AMiner Academic Data Search (學術資料查詢)

AMiner is a leading global academic data platform. This skill covers all 28 open APIs organized into 6 practical workflows for comprehensive academic research.

• API Docs: https://open.aminer.cn/open/doc
• Console (Token): https://open.aminer.cn/open/board?tab=control

Getting Started

1. Get API Token

1. Visit AMiner Console
2. Login and generate an API Token
3. Token goes in Authorization header for all requests

2. Quick Usage

# Scholar profile analysis
python scripts/aminer_client.py --token <TOKEN> --action scholar_profile --name "Andrew Ng"

# Paper deep dive (with citation chain)
python scripts/aminer_client.py --token <TOKEN> --action paper_deep_dive --title "Attention is all you need"

# Organization analysis
python scripts/aminer_client.py --token <TOKEN> --action org_analysis --org "清華大學"

# Venue/journal paper monitoring
python scripts/aminer_client.py --token <TOKEN> --action venue_papers --venue "Nature" --year 2024

# Academic Q&A (natural language)
python scripts/aminer_client.py --token <TOKEN> --action paper_qa --query "transformer架構最新進展"

# Patent search
python scripts/aminer_client.py --token <TOKEN> --action patent_search --query "量子計算"

Reliability & Error Handling

Built-in resilience:

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• Timeout: 30s default
• Retries: Max 3 with exponential backoff (1s → 2s → 4s) + jitter
• Retryable: 408 / 429 / 500 / 502 / 503 / 504
• Degradation: paper_deep_dive auto-falls back to paper_search_pro; paper_qa degrades to paper_search_pro
• Traceability: Composite workflow output includes source_api_chain

Paper Search API Selection Guide

Recommended routing:

1. Known title → paper_search → paper_detail → paper_relation
2. Condition filter → paper_search_pro → paper_detail
3. Natural language → paper_qa_search (fallback: paper_search_pro)
4. Venue analysis → venue_search → venue_paper_relation → paper_detail_by_condition

6 Composite Workflows

1. Scholar Profile (學者全景分析)

Use: Complete academic profile of a scholar.

Scholar Search (name → person_id)
    ↓
Parallel:
  ├── Scholar Detail (bio/education/honors)
  ├── Scholar Figure (research areas/interests)
  ├── Scholar Papers (publication list)
  ├── Scholar Patents (patent list)
  └── Scholar Projects (grants/funding)

python scripts/aminer_client.py --token <TOKEN> --action scholar_profile --name "Yann LeCun"

2. Paper Deep Dive (論文深度挖掘)

Use: Full paper info + citation chain.

Paper Search (title → paper_id)
    ↓
Paper Detail (abstract/authors/DOI/venue/year)
    ↓
Paper Citations (cited papers → cited_ids)
    ↓
(Optional) Batch paper info for cited papers

python scripts/aminer_client.py --token <TOKEN> --action paper_deep_dive --title "BERT"

3. Organization Analysis (機構研究力分析)

Use: Analyze an institution's research capabilities.

Org Disambiguation Pro (raw string → org_id)
    ↓
Parallel:
  ├── Org Detail (intro/type/founded)
  ├── Org Scholars (scholar list)
  ├── Org Papers (paper list)
  └── Org Patents (patent list, up to 10k)

python scripts/aminer_client.py --token <TOKEN> --action org_analysis --org "MIT"

4. Venue Papers (期刊論文監控)

Use: Track papers from a specific journal/venue by year.

Venue Search (name → venue_id)
    ↓
Venue Detail (ISSN/type/abbreviation)
    ↓
Venue Papers (venue_id + year → paper_ids)
    ↓
(Optional) Batch paper details

python scripts/aminer_client.py --token <TOKEN> --action venue_papers --venue "NeurIPS" --year 2023

5. Paper Q&A (學術智慧問答)

Use: Natural language academic search.

Supports: query (natural language), topic_high/middle/low (keyword weights), sci_flag, force_citation_sort, author_terms, org_terms.

python scripts/aminer_client.py --token <TOKEN> --action paper_qa \
  --query "用於蛋白質結構預測的深度學習方法"

6. Patent Analysis (專利鏈分析)

Use: Search patents by technology domain.

Patent Search (query → patent_id)
    ↓
Patent Detail (abstract/filing date/assignee/inventor)

python scripts/aminer_client.py --token <TOKEN> --action patent_search --query "量子計算晶片"

Full API Reference

Base URL: https://datacenter.aminer.cn/gateway/open_platform

References

• Official Docs: https://open.aminer.cn/open/doc
• Console: https://open.aminer.cn/open/board?tab=control

這個Skill質量中等偏上，文件寫得非常詳細清楚，工作流設計實用，錯誤處理考慮周全。但最大的問題是它只提供了說明書，缺少能直接執行的程式程式碼，所以沒法真正使用。如果你需要的是一份學術搜尋API的參考手冊，它很合適；但如果想要一個能直接呼叫的工具，目前還做不到。