Xin Li Xiaoye Jin
TECHNOLOGY-‐STEP 1
Product features mining system
Mechanism: Finding different “words” describing “good quality” for different products
To find product features that considered to be useful in determining the customer’s purchase
Clothes
TV
TECHNOLOGY-‐STEP2
Customers preference mining system
To search customers preferences based on the history purchase
TECHNOLOGY-‐STEP 3 Product reviews ranking score system
To identify each review that have been commented on by customers
Mechanism: Presenting a product-ranking model that applies weights to product review factors to calculate products ranking score. Factors needed to be considered: Product Features, customer preference, helpful votes amount, post date and star rating.
There’s a good positive correlation (r = 0.26) between average helpfulness and average length, which the trend line supports.
Score Ranking Criteria 1000 words and above 600-1000 words 300-600 words 100-300 words 100 words and below
5 points 4 points 3 points 2 points 1 points
TECHNOLOGY-‐STEP 4 Top-reviews automated refreshed system
Integrating & positioning
Mechanism: Integrating the scores to find the “most important” reviews for individual customer and upgrading the ranking system periodically.