To retain consumer attention and increase their purchasing rates, many online e-commerce vendors haveadopted content-based approaches in their recommender systems. However, except text based documents,there are few theoretic background guiding the selection of elements. On the other hand, Mean End Chaintheory pointed out that deciding elements that dictate product selection include attributes, benefits, andvalues can be systematically identified.This study will strive to establish a methodology to recommend favorite attributes to users based on MECtheory. Two experiments will be conducted to compare and contrast the performance of the proposed methodand two traditional content (attribute) based methodologies.
|Effective start/end date||1/08/17 → 31/07/18|
- Content based recommender system
- Mean-end chain theory
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