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# System prepended metadata

title: 'AliCoCo: Alibaba E-commerce Cognitive Concept Net (SIGMOD-2020)'

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# AliCoCo: Alibaba E-commerce Cognitive Concept Net (SIGMOD-2020)

- 4 Parts
  -  Items (Product)
  -  Taxonomy: Manual Defined High level category/attributes, e.g., Category->Dress, Time->Holiday, Time->Season, IP->Movie Star, Location, etc.
  -  Primitive Concept: Minied Lower level category/attributes, e.g., Outdoor, Barbecue, Winter, etc.
  -  E-commerce Concepts: scenarios, e.g., outdoor barbecue, christmas gifts

- Primitive Concept Discovery
  - data
    - get concept candidates from multiple sources: catalog attribute values, wikipedia, etc.
    - distance supervision training data (6M sentences)
      - matching attribute values with text (query/title/review)
      - remove text with multiple matching
  - model: learn BiLSTM-CRF model from distance supervision examples
  - apply: run prediction on sentences, getting 2.7M primitive concepts

- Learning Primitive Concept Hierarchy: Hypernym Discovery
  - algorithm: bi-linear matching
  - data: active-learning (both most confident ones and most uncertain ones)

- E-commerce Concepts
  - candidate generation
    - AutoPhrase detection (TBD) from query/title/review
    - Pattern generation based on Priminative Concepts
  - classify: is it a good concept?
    - model: Deep & Wide
      - Wide: meta features
      - Deep: LSTM of word embedding + wikipedia augmented Features
  
- Item Association
  - data: data pairs of (queries, Concepts associated with higly clicked products)
  - algorithm: text matching between query and concepts
