holiday season, sales share of each product utilized
  • Product association
    • AR (Association Rule) algorithm used - Calculate the association based on the purchase record information
SENA - Recommendation

03. SENA-Recommendation 추천성능 및 기본정보에 대한 다양한 Visualization 기능을 제공합니다. In addition, Recommendation lists with reasons why recommended are provided.

Use Case

  • Korea's leading Household & Healthcare Company
    • Personalized Recommendation Service

“SENA-Recommendation can simply applied to anywhere in any business where customer’s preference needs to be read. It is the most preferred solution for such enterprise which is eager in personalized marketing”


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