ai initial proposal

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YELP! R02725004 楊筑雅 R02921073 鍾家涵 R02921078 柯有容 Tuesday, November 26, 2013

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YELP!R02725004 楊筑雅R02921073 鍾家涵R02921078 柯有容

Tuesday, November 26, 2013

What We Will Do

• Let business know which parts need to care more(business-driven)

• Add and rank tags on each review (e.g., taste, hygiene)

• Classify top 10 and worst 10 frequently show up keywords

• Distinguish the review based on the users

Tuesday, November 26, 2013

Why We Want to Do It

• Business can get the opinion from users from the reviews, without questionary usage

• Review’s rating is not specific, and the rating is subjective

• There lies a lot of hidden information within the reviews

• The classified data (result data) may had further improvement

Tuesday, November 26, 2013

How We Do It

Classification

POS+LDA

Rating

Evalutaion

Tuesday, November 26, 2013

What we will do

從review 分種類,(e.g, 服務, 好吃程度),做出評分,舉出具體例,判別出關鍵字(店員名稱)

4. top 10 or worst 10 frequent show up word讓餐廳知道有沒有(多寡)老饕留review

網站demoCategories

1. taste- beverage- main-dish-sub-dish2. service3. hygiene

4. atmosphere5. cp value

business-driven

Tuesday, November 26, 2013

1. 消費者不必填問卷,沒有意見不用硬填

Why

2. 店家可快速得到整理後分類的結果3. 整體評分不夠具體,可信度也不高 (may improved by

老饕)

4. hidden information retrieval from review5. open the classified data (result data) for further

improvement

Tuesday, November 26, 2013

How

1. LDA

2. Checkin re-check

3. keyword classification

4. POS

Tuesday, November 26, 2013