Crime & Justice Website Classification API Label Taxonomy Design

You need to automatically detect and act on Crime & Justice content across the open web: block signups from certain sites, flag ad placements for brand safety, or enrich a lead with relevant industry signals. By the end of this guide, you’ll have a working path to call the Klazify categorize endpoint, interpret its category labels and confidence, and turn those into yes/no filters for a “Crime & Justice” label taxonomy you control.

Why Klazify excels at classifying Crime & Justice content

When your workflow depends on accurately recognizing Crime & Justice topics (e.g., criminal law resources, court systems, public safety, legal aid), you need an API that can parse full site content, not just a homepage title. Klazify focuses on developer-ready signals that fit Crime & Justice use cases:

• Accurate website categorization using AI: The API analyzes page content, semantic context, and structure, enabling precise detection of nuanced Crime & Justice topics that aren’t always obvious from metadata alone.
• Global coverage: Many Crime & Justice resources are local to jurisdictions and published in multiple languages. Klazify’s language-agnostic approach supports classifying those sites consistently.
• Real-time classification: Crime & Justice websites (e.g., government advisories, legal updates) change frequently. Klazify provides fresh categorization rather than relying on static lists.
• Industry-level categories with IAB mapping: You can align Crime & Justice content to IAB taxonomy for ad tech and brand safety controls, while still keeping your internal Crime & Justice label set intact.
• Simple API integration: A single REST call gives you categories, company metadata, logo URLs, related domains, and more—ideal for pipelines that must enrich and filter at the same time.
• Compliance and filtering: Use category paths and confidence scores to detect, filter, or whitelist relevant sites, enabling safe-by-default experiences without hand-curated blocklists.

If you’re building brand safety rules, content filtering, CRM enrichment, or analytics around Crime & Justice topics, Klazify provides the categorization primitives and web signals to get you there fast. Create a free account to test live requests now: Register.

The scenario: block, enrich, and audit Crime & Justice content

Let’s anchor the problem to three common pipelines:

• Brand safety enforcement: Before bidding or serving an ad, ensure the destination page does not belong to your restricted Crime & Justice segments (or does, if you target public-interest campaigns).
• Signup and lead enrichment: When a new company signs up, enrich their domain to identify if they operate in or around Crime & Justice topics; route to the right sales or compliance queue.
• Network filtering: On a corporate or school network, apply stricter controls or monitoring on specified Crime & Justice categories per policy, while allowing neutral legal resources.

All three require quick, repeatable answers: what are the site’s categories, how confident are they, and what organizational data can support a decision? Klazify’s categorize endpoint returns hierarchical categories, IAB mappings, and useful per-domain context in one response.

Call the categorize endpoint with a Crime & Justice example

Use the main endpoint to classify a specific URL (page-level) or a root domain (domain-level). For Crime & Justice content, you can target public-sector domains, legal information sites, or NGOs. Below is a complete curl you can copy and run:

curl -X POST "https://www.klazify.com/api/categorize" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url":"https://www.justice.gov/"}'

Notes:

• Authorization: Provide a Bearer token. Replace YOUR_API_KEY with your key.
• Body: Pass a JSON object with a single url field. You can submit a root domain or a full path; Klazify supports both domain and URL classification.
• Timeouts and retries: Set client timeouts and retry logic in your application; see the Documentation for connection guidance.

Understand the JSON response and the fields that matter

Use the following official example to understand the structure. The category values here are for an unrelated domain, but the shape of the response is the same you will parse for Crime & Justice workflows. Do not change field names when integrating.

{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}

How to use these fields for Crime & Justice decisions:

• domain.categories: Each element has a hierarchical category name and a confidence score. Your decision logic checks whether any category path matches your Crime & Justice taxonomy list. Confidence helps you tune thresholds.
• IAB mapping: When present (e.g., the field with key IAB-632-596 above), you can link the site to an IAB taxonomy code string. If your ad tech stack expects IAB terms, use these to drive block/allow rules.
• domain.logo_url: Retrieve a logo for UI display or analyst workflows when reviewing flagged domains.
• objects.company: Enrichment data (name, location, size, tags, tech) aids routing and scoring. For example, if a domain matches Crime & Justice categories and company tags support that context, prioritize for compliance review.
• domain_registration_data: Use age and expiration data as auxiliary risk inputs (e.g., very new domains in sensitive categories might be flagged for human review).
• similar_domains: Expand coverage by evaluating adjacent domains for the same decision. This is useful for whitelisting well-known public sector or legal resources, or broadening blocklists.

Turn categories into a yes/no Crime & Justice label

You likely maintain your own taxonomy, where “Crime & Justice” is a top-level label that maps to a set of hierarchical category paths and/or IAB strings. Keep this mapping in configuration (e.g., YAML, JSON, or a DB table) so policy can evolve without redeploying code. Your logic should:

• Normalize the returned category name strings (case, whitespace) and check prefix matches against your known Crime & Justice category paths.
• Optionally inspect any present IAB mapping fields for direct inclusion in your label’s allow/block sets.
• Use a confidence threshold to reduce false positives. For example, require at least one match above a configured threshold, or use a weighted combination across categories.
• Fallback to “unknown” handling for uncategorized or low-confidence results, routing them to manual review or a soft policy.

Python example: classify as Crime & Justice yes/no

This sample calls the same endpoint, reads categories, and applies an external mapping to output a boolean decision. Integrate it as a microservice or a step in your ETL.

import json
import os
import requests

API_KEY = os.getenv("KLAZIFY_API_KEY", "YOUR_API_KEY")
API_URL = "https://www.klazify.com/api/categorize"

# Load your Crime & Justice category prefixes and IAB terms from config.
# Keep this list in a file or database so policy owners can update without code changes.
# Example structure (do not hardcode real names here if you manage them elsewhere):
CRIME_JUSTICE_PREFIXES = set([
# e.g., "/<Your Hierarchy>/<Crime & Justice>/..."
# Populate from your internal mapping repository
])

CRIME_JUSTICE_IAB_TERMS = set([
# e.g., strings present in IAB mapping fields when available
])

CONFIDENCE_THRESHOLD = 0.70 # tune to your risk tolerance

def is_crime_justice(categories):
"""
Decide if the site falls under your Crime & Justice label.
categories: list of dicts with 'name', 'confidence', and optional IAB-mapped fields.
"""
decision = False
evidence = []

for cat in categories:
name = cat.get("name", "")
conf = float(cat.get("confidence", 0.0))

# Match by category path prefix
if any(name.startswith(prefix) for prefix in CRIME_JUSTICE_PREFIXES) and conf >= CONFIDENCE_THRESHOLD:
decision = True
evidence.append({"type": "category", "value": name, "confidence": conf})

# Match by any IAB-* field present
for key, value in cat.items():
if key.startswith("IAB-"):
if value in CRIME_JUSTICE_IAB_TERMS and conf >= CONFIDENCE_THRESHOLD:
decision = True
evidence.append({"type": "iab", "value": value, "confidence": conf})

return decision, evidence

def categorize(url):
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
}
payload = {"url": url}
resp = requests.post(API_URL, headers=headers, data=json.dumps(payload), timeout=15)
resp.raise_for_status()
data = resp.json()
return data

if __name__ == "__main__":
test_url = "https://www.justice.gov/"
data = categorize(test_url)

categories = data.get("domain", {}).get("categories", [])
decision, evidence = is_crime_justice(categories)

print("URL:", test_url)
print("Decision:", "CRIME_JUSTICE" if decision else "NOT_CRIME_JUSTICE")
print("Evidence:", json.dumps(evidence, indent=2))
print("Logo URL:", data.get("domain", {}).get("logo_url"))
print("Company:", data.get("objects", {}).get("company", {}).get("name"))
print("Similar domains:", data.get("similar_domains"))

What to do with the outputs:

• decision: Gate access, apply brand safety blocks, or route the lead to the right queue.
• evidence: Log the matched category paths/IAB strings with confidence for auditors.
• logo_url: Display to analysts or in CRM profiles to speed manual review.
• objects.company: Enrich your CRM and analytics models with company attributes and tags.
• similar_domains: Seed further checks to expand allow/block decisions quickly.

Field-to-action mapping for Crime & Justice workflows

Operational details: batching, caching, and handling unknowns

Batching at scale

The categorize endpoint is called per URL/domain. For high throughput, use client-side batching strategies:

• Parallel requests: Run requests concurrently with connection pooling. Control concurrency to stay within your plan’s limits.
• Queueing: Buffer incoming domains and process in workers to maintain steady throughput without bursts.
• Deduplication: Before sending, hash and dedupe domains to avoid duplicate lookups within a time window.

Always adhere to your plan’s rate and usage policies. If you experience 429 or similar throttling responses, apply exponential backoff and jitter, and persist failed items for retry.

Caching per domain

Crime & Justice content does change, but many domains are stable day to day. Cache classifications per root domain and optionally per URL path:

• Domain-level cache TTL: Use a TTL aligned with how fast you expect content to change (e.g., hours to days). Revalidate on cache expiry or upon important events.
• URL-level cache: For large publishers with diverse sections, cache per path to get accurate, page-level categorization.
• Versioned policy: Store the mapping version used at decision time to ensure reproducible audits even if your taxonomy evolves.

Handling unknown or new domains

• Unknown classification: If domain.categories is empty or below threshold, mark as “unknown” and apply conservative defaults. Optionally queue for recheck.
• Escalation: For high-impact workflows (e.g., ads), route unknowns to review or sandbox until classification is confirmed.
• Warmup runs: Pre-scan high-traffic or newly observed domains periodically so production requests hit a warm cache.

Mapping to your own taxonomy

Most teams maintain an internal Crime & Justice label that maps to multiple hierarchical categories and IAB strings. Recommended approach:

• Configuration-first: Keep mappings outside code (YAML/JSON/DB) and load them at startup.
• Prefix semantics: Match category paths by prefix to include all relevant sub-branches under your Crime & Justice label.
• IAB bridging: Where IAB mappings exist, attach them to your label to align with ad tech policies.
• Confidence policy: Define minimum confidence thresholds globally and per sub-label if needed.
• Auditability: Log matched categories, IAB terms, confidence, input URL, and mapping version for review.

Putting it together: end-to-end path to a decision

1. Receive a URL or domain from your pipeline (ad placement, signup, or network event).
2. Check your cache. If miss, POST to https://www.klazify.com/api/categorize with the URL in the body and a Bearer token.
3. Parse domain.categories[].name and .confidence. If present, also read IAB-*-mapped fields.
4. Apply your Crime & Justice mapping:
   • If any path or IAB term matches above your threshold, mark as Crime & Justice = yes.
   • If none match but confidence is low, mark unknown and follow your escalation policy.
   • Otherwise, mark as not Crime & Justice.
5. Optionally enrich your records with objects.company, logo_url, domain_registration_data, and similar_domains.
6. Cache the result keyed by domain and optionally by path with a reasonable TTL.
7. Log evidence and mapping version for audit and analytics.

Example: using the response fields after classification

Assume your policy marks the site as Crime & Justice = yes. Here’s how you might act:

• Brand safety: Add a label to the bid request context for your ad server or bidder to exclude or include per campaign rules.
• Signup enrichment: If objects.company is present, set CRM fields (industry tags, company size), attach the logo_url for the profile, and apply a risk or ownership routing rule.
• Filtering: On a managed network, move the session into a policy tier that enforces reporting or access rules suitable for Crime & Justice browsing.

For more API details, see the Documentation. If you need support for model lifecycle or integration patterns, visit MCP.

Reliability and pipeline notes engineers ask about

• Idempotency: Hash inputs and reuse results to avoid duplicate requests under retries.
• Backpressure: Implement bounded queues and concurrency caps so upstreams don’t overwhelm your classifier step.
• Observability: Emit metrics for success, latency, error rates, and category hit rates by label. Log sample payloads with PII-safety.
• Data quality: Track the percentage of unknowns. If it rises, reassess thresholds and refresh mappings.
• Security: Store the API key securely, rotate on a regular cadence, and scope usage to your service.

curl you can copy and paste

curl -X POST "https://www.klazify.com/api/categorize" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url":"https://www.justice.gov/"}'

Replace YOUR_API_KEY with your key. For team access, create a free account here: Register.

FAQ

• How should I set confidence thresholds?
  Start with a single global threshold and measure false positives/negatives against your label. If needed, set stricter thresholds for sensitive sub-labels. Always log evidence for audits.
• What if a site spans multiple categories?
  Treat domain.categories as a set. If any category path or IAB mapping matches your Crime & Justice mapping above threshold, mark it as a match and record the evidence. You can also use weighted combinations.
• Can I classify individual article URLs, not just domains?
  Yes. Send the full URL in the request body. Cache page-level results separately from domain-level results.
• How do I avoid reclassifying the same domains repeatedly?
  Implement a cache with TTL and dedup requests per batch window. Revalidate on expiry or when you detect significant site changes.
• How can I map the results to my ad tech taxonomy?
  Use the category path and any IAB-mapped fields in the response. Keep a central mapping file that aligns Klazify outputs to your inventory labels and buyer policies.

Ready to classify Crime & Justice content at scale? Explore the Documentation, and create a free account to get your API key: Register. For implementation patterns and model control, check MCP. Visit https://www.klazify.com to learn more.