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Advanced Search System
AutoBot Solutions edited this page May 13, 2026
·
1 revision
The advanced search system provides comprehensive search capabilities with Elasticsearch integration, intelligent ranking, analytics, and personalized user preferences.
- Full-text Search: Search across all forum content with advanced query support
- Elasticsearch Integration: Powerful search engine with fast indexing and retrieval
- Intelligent Ranking: Smart ranking algorithm based on relevance, votes, and recency
- Search Suggestions: Autocomplete and intelligent query suggestions
- Advanced Filtering: Filter results by category, author, date range, and more
- Popular Queries: Track and display trending search terms
- User Behavior: Analyze how users interact with search results
- Search Performance: Monitor search speed and accuracy metrics
- Query Optimization: Automatically improve search based on usage patterns
- Personalized Results: Tailored search results based on user history
- Search History: Save and manage previous searches
- Result Preferences: Customize result display and sorting
- Alert System: Get notified for new content matching saved searches
- Boolean Operators: Support for AND, OR, NOT operators
- Phrase Matching: Exact phrase search with quotes
- Wildcard Support: Use * and ? for partial matches
- Field-specific Search: Search specific fields like title, content, author
- Date Range Queries: Search within specific time periods
class SearchEngine:
def __init__(self):
self.elasticsearch_client = Elasticsearch()
self.query_analyzer = QueryAnalyzer()
self.ranker = SearchRanker()
def search(self, query, filters=None, user_id=None):
# Analyze and optimize query
optimized_query = self.query_analyzer.process(query)
# Execute search with filters
results = self.elasticsearch_client.search(
index="forum_content",
body=optimized_query
)
# Rank and personalize results
ranked_results = self.ranker.rank(results, user_id)
return ranked_resultsclass QueryAnalyzer:
def process(self, query):
# Tokenize and normalize
tokens = self.tokenize(query)
# Apply stemming and synonyms
processed_tokens = self.apply_stemming(tokens)
# Build Elasticsearch query
es_query = self.build_query(processed_tokens)
return es_queryclass SearchRanker:
def rank(self, results, user_id=None):
for result in results:
# Base relevance score
score = result['_score']
# Boost factors
score += self.vote_boost(result)
score += self.recency_boost(result)
score += self.user_preference_boost(result, user_id)
result['final_score'] = score
return sorted(results, key=lambda x: x['final_score'], reverse=True)// Search autocomplete
$('#search-input').on('input', function() {
const query = $(this).val();
if (query.length >= 2) {
$.get('/api/search/suggestions', {q: query}, function(suggestions) {
displaySuggestions(suggestions);
});
}
});- Category Filter: Limit search to specific categories
- Author Filter: Search by specific users
- Date Range: Search within time periods
- Vote Threshold: Only show content with minimum votes
- Content Type: Filter posts, comments, or both
- Query Volume: Track search query frequency
- Result Clicks: Monitor which results users click
- Search Success: Measure search effectiveness
- Popular Terms: Display trending search terms
- Incremental Updates: Update index incrementally for new content
- Bulk Operations: Process multiple updates efficiently
- Index Optimization: Regular index maintenance and optimization
- Sharding: Distribute index across multiple shards for scalability
- Query Caching: Cache frequent search queries
- Result Caching: Cache popular search results
- User Preference Caching: Cache personalized rankings
- Analytics Caching: Cache analytics calculations
- Query Analysis: Analyze and optimize slow queries
- Index Tuning: Optimize Elasticsearch index settings
- Result Pagination: Efficient pagination for large result sets
- Search Suggestions: Pre-compute popular suggestions
- Content Permissions: Only search content user has access to
- Private Content: Exclude private content from public searches
- Search Rate Limiting: Prevent search abuse and DoS attacks
- Query Validation: Sanitize and validate all search queries
- Search Logging: Log searches for analytics while respecting privacy
- User Data: Protect user search history and preferences
- Content Filtering: Filter inappropriate content from search results
-
GET /api/search?q={query}: Basic search -
GET /api/search/advanced: Advanced search with filters -
GET /api/search/suggestions?q={query}: Search suggestions -
POST /api/search/save: Save search preferences
-
GET /api/search/analytics/popular: Popular queries -
GET /api/search/analytics/performance: Search performance metrics -
GET /api/search/analytics/user/{id}: User search behavior
elasticsearch:
hosts: ["localhost:9200"]
index_name: "forum_content"
settings:
number_of_shards: 3
number_of_replicas: 1
analysis:
analyzer:
forum_analyzer:
type: custom
tokenizer: standard
filter: [lowercase, stop, snowball]SEARCH_CONFIG = {
'max_results': 50,
'highlight_enabled': True,
'suggestions_enabled': True,
'analytics_enabled': True,
'cache_ttl': 300, # 5 minutes
}- No Results: Check query syntax and index health
- Slow Performance: Monitor Elasticsearch cluster health
- Incorrect Ranking: Review ranking algorithm and boost factors
- Missing Content: Verify index is up to date
- Query Debugger: Analyze Elasticsearch queries
- Index Inspector: Check index status and content
- Performance Monitor: Track search performance metrics
- Health Checker: Monitor Elasticsearch cluster health