Name: Housing voucher resettlement policy dataset
Creator: Changsha Langhui Information Technology Co., Ltd.
Keywords: housing voucher, expropriation, urban renewal, policy analysis

Dataset Overview

Dataset Name	Housing Voucher Resettlement Policy Dataset
Total Data Volume	12,600 (policy documents + implementing rules + operational guidelines + case bank)
Coverage	National system of housing policy at the provincial/autonomous/municipal/county level
Time Span	2015 - 2026 (continuously updated)
Data Source	Public communications from government officials, natural resources, housing, and public sector bodies
Level of structuring	Full-Structure Field + Original Text Comparison
Annotation Method	Policy analyst + double-checking by legal professionals
Format Output	JSON / CSV / XML / Knowledge Graph Triple Set

Detailed Description of Data Dimensions

Field Name	Data Type	Value Range / Description
policy_id	String(32)	Policy exclusive ID
policy_title	Text	Full title of policy document
issuing_body	String	Issuing bodies (e.g., People's Government of XX)
administrative_level	Enum	NATIONAL \| PROVINCE \| CITY \| COUNTY
region	String	Administrative Division (provincial/municipal/county)
publish_date	Date	Release Date
effective_date	Date	Effective date
policy_status	Enum	DRAFT \| ACTIVE \| REVISED \| EXPIRED \| REPEALED
voucher_face_value	Object	{min, max, unit, calculation_method}
eligible_properties	Array	List of available source types: RESIDENTIAL · COMMERCIAL · PARKING
compensation_standard	Object	{base_rate, adjustment_factors, bonus_policy}
transfer_restrictions	Object	{transferable, min_holding_period, max_transfers}
key_clauses	Array	[{clause_type, summary, original_text, legal_basis}]
related_policies	Array	List of associated policies

De-identified JSON Data Sample

[ { "policy_id": "HVP-2024-GD-SZ-001", "policy_title": "Shenzhen urban-renewal housing-voucher resettlement rules", "issuing_body": "Shenzhen Housing and Construction Bureau", "administrative_level": "CITY", "region": "[]-[Shenzhen]", "publish_date": "2024-03-15", "effective_date": "2024-05-01", "policy_status": "ACTIVE", "voucher_face_value": { "min": 500000, "max": 5000000, "unit": "CNY", "calculation_method": "appraised value of expropriated housing × 1.2 + " }, "eligible_properties": ["RESIDENTIAL", "COMMERCIAL"], "compensation_standard": { "base_rate": "[]120%", "adjustment_factors": ["[]", "[]", "[]resettlement[]"], "bonus_policy": "30[]8%" }, "transfer_restrictions": { "transferable": true, "min_holding_period": "6[]", "max_transfers": 1 }, "key_clauses": [ {"clause_type": "scope of application", "summary": "urban renewalhousing expropriation"}, {"clause_type": "[]", "summary": "=appraised value of expropriated housing×1.2+"} ], "related_policies": ["HVP-2023-GD-SZ-005"] }, { "policy_id": "HVP-2023-ZJ-HZ-002", "policy_title": "Hangzhouhousing voucherresettlement", "issuing_body": "[Hangzhou]Reg[] and []", "administrative_level": "CITY", "region": "[Zhejiang]-[Hangzhou]", "publish_date": "2023-08-22", "effective_date": "2023-10-01", "policy_status": "ACTIVE", "voucher_face_value": { "min": 300000, "max": 3000000, "unit": "CNY", "calculation_method": "resettlement[] × [] + []" }, "eligible_properties": ["RESIDENTIAL"], "compensation_standard": { "base_rate": "[]105%", "adjustment_factors": ["[]", "[]"], "bonus_policy": "[]housing voucherresettlement[]resettlement[]10%" }, "transfer_restrictions": { "transferable": false, "min_holding_period": null, "max_transfers": null }, "key_clauses": [ {"clause_type": "[]", "summary": "housing voucher24，resettlement"} ], "related_policies": ["HVP-2022-ZJ-001"] }, { "policy_id": "HVP-2024-HN-CS-003", "policy_title": "Changsha[]housing voucherresettlement[]", "issuing_body": "Changsha[]urban renewal[]", "administrative_level": "CITY", "region": "[]-Changsha[]", "publish_date": "2024-06-10", "effective_date": "2024-07-01", "policy_status": "ACTIVE", "voucher_face_value": { "min": 200000, "max": 2500000, "unit": "CNY", "calculation_method": " × 1.0 + " }, "eligible_properties": ["RESIDENTIAL", "PARKING"], "compensation_standard": { "base_rate": "", "adjustment_factors": ["[]", "[]"], "bonus_policy": "housing voucher[]50%" }, "transfer_restrictions": { "transferable": true, "min_holding_period": "12[]", "max_transfers": 1 }, "key_clauses": [ {"clause_type": "[]", "summary": "、3"} ], "related_policies": [] }, { "policy_id": "HVP-2022-JS-NJ-004", "policy_title": "Nanjinghousing voucherresettlementLaw", "issuing_body": "[Nanjing]Reg[] and []", "administrative_level": "CITY", "region": "[]-[Nanjing]", "publish_date": "2022-11-01", "effective_date": "2023-01-01", "policy_status": "REVISED", "voucher_face_value": { "min": 250000, "max": 4000000, "unit": "CNY", "calculation_method": "resettlement[] × []resettlement[]" }, "eligible_properties": ["RESIDENTIAL"], "compensation_standard": { "base_rate": "resettlement[]", "adjustment_factors": ["[]", "[]"], "bonus_policy": "housing voucher[]" }, "transfer_restrictions": { "transferable": true, "min_holding_period": "[]", "max_transfers": 2 }, "key_clauses": [ {"clause_type": "[]Description", "summary": "2024scope of application"} ], "related_policies": ["HVP-2024-JS-NJ-007"] }, { "policy_id": "HVP-2025-SC-CD-005", "policy_title": "[Chengdu]housing voucherresettlementFull Workflow[]（[]）", "issuing_body": "[Chengdu] and []", "administrative_level": "CITY", "region": "[]-[Chengdu]", "publish_date": "2025-02-20", "effective_date": "2025-04-01", "policy_status": "ACTIVE", "voucher_face_value": { "min": 150000, "max": 3500000, "unit": "CNY", "calculation_method": "appraised value of expropriated housing + " }, "eligible_properties": ["RESIDENTIAL", "COMMERCIAL", "PARKING"], "compensation_standard": { "base_rate": "[]", "adjustment_factors": ["[]", "[]"], "bonus_policy": "housing voucherresettlement9.5" }, "transfer_restrictions": { "transferable": true, "min_holding_period": "6[]", "max_transfers": 1 }, "key_clauses": [ {"clause_type": "[]", "summary": "housing voucher，"} ], "related_policies": ["HVP-2024-SC-003"] } ]

AI Training Use Cases

Policy Intelligence Q&A (Policy QA)

Applied model: RAG + LLM (Langchain + GPT-4o/Qwen2.5). Build a knowledge base on housing voucher policy, enabling multi-role intelligent Q&A for collectors, developers, and government workers.

Policy comparative analysis

Applied model: Sentence-BERT + text clustering / Legal-BERT. Automatically compare differences in urban housing voucher policies, generate policy comparison reports, and provide best-practice recommendations.

Compensation estimation

Applied models: Rule engine + XGBoost/TabNet. Based on structured policy parameters and case data, the model is trained for forward estimation of compensation payments, supporting collection decisions.

Policy knowledge graphs

Applied models: REBEL/Casarel + Neo4j. Extracts entities and relationships from unstructured policy texts and constructs searchable, verifiable policy knowledge graphs.

Get This Dataset

The housing voucher policy dataset provides full delegation of authority, with customizable area subsets and update frequency as required.

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Commercial Application Value

Land acquisition and resettlement platforms

Provides intelligent policy matching and compensation schemes for the collection management system to generate automated decisions, increasing the efficiency of the collection project by 35%.

Housing market research

Helps real estate enterprises quickly understand the differences in urban housing policies and accurately assess the feasibility of investment in urban renewal projects.

Legal service automation

Policy retrieval and case matching tools for law firms, revenue collection and evaluation agencies reduce the cost of legal research by 60%.

Housing Voucher Policy Dataset

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Housing Voucher Resettlement Policy Dataset