Search and Discovery System - Give Protocol Documentation

This comprehensive guide covers Give Protocol’s advanced search and discovery features, helping users find relevant organizations, campaigns, and volunteer opportunities efficiently.

Overview

Give Protocol’s search and discovery system uses advanced algorithms, machine learning, and user behavior analysis to connect donors with causes they care about and match volunteers with meaningful opportunities.

Key Features

Intelligent Search: Natural language processing and semantic understanding
Personalized Recommendations: AI-driven matching based on interests and history
Advanced Filtering: Multi-dimensional filtering and sorting options
Real-time Results: Instant search with dynamic updates
Cross-entity Search: Find organizations, campaigns, and opportunities in one search

Search Architecture

Search Infrastructure

graph TD
    A[User Query] --> B[Query Parser]
    B --> C[NLP Processing]
    C --> D[Search Engine]
    D --> E[Elasticsearch Cluster]
    D --> F[ML Ranking Service]
    E --> G[Primary Results]
    F --> H[Personalized Ranking]
    G --> I[Result Merger]
    H --> I
    I --> J[Final Results]
    J --> K[User Interface]

Technology Stack

Search Engine: Elasticsearch 8.x
NLP Processing: spaCy and BERT models
Recommendation Engine: TensorFlow-based collaborative filtering
Caching Layer: Redis for frequent queries
Analytics: Apache Spark for behavior analysis

Search Functionality

Basic Search

Query Types Supported:

Simple keyword search
Phrase matching with quotes
Boolean operators (AND, OR, NOT)
Wildcards and fuzzy matching
Geographic search

Example Queries:

education "New York"
environmental AND conservation
volunteer opportunities near me
crypto-friendly charities
disaster relief -administrative

Advanced Search

Search Syntax:

field:value AND (field2:value2 OR field3:value3) NOT field4:value4

Searchable Fields:

name: Organization or campaign name
category: Cause category
location: Geographic location
tags: Associated tags
description: Full-text description
ein: Tax ID number (organizations)
verified: Verification status

Natural Language Processing

Understanding Intent:

// Query: "I want to help children in Africa with education"
{
  intent: "donate",
  cause: "education",
  beneficiary: "children",
  location: "Africa",
  sentiment: "positive"
}

Synonym Expansion:

“kids” → “children”, “youth”, “minors”
“help” → “support”, “assist”, “aid”
“education” → “schools”, “learning”, “literacy”

Discovery Features

Personalized Recommendations

Recommendation Algorithm:

def get_recommendations(user_id, context):
    # Collaborative filtering
    similar_users = find_similar_users(user_id)
    cf_recommendations = aggregate_preferences(similar_users)

    # Content-based filtering
    user_interests = get_user_interests(user_id)
    cb_recommendations = match_content(user_interests)

    # Hybrid approach
    recommendations = merge_recommendations(
        cf_recommendations,
        cb_recommendations,
        weights={'cf': 0.6, 'cb': 0.4}
    )

    # Context adjustment
    return adjust_for_context(recommendations, context)

Trend Calculation:

Recent donation velocity
Social media mentions
News coverage
Seasonal relevance
Emergency response needs

Categories:

Trending Now
Rising Stars
Seasonal Causes
Emergency Appeals
Local Highlights

Geographic Discovery

Location-Based Features:

Automatic location detection
Radius-based search
Regional cause mapping
Local volunteer opportunities
Community impact visualization

Map Integration:

// Initialize map view
const mapView = new GiveProtocolMap({
  center: userLocation,
  zoom: 12,
  layers: ["organizations", "opportunities", "events"],
});

// Add search results to map
mapView.addResults(searchResults, {
  clustering: true,
  heatmap: true,
  filters: activeFilters,
});

Filter System

Primary Categories:

Animals & Wildlife
Arts & Culture
Community Development
Disaster Relief
Education
Environment
Health & Medicine
Human Rights
International Aid
Religion & Spirituality

Sub-category Examples:

{
  "Education": [
    "Early Childhood",
    "K-12 Schools",
    "Higher Education",
    "Adult Literacy",
    "STEM Programs",
    "Special Education"
  ]
}

Advanced Filters

Organization Filters:

Verification level
Tax-deductible status
Size (budget/staff)
Years active
Transparency rating
Payment methods accepted

Campaign Filters:

Funding goal range
Deadline
Matching funds available
Progress percentage
Update frequency

Volunteer Filters:

Time commitment
Skill requirements
Virtual/in-person
Background check required
Age restrictions
Accessibility

Dynamic Filtering

// Real-time filter updates
const filterManager = new FilterManager({
  onChange: (filters) => {
    // Update results without page reload
    searchAPI.updateResults(filters);

    // Update URL for sharing
    updateURLParams(filters);

    // Track filter usage
    analytics.track("filter_applied", filters);
  },
});

// Smart filter suggestions
filterManager.suggestFilters(searchResults);

Ranking Algorithm

Relevance Scoring

Factors Considered:

Text Relevance (30%)
- Title matches
- Description relevance
- Tag alignment
User Behavior (25%)
- Click-through rate
- Conversion rate
- Dwell time
Entity Quality (20%)
- Verification status
- Completeness score
- Update recency
Social Signals (15%)
- User ratings
- Social shares
- Testimonials
Personalization (10%)
- User history
- Preference matching
- Behavioral patterns

Machine Learning Model

# Ranking model architecture
model = tf.keras.Sequential([
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(64, activation='relu'),
    tf.keras.layers.Dense(32, activation='relu'),
    tf.keras.layers.Dense(1, activation='sigmoid')
])

# Features include:
# - Query-document similarity
# - User engagement metrics
# - Entity characteristics
# - Temporal factors
# - User-entity affinity

Search API

Basic Search Endpoint

GET /api/v1/search

Parameters:

q (required): Search query
type: Entity type (organization, campaign, opportunity)
category: Filter by category
location: Geographic filter
radius: Distance in miles
verified: Verification status
sort: Sorting option
page: Page number
limit: Results per page

Example Request:

GET /api/v1/search?q=education&type=organization&location=NYC&radius=50&verified=true&sort=relevance&page=1&limit=20

Advanced Search Endpoint

POST /api/v1/search/advanced
Content-Type: application/json

{
  "query": {
    "must": [
      { "match": { "description": "education" } }
    ],
    "should": [
      { "match": { "tags": "STEM" } }
    ],
    "filter": [
      { "range": { "founded": { "gte": "2010" } } },
      { "term": { "verified": true } }
    ]
  },
  "sort": [
    { "_score": "desc" },
    { "rating": "desc" }
  ],
  "aggs": {
    "categories": {
      "terms": { "field": "category" }
    }
  }
}

Autocomplete Endpoint

GET /api/v1/search/autocomplete?q=educ

Response:
{
  "suggestions": [
    {
      "text": "education",
      "type": "category",
      "count": 1234
    },
    {
      "text": "Education First Foundation",
      "type": "organization",
      "id": "org_123"
    }
  ]
}

User Interface Components

Search Bar

<!-- Advanced search bar component -->
<div class="search-container">
  <input
    type="text"
    id="search-input"
    placeholder="Search causes, organizations, or opportunities..."
    autocomplete="off"
  />
  <div class="search-filters">
    <button class="filter-btn" data-filter="location">
      <i class="icon-location"></i> Near me
    </button>
    <button class="filter-btn" data-filter="verified">
      <i class="icon-verified"></i> Verified only
    </button>
  </div>
  <div id="search-suggestions" class="suggestions-dropdown"></div>
</div>

Result Display

// Result card component
const ResultCard = ({ result }) => (
  <div className="result-card">
    <div className="result-header">
      <img src={result.logo} alt={result.name} />
      <div className="result-title">
        <h3>{result.name}</h3>
        {result.verified && <VerifiedBadge />}
      </div>
    </div>
    <p className="result-description">
      {highlightMatches(result.description, searchQuery)}
    </p>
    <div className="result-meta">
      <span className="category">{result.category}</span>
      <span className="location">{result.location}</span>
      <span className="rating">★ {result.rating}</span>
    </div>
    <div className="result-actions">
      <button onClick={() => viewDetails(result.id)}>Learn More</button>
      <button onClick={() => quickDonate(result.id)}>Donate Now</button>
    </div>
  </div>
);

Filter Interface

// Dynamic filter component
const FilterPanel = ({ availableFilters, onFilterChange }) => {
  const [activeFilters, setActiveFilters] = useState({});

  const handleFilterChange = (filterType, value) => {
    const newFilters = {
      ...activeFilters,
      [filterType]: value,
    };
    setActiveFilters(newFilters);
    onFilterChange(newFilters);
  };

  return (
    <div className="filter-panel">
      {Object.entries(availableFilters).map(([type, options]) => (
        <FilterGroup
          key={type}
          type={type}
          options={options}
          selected={activeFilters[type]}
          onChange={(value) => handleFilterChange(type, value)}
        />
      ))}
    </div>
  );
};

Search Analytics

Tracking Implementation

// Search analytics tracking
const searchAnalytics = {
  trackSearch: (query, filters, results) => {
    gtag("event", "search", {
      search_term: query,
      filters_used: Object.keys(filters),
      results_count: results.length,
      has_results: results.length > 0,
    });
  },

  trackClick: (result, position) => {
    gtag("event", "search_result_click", {
      result_id: result.id,
      result_type: result.type,
      position: position,
      search_query: currentQuery,
    });
  },

  trackConversion: (result, action) => {
    gtag("event", "search_conversion", {
      result_id: result.id,
      action: action, // 'donate', 'volunteer', 'share'
      value: result.amount || 0,
    });
  },
};

Performance Metrics

Key Metrics:

Average search latency
Click-through rate by position
Conversion rate by query type
Zero-result rate
Query refinement rate

Dashboard Example:

-- Top performing searches
SELECT
  query,
  COUNT(*) as search_count,
  AVG(click_through_rate) as avg_ctr,
  AVG(conversion_rate) as avg_conversion
FROM search_analytics
WHERE date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY query
ORDER BY search_count DESC
LIMIT 100;

Mobile Search Experience

Touch-Optimized Interface

// Mobile search optimizations
const mobileSearch = {
  init: () => {
    // Voice search
    if ("webkitSpeechRecognition" in window) {
      enableVoiceSearch();
    }

    // Location-based search
    if ("geolocation" in navigator) {
      enableLocationSearch();
    }

    // Infinite scroll
    enableInfiniteScroll({
      threshold: 100,
      loadMore: loadNextPage,
    });
  },
};

Offline Capabilities

// Service worker for offline search
self.addEventListener("fetch", (event) => {
  if (event.request.url.includes("/api/search")) {
    event.respondWith(
      caches
        .match(event.request)
        .then((response) => response || fetch(event.request))
        .catch(() => caches.match("/offline-search")),
    );
  }
});

SEO Optimization

Search Results Pages

<!-- SEO-friendly search results -->
<div itemscope itemtype="http://schema.org/SearchResultsPage">
  <h1>Search Results for "education"</h1>
  <meta itemprop="about" content="education charities" />
  <div itemprop="mainEntity" itemscope itemtype="http://schema.org/ItemList">
    <link
      itemprop="itemListOrder"
      href="http://schema.org/ItemListOrderDescending"
    />
    <meta itemprop="numberOfItems" content="50" />
    <!-- Individual results -->
  </div>
</div>

Structured Data

{
  "@context": "https://schema.org",
  "@type": "SearchAction",
  "target": {
    "@type": "EntryPoint",
    "urlTemplate": "https://give.io/search?q={search_term}"
  },
  "query-input": "required name=search_term"
}

Best Practices

For Users

Effective Searching
- Use specific keywords
- Apply relevant filters
- Try different search terms
- Use location filters for local results
Discovery Tips
- Explore trending causes
- Check recommendations
- Save searches for updates
- Follow favorite organizations

For Organizations

Optimization
- Complete all profile fields
- Use relevant keywords
- Update content regularly
- Add high-quality images
Visibility
- Maintain verification
- Encourage reviews
- Share updates
- Engage with supporters

For Developers

Integration
- Cache frequent searches
- Implement pagination properly
- Handle errors gracefully
- Monitor API usage
Performance
- Debounce search input
- Lazy load images
- Use search analytics
- Optimize for mobile

Future Enhancements

Planned Features

Visual search capabilities
Multi-language support
AI-powered chat search
Augmented reality discovery
Blockchain-verified results

Research Areas

Semantic search improvements
Federated search across platforms
Predictive search suggestions
Context-aware recommendations
Privacy-preserving personalization