Knowledge Graphs and Semantic Networks

<h2 id="knowledge-graphs-and-semantic-networks" class="position-relative d-flex align-items-center group"> Knowledge Graphs and Semantic Networks <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="knowledge-graphs-and-semantic-networks" aria-haspopup="dialog" aria-label="Share link: Knowledge Graphs and Semantic Networks"> Share link </button> </h2><div id="headingShareModal" class="heading-share-modal" role="dialog" aria-modal="true" aria-labelledby="headingShareTitle" hidden> <div class="hsm-dialog" role="document"> <div class="hsm-header"> <h2 id="headingShareTitle" class="h6 mb-0 fw-bold">Share this section</h2> <button type="button" class="hsm-close" aria-label="Close"> </button> </div> <div class="hsm-body"> <label for="headingShareInput" class="form-label small text-muted mb-1 text-uppercase fw-bold" style="font-size: 0.7rem; letter-spacing: 0.5px;">Permalink</label> <div class="input-group mb-4 hsm-url-group"> <input id="headingShareInput" type="text" class="form-control font-monospace" readonly aria-readonly="true" style="font-size: 0.85rem;" /> <button class="btn btn-primary hsm-copy" type="button" aria-label="Copy" title="Copy"> </button> </div> <div class="small fw-bold mb-2 text-muted text-uppercase" style="font-size: 0.7rem; 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const input = modal.querySelector('#headingShareInput'); const copyBtn = modal.querySelector('.hsm-copy'); const twitter = modal.querySelector('#share-twitter'); const linkedin = modal.querySelector('#share-linkedin'); const facebook = modal.querySelector('#share-facebook'); const closeBtn = modal.querySelector('.hsm-close'); let lastFocus=null; let trapBound=false; function buildUrl(id){ return window.location.origin + window.location.pathname + '#' + id; } function isOpen(){ return !modal.hasAttribute('hidden'); } function hydrate(id){ const url=buildUrl(id); input.value=url; const enc=encodeURIComponent(url); const text=encodeURIComponent(document.title); if(twitter) twitter.href=`https://twitter.com/intent/tweet?url=${enc}&text=${text}`; if(linkedin) linkedin.href=`https://www.linkedin.com/sharing/share-offsite/?url=${enc}`; if(facebook) facebook.href=`https://www.facebook.com/sharer/sharer.php?u=${enc}`; } function openModal(id){ lastFocus=document.activeElement; hydrate(id); if(!isOpen()){ modal.removeAttribute('hidden'); } requestAnimationFrame(()=>{ input.focus(); }); trapFocus(); } function closeModal(){ if(!isOpen()) return; modal.setAttribute('hidden',''); if(lastFocus && typeof lastFocus.focus==='function') lastFocus.focus(); } function copyCurrent(){ try{ navigator.clipboard.writeText(input.value).then(()=>feedback(true),()=>fallback()); } catch(e){ fallback(); } } function fallback(){ input.select(); try{ document.execCommand('copy'); feedback(true);}catch(e){ feedback(false);} } function feedback(ok){ if(!copyBtn) return; const icon=copyBtn.querySelector('i'); if(!icon) return; const prev=copyBtn.getAttribute('data-prev')||icon.className; if(!copyBtn.getAttribute('data-prev')) copyBtn.setAttribute('data-prev',prev); icon.className= ok ? 'fa-duotone fa-clipboard-check':'fa-duotone fa-circle-exclamation'; setTimeout(()=>{ icon.className=prev; },1800); } function handleShareClick(e){ e.preventDefault(); const btn=e.currentTarget; const id=btn.getAttribute('data-share-target'); if(id) openModal(id); } function bindShareButtons(){ document.querySelectorAll('.h-share').forEach(btn=>{ if(!btn.dataset.hShareBound){ btn.addEventListener('click', handleShareClick); btn.dataset.hShareBound='1'; } }); } bindShareButtons(); if(document.readyState==='loading'){ document.addEventListener('DOMContentLoaded', bindShareButtons); } else { requestAnimationFrame(bindShareButtons); } document.addEventListener('click', function(e){ const shareBtn=e.target.closest && e.target.closest('.h-share'); if(shareBtn && !shareBtn.dataset.hShareBound){ handleShareClick.call(shareBtn, e); } }, true); document.addEventListener('click', e=>{ if(e.target===modal) closeModal(); if(e.target.closest && e.target.closest('.hsm-close')){ e.preventDefault(); closeModal(); } if(copyBtn && (e.target===copyBtn || (e.target.closest && e.target.closest('.hsm-copy')))) { e.preventDefault(); copyCurrent(); } }); document.addEventListener('keydown', e=>{ if(e.key==='Escape' && isOpen()) closeModal(); }); function trapFocus(){ if(trapBound) return; trapBound=true; modal.addEventListener('keydown', f=>{ if(f.key==='Tab' && isOpen()){ const focusable=[...modal.querySelectorAll('a[href],button,input,textarea,select,[tabindex]:not([tabindex="-1"])')].filter(el=>!el.hasAttribute('disabled')); if(!focusable.length) return; const first=focusable[0]; const last=focusable[focusable.length-1]; if(f.shiftKey && document.activeElement===first){ f.preventDefault(); last.focus(); } else if(!f.shiftKey && document.activeElement===last){ f.preventDefault(); first.focus(); } } }); } if(closeBtn) closeBtn.addEventListener('click', e=>{ e.preventDefault(); closeModal(); }); })(); </script>Build intelligent knowledge graphs with Geode for semantic search, entity linking, and complex information retrieval. <h3 id="overview" class="position-relative d-flex align-items-center group"> Overview <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="overview" aria-haspopup="dialog" aria-label="Share link: Overview"> Share link </button> </h3>Knowledge graphs represent real-world entities and their relationships in a structured, semantic format. Geode’s property graph model naturally supports knowledge graph construction with rich metadata, type hierarchies, and flexible schema evolution. <h4 id="what-is-a-knowledge-graph" class="position-relative d-flex align-items-center group"> What is a Knowledge Graph? <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="what-is-a-knowledge-graph" aria-haspopup="dialog" aria-label="Share link: What is a Knowledge Graph?"> Share link </button> </h4>A knowledge graph is a network of entities (people, places, concepts) connected by meaningful relationships, enriched with: <ul> <li>Entity Types: Categorization using labels and properties</li> <li>Relationships: Typed connections with metadata</li> <li>Semantics: Meaning encoded in structure and attributes</li> <li>Inference: Derive new knowledge from existing facts</li> </ul> <h4 id="key-capabilities" class="position-relative d-flex align-items-center group"> Key Capabilities <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="key-capabilities" aria-haspopup="dialog" aria-label="Share link: Key Capabilities"> Share link </button> </h4><ul> <li>Semantic Querying: Find information by meaning, not just keywords</li> <li>Entity Resolution: Merge duplicate entities across sources</li> <li>Ontology Management: Define and enforce domain models</li> <li>Relationship Discovery: Uncover hidden connections</li> <li>Multi-hop Reasoning: Answer complex questions across relationships</li> </ul> <h3 id="use-case-scenarios" class="position-relative d-flex align-items-center group"> Use Case Scenarios <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="use-case-scenarios" aria-haspopup="dialog" aria-label="Share link: Use Case Scenarios"> Share link </button> </h3> <h4 id="1-enterprise-knowledge-management" class="position-relative d-flex align-items-center group"> 1. Enterprise Knowledge Management <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="1-enterprise-knowledge-management" aria-haspopup="dialog" aria-label="Share link: 1. Enterprise Knowledge Management"> Share link </button> </h4>Challenge: Organize organizational knowledge across departments Solution: Build a unified knowledge graph of: <ul> <li>People (employees, customers, partners)</li> <li>Projects and deliverables</li> <li>Documents and assets</li> <li>Expertise and skills</li> </ul> Benefits: <ul> <li>Find relevant expertise quickly</li> <li>Discover hidden project connections</li> <li>Automate knowledge discovery</li> <li>Improve decision-making</li> </ul> <h4 id="2-scientific-research-networks" class="position-relative d-flex align-items-center group"> 2. Scientific Research Networks <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="2-scientific-research-networks" aria-haspopup="dialog" aria-label="Share link: 2. Scientific Research Networks"> Share link </button> </h4>Challenge: Navigate millions of papers, authors, and citations Solution: Create research knowledge graph with: <ul> <li>Authors and affiliations</li> <li>Papers and citations</li> <li>Topics and keywords</li> <li>Funding sources</li> </ul> Benefits: <ul> <li>Find related research</li> <li>Identify collaboration opportunities</li> <li>Track research trends</li> <li>Discover influential work</li> </ul> <h4 id="3-product-catalogs-and-recommendations" class="position-relative d-flex align-items-center group"> 3. Product Catalogs and Recommendations <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="3-product-catalogs-and-recommendations" aria-haspopup="dialog" aria-label="Share link: 3. Product Catalogs and Recommendations"> Share link </button> </h4>Challenge: Organize complex product hierarchies with attributes Solution: Model products as knowledge graph: <ul> <li>Products and variants</li> <li>Categories and taxonomies</li> <li>Attributes and specifications</li> <li>Customer preferences</li> </ul> Benefits: <ul> <li>Semantic product search</li> <li>Intelligent recommendations</li> <li>Cross-selling opportunities</li> <li>Attribute-based filtering</li> </ul> <h3 id="data-model" class="position-relative d-flex align-items-center group"> Data Model <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="data-model" aria-haspopup="dialog" aria-label="Share link: Data Model"> Share link </button> </h3> <h4 id="entity-modeling" class="position-relative d-flex align-items-center group"> Entity Modeling <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="entity-modeling" aria-haspopup="dialog" aria-label="Share link: Entity Modeling"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Core entity types CREATE (:Entity { id: 'ent_123', type: 'Person', name: 'Marie Curie', canonical_name: 'marie curie', aliases: ['Maria Sklodowska', 'Madame Curie'] }), (:Entity { id: 'ent_456', type: 'Organization', name: 'University of Paris', founded: 1150, location: 'Paris, France' }), (:Entity { id: 'ent_789', type: 'Concept', name: 'Radioactivity', domain: 'Physics', definition: 'Emission of radiation from atomic nuclei' }); </code></pre></div> <h4 id="relationship-types" class="position-relative d-flex align-items-center group"> Relationship Types <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="relationship-types" aria-haspopup="dialog" aria-label="Share link: Relationship Types"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Typed relationships with metadata MATCH (marie:Entity {id: 'ent_123'}), (uni:Entity {id: 'ent_456'}) CREATE (marie)-[:AFFILIATED_WITH { role: 'Professor', start_date: date('1906-01-01'), end_date: date('1934-07-04'), department: 'Physics' }]->(uni); MATCH (marie:Entity {id: 'ent_123'}), (radio:Entity {id: 'ent_789'}) CREATE (marie)-[:DISCOVERED { year: 1898, recognition: 'Nobel Prize in Physics (1903)', co_discoverers: ['Pierre Curie', 'Henri Becquerel'] }]->(radio); </code></pre></div> <h4 id="ontology-definition" class="position-relative d-flex align-items-center group"> Ontology Definition <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="ontology-definition" aria-haspopup="dialog" aria-label="Share link: Ontology Definition"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Type hierarchy CREATE (:Type {name: 'Entity', level: 0}), (:Type {name: 'Person', level: 1, parent: 'Entity'}), (:Type {name: 'Scientist', level: 2, parent: 'Person'}), (:Type {name: 'Physicist', level: 3, parent: 'Scientist'}), (:Type {name: 'Organization', level: 1, parent: 'Entity'}), (:Type {name: 'University', level: 2, parent: 'Organization'}), (:Type {name: 'Concept', level: 1, parent: 'Entity'}), (:Type {name: 'Scientific_Concept', level: 2, parent: 'Concept'}); -- Type relationships MATCH (scientist:Type {name: 'Scientist'}), (person:Type {name: 'Person'}) CREATE (scientist)-[:SUBCLASS_OF]->(person); </code></pre></div> <h3 id="implementation-guide" class="position-relative d-flex align-items-center group"> Implementation Guide <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="implementation-guide" aria-haspopup="dialog" aria-label="Share link: Implementation Guide"> Share link </button> </h3> <h4 id="step-1-data-ingestion" class="position-relative d-flex align-items-center group"> Step 1: Data Ingestion <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="step-1-data-ingestion" aria-haspopup="dialog" aria-label="Share link: Step 1: Data Ingestion"> Share link </button> </h4> <h5 id="from-structured-sources" class="position-relative d-flex align-items-center group"> From Structured Sources <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="from-structured-sources" aria-haspopup="dialog" aria-label="Share link: From Structured Sources"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Import from CSV LOAD CSV WITH HEADERS FROM 'file:///entities.csv' AS row CREATE (:Entity { id: row.id, type: row.type, name: row.name, properties: row }); -- Import from JSON LOAD JSON FROM 'file:///knowledge_base.json' AS data UNWIND data.entities AS entity CREATE (:Entity { id: entity.id, type: entity.type, name: entity.name, attributes: entity.attributes }); </code></pre></div> <h5 id="from-unstructured-text" class="position-relative d-flex align-items-center group"> From Unstructured Text <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="from-unstructured-text" aria-haspopup="dialog" aria-label="Share link: From Unstructured Text"> Share link </button> </h5> <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Python client - Extract entities from text from geode_client import Client import spacy client = Client(host="geode.example.com", port=3141) nlp = spacy.load("en_core_web_sm") def extract_entities(text): doc = nlp(text) entities = [] for ent in doc.ents: entities.append({ 'text': ent.text, 'label': ent.label_, 'start': ent.start_char, 'end': ent.end_char }) return entities # Process document text = "Marie Curie discovered radioactivity at the University of Paris." entities = extract_entities(text) # Create entities in Geode async def store_entities(entities_to_store): async with client.connection() as conn: for ent in entities_to_store: await conn.execute(""" MERGE (e:Entity {name: $name, type: $type}) ON CREATE SET e.mentions = 1 ON MATCH SET e.mentions = e.mentions + 1 """, {'name': ent['text'], 'type': ent['label']}) # asyncio.run(store_entities(entities)) </code></pre></div> <h4 id="step-2-entity-resolution" class="position-relative d-flex align-items-center group"> Step 2: Entity Resolution <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="step-2-entity-resolution" aria-haspopup="dialog" aria-label="Share link: Step 2: Entity Resolution"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find potential duplicates MATCH (e1:Entity), (e2:Entity) WHERE e1.id < e2.id AND e1.type = e2.type AND ( e1.name = e2.name OR e1.canonical_name = e2.canonical_name OR ANY(alias IN e1.aliases WHERE alias IN e2.aliases) ) RETURN e1.id, e1.name, e2.id, e2.name, 'exact_match' AS match_type; -- Fuzzy matching with string similarity MATCH (e1:Entity), (e2:Entity) WHERE e1.id < e2.id AND e1.type = e2.type AND levenshtein_distance(e1.canonical_name, e2.canonical_name) < 3 RETURN e1.id, e1.name, e2.id, e2.name, levenshtein_distance(e1.canonical_name, e2.canonical_name) AS edit_distance ORDER BY edit_distance; </code></pre></div> <h5 id="merge-duplicates" class="position-relative d-flex align-items-center group"> Merge Duplicates <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="merge-duplicates" aria-haspopup="dialog" aria-label="Share link: Merge Duplicates"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Merge two entities MATCH (primary:Entity {id: 'ent_123'}) MATCH (duplicate:Entity {id: 'ent_124'}) -- Merge relationships MATCH (duplicate)-[r]->(other) MERGE (primary)-[r2:TYPE(r)]->(other) SET r2 = properties(r); MATCH (other)-[r]->(duplicate) MERGE (other)-[r2:TYPE(r)]->(primary) SET r2 = properties(r); -- Merge properties SET primary.aliases = primary.aliases + duplicate.aliases, primary.mentions = primary.mentions + duplicate.mentions, primary.sources = primary.sources + duplicate.sources; -- Delete duplicate DETACH DELETE duplicate; </code></pre></div> <h4 id="step-3-semantic-search" class="position-relative d-flex align-items-center group"> Step 3: Semantic Search <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="step-3-semantic-search" aria-haspopup="dialog" aria-label="Share link: Step 3: Semantic Search"> Share link </button> </h4> <h5 id="full-text-search" class="position-relative d-flex align-items-center group"> Full-Text Search <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="full-text-search" aria-haspopup="dialog" aria-label="Share link: Full-Text Search"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create full-text index CREATE INDEX entity_name_ft_idx ON Entity(name) USING fulltext; -- Search with ranking MATCH (e:Entity) WHERE fulltext_match(e.name, "physics nobel prize") RETURN e.name, e.type, bm25_score(e.name, "physics nobel prize") AS relevance ORDER BY relevance DESC LIMIT 10; </code></pre></div> <h5 id="contextual-search" class="position-relative d-flex align-items-center group"> Contextual Search <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="contextual-search" aria-haspopup="dialog" aria-label="Share link: Contextual Search"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find entities in context MATCH (e:Entity)-[r]-(related:Entity) WHERE fulltext_match(e.name, "curie") RETURN e.name, e.type, collect({ relationship: type(r), entity: related.name, entity_type: related.type }) AS context ORDER BY e.mentions DESC; </code></pre></div> <h4 id="step-4-knowledge-discovery" class="position-relative d-flex align-items-center group"> Step 4: Knowledge Discovery <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="step-4-knowledge-discovery" aria-haspopup="dialog" aria-label="Share link: Step 4: Knowledge Discovery"> Share link </button> </h4> <h5 id="find-hidden-connections" class="position-relative d-flex align-items-center group"> Find Hidden Connections <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="find-hidden-connections" aria-haspopup="dialog" aria-label="Share link: Find Hidden Connections"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find connection paths between entities MATCH path = shortestPath( (marie:Entity {name: 'Marie Curie'})-[*1..5]-(einstein:Entity {name: 'Albert Einstein'}) ) RETURN [n IN nodes(path) | {name: n.name, type: n.type}] AS connection_path, [r IN relationships(path) | type(r)] AS relationship_types, length(path) AS degree_of_separation; </code></pre></div> <h5 id="discover-patterns" class="position-relative d-flex align-items-center group"> Discover Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="discover-patterns" aria-haspopup="dialog" aria-label="Share link: Discover Patterns"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Find common collaboration patterns MATCH (p1:Entity {type: 'Scientist'})-[:COLLABORATED_WITH]->(p2:Entity {type: 'Scientist'}), (p2)-[:COLLABORATED_WITH]->(p3:Entity {type: 'Scientist'}), (p3)-[:COLLABORATED_WITH]->(p1) WHERE p1.id < p2.id AND p2.id < p3.id RETURN p1.name, p2.name, p3.name, count(*) AS triangle_count ORDER BY triangle_count DESC LIMIT 10; </code></pre></div> <h4 id="step-5-inference-and-reasoning" class="position-relative d-flex align-items-center group"> Step 5: Inference and Reasoning <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="step-5-inference-and-reasoning" aria-haspopup="dialog" aria-label="Share link: Step 5: Inference and Reasoning"> Share link </button> </h4> <h5 id="type-inference" class="position-relative d-flex align-items-center group"> Type Inference <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="type-inference" aria-haspopup="dialog" aria-label="Share link: Type Inference"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Infer types from relationships MATCH (person:Entity)-[:WORKS_AT]->(org:Entity {type: 'University'}) WHERE NOT person.type = 'Professor' SET person.type = 'Academic'; -- Infer expertise from publications MATCH (author:Entity {type: 'Person'})-[:AUTHORED]->(paper:Entity), (paper)-[:ABOUT]->(topic:Entity {type: 'Concept'}) WITH author, topic, count(*) AS paper_count WHERE paper_count > 5 MERGE (author)-[:EXPERT_IN {strength: paper_count}]->(topic); </code></pre></div> <h5 id="rule-based-inference" class="position-relative d-flex align-items-center group"> Rule-Based Inference <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="rule-based-inference" aria-haspopup="dialog" aria-label="Share link: Rule-Based Inference"> Share link </button> </h5><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Transitivity: If A→B and B→C, infer A→C MATCH (a:Entity)-[:INFLUENCES]->(b:Entity)-[:INFLUENCES]->(c:Entity) WHERE NOT EXISTS((a)-[:INFLUENCES]->(c)) MERGE (a)-[:INFLUENCES {derived: true, confidence: 0.7}]->(c); -- Symmetry: If A COLLABORATED_WITH B, then B COLLABORATED_WITH A MATCH (a:Entity)-[r:COLLABORATED_WITH]->(b:Entity) WHERE NOT EXISTS((b)-[:COLLABORATED_WITH]->(a)) MERGE (b)-[:COLLABORATED_WITH { derived: true, source: r.source, year: r.year }]->(a); </code></pre></div> <h3 id="advanced-patterns" class="position-relative d-flex align-items-center group"> Advanced Patterns <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="advanced-patterns" aria-haspopup="dialog" aria-label="Share link: Advanced Patterns"> Share link </button> </h3> <h4 id="rdf-integration" class="position-relative d-flex align-items-center group"> RDF Integration <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="rdf-integration" aria-haspopup="dialog" aria-label="Share link: RDF Integration"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Model RDF triples as graph -- Triple: (subject, predicate, object) -- Create entities MERGE (marie:Entity {uri: 'http://example.org/person/marie_curie', name: 'Marie Curie'}) MERGE (nobel:Entity {uri: 'http://example.org/award/nobel_physics_1903', name: 'Nobel Prize in Physics 1903'}); -- Create relationship (predicate) MATCH (marie:Entity {uri: 'http://example.org/person/marie_curie'}), (nobel:Entity {uri: 'http://example.org/award/nobel_physics_1903'}) CREATE (marie)-[:RECEIVED { predicate: 'http://example.org/ontology/received', year: 1903 }]->(nobel); -- SPARQL-like query in GQL MATCH (subject:Entity)-[r]->(object:Entity) WHERE r.predicate = 'http://example.org/ontology/received' AND object.uri CONTAINS 'nobel' RETURN subject.uri, r.predicate, object.uri; </code></pre></div> <h4 id="vector-embeddings-for-semantic-similarity" class="position-relative d-flex align-items-center group"> Vector Embeddings for Semantic Similarity <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="vector-embeddings-for-semantic-similarity" aria-haspopup="dialog" aria-label="Share link: Vector Embeddings for Semantic Similarity"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Generate entity embeddings from sentence_transformers import SentenceTransformer from geode_client import Client model = SentenceTransformer('all-MiniLM-L6-v2') client = Client(host="geode.example.com", port=3141) async def embed_entities(): async with client.connection() as conn: # Get entities page, _ = await conn.query("MATCH (e:Entity) RETURN e.id, e.name, e.description") for record in page.rows: ent_id = record["e.id"].raw_value text = f"{record['e.name'].raw_value} {record['e.description'].raw_value}" # Generate embedding embedding = model.encode(text) # Store in Geode await conn.execute(""" MATCH (e:Entity {id: $id}) SET e.embedding = $embedding """, {'id': ent_id, 'embedding': embedding.tolist()}) # Create vector index await conn.execute("CREATE INDEX entity_emb_idx ON Entity(embedding) USING vector") # Find semantically similar entities query_embedding = model.encode("nuclear physics research") page, _ = await conn.query(""" MATCH (e:Entity) WHERE vector_distance_cosine(e.embedding, $query_vec) < 0.5 RETURN e.name, e.type, vector_distance_cosine(e.embedding, $query_vec) AS similarity ORDER BY similarity ASC LIMIT 10 """, {'query_vec': query_embedding.tolist()}) # asyncio.run(embed_entities()) </code></pre></div> <h4 id="temporal-knowledge-graphs" class="position-relative d-flex align-items-center group"> Temporal Knowledge Graphs <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="temporal-knowledge-graphs" aria-haspopup="dialog" aria-label="Share link: Temporal Knowledge Graphs"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Model time-varying facts CREATE (:Entity { id: 'ent_123', name: 'Marie Curie', type: 'Person' }); -- Facts with temporal validity CREATE (marie:Entity {id: 'ent_123'}), (uni_paris:Entity {id: 'ent_456'}), (uni_sorbonne:Entity {id: 'ent_457'}) CREATE (marie)-[:WORKS_AT { valid_from: date('1906-01-01'), valid_to: date('1934-07-04'), position: 'Professor of Physics' }]->(uni_paris); -- Query facts at specific time MATCH (person:Entity)-[r:WORKS_AT]->(org:Entity) WHERE $query_date >= r.valid_from AND $query_date <= r.valid_to RETURN person.name, org.name, r.position; </code></pre></div> <h3 id="query-examples" class="position-relative d-flex align-items-center group"> Query Examples <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="query-examples" aria-haspopup="dialog" aria-label="Share link: Query Examples"> Share link </button> </h3> <h4 id="question-answering" class="position-relative d-flex align-items-center group"> Question Answering <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="question-answering" aria-haspopup="dialog" aria-label="Share link: Question Answering"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- "Who won the Nobel Prize in Physics in 1903?" MATCH (person:Entity)-[r:RECEIVED]->(award:Entity) WHERE award.name CONTAINS 'Nobel' AND award.name CONTAINS 'Physics' AND r.year = 1903 RETURN person.name, award.name; -- "What did Marie Curie discover?" MATCH (marie:Entity {name: 'Marie Curie'})-[:DISCOVERED]->(thing:Entity) RETURN thing.name, thing.type; -- "Who collaborated with Marie Curie?" MATCH (marie:Entity {name: 'Marie Curie'})-[:COLLABORATED_WITH]-(colleague:Entity) RETURN colleague.name, colleague.type; </code></pre></div> <h4 id="multi-hop-reasoning" class="position-relative d-flex align-items-center group"> Multi-hop Reasoning <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="multi-hop-reasoning" aria-haspopup="dialog" aria-label="Share link: Multi-hop Reasoning"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- "Find researchers influenced by Marie Curie's work" MATCH (marie:Entity {name: 'Marie Curie'})-[:DISCOVERED]->(concept:Entity), (concept)<-[:STUDIED]-(researcher:Entity) WHERE researcher <> marie RETURN DISTINCT researcher.name, collect(DISTINCT concept.name) AS studied_concepts ORDER BY size(studied_concepts) DESC; -- "Find potential research collaborations" MATCH (a:Entity {type: 'Scientist'})-[:EXPERT_IN]->(topic:Entity), (topic)<-[:EXPERT_IN]-(b:Entity {type: 'Scientist'}) WHERE a <> b AND NOT EXISTS((a)-[:COLLABORATED_WITH]-(b)) WITH a, b, collect(topic.name) AS common_topics WHERE size(common_topics) >= 2 RETURN a.name, b.name, common_topics, size(common_topics) AS match_score ORDER BY match_score DESC LIMIT 20; </code></pre></div> <h3 id="performance-optimization" class="position-relative d-flex align-items-center group"> Performance Optimization <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="performance-optimization" aria-haspopup="dialog" aria-label="Share link: Performance Optimization"> Share link </button> </h3> <h4 id="indexing-strategy" class="position-relative d-flex align-items-center group"> Indexing Strategy <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="indexing-strategy" aria-haspopup="dialog" aria-label="Share link: Indexing Strategy"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Core indexes CREATE INDEX entity_id_idx ON Entity(id) USING hash; CREATE INDEX entity_type_idx ON Entity(type) USING btree; CREATE INDEX entity_name_idx ON Entity(canonical_name) USING btree; CREATE INDEX entity_ft_idx ON Entity(name, description) USING fulltext; CREATE INDEX entity_vector_idx ON Entity(embedding) USING vector; -- Composite indexes CREATE INDEX entity_type_name_idx ON Entity(type, canonical_name) USING btree; </code></pre></div> <h4 id="query-optimization" class="position-relative d-flex align-items-center group"> Query Optimization <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="query-optimization" aria-haspopup="dialog" aria-label="Share link: Query Optimization"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Use PROFILE to analyze PROFILE MATCH (e:Entity {type: 'Person'})-[:WORKS_AT]->(org:Entity {type: 'University'}) RETURN e.name, org.name; -- Add index if SeqScan detected CREATE INDEX person_type_idx ON Entity(type) USING btree; </code></pre></div> <h4 id="caching-popular-queries" class="position-relative d-flex align-items-center group"> Caching Popular Queries <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="caching-popular-queries" aria-haspopup="dialog" aria-label="Share link: Caching Popular Queries"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"># Python client with caching from geode_client import Client client = Client(host="geode.example.com", port=3141) context_cache = {} async def get_entity_context(conn, entity_id): if entity_id in context_cache: return context_cache[entity_id] page, _ = await conn.query(""" MATCH (e:Entity {id: $id})-[r]-(related:Entity) RETURN e, collect({rel: type(r), entity: related}) AS context """, {'id': entity_id}) context = page.rows[0] if page.rows else None context_cache[entity_id] = context return context # async with client.connection() as conn: # ctx = await get_entity_context(conn, "entity_123") </code></pre></div> <h3 id="best-practices" class="position-relative d-flex align-items-center group"> Best Practices <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="best-practices" aria-haspopup="dialog" aria-label="Share link: Best Practices"> Share link </button> </h3> <h4 id="1-entity-naming" class="position-relative d-flex align-items-center group"> 1. Entity Naming <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="1-entity-naming" aria-haspopup="dialog" aria-label="Share link: 1. Entity Naming"> Share link </button> </h4><ul> <li>Canonical Forms: Normalize to lowercase, remove punctuation</li> <li>Aliases: Store all known variations</li> <li>URIs: Use stable identifiers (not display names)</li> </ul> <h4 id="2-relationship-design" class="position-relative d-flex align-items-center group"> 2. Relationship Design <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="2-relationship-design" aria-haspopup="dialog" aria-label="Share link: 2. Relationship Design"> Share link </button> </h4><ul> <li>Explicit Types: Use specific relationship types (avoid generic <code>:RELATED_TO</code>)</li> <li>Metadata: Add context (date, confidence, source)</li> <li>Directionality: Choose meaningful direction</li> </ul> <h4 id="3-ontology-management" class="position-relative d-flex align-items-center group"> 3. Ontology Management <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="3-ontology-management" aria-haspopup="dialog" aria-label="Share link: 3. Ontology Management"> Share link </button> </h4><ul> <li>Start Simple: Begin with core types, expand as needed</li> <li>Document: Maintain ontology documentation</li> <li>Versioning: Track ontology changes over time</li> </ul> <h4 id="4-data-quality" class="position-relative d-flex align-items-center group"> 4. Data Quality <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="4-data-quality" aria-haspopup="dialog" aria-label="Share link: 4. Data Quality"> Share link </button> </h4><ul> <li>Validation: Enforce constraints on entity types</li> <li>Provenance: Track data sources</li> <li>Confidence Scores: Indicate certainty of facts</li> </ul> <h3 id="use-case-implementation" class="position-relative d-flex align-items-center group"> Use Case Implementation <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="use-case-implementation" aria-haspopup="dialog" aria-label="Share link: Use Case Implementation"> Share link </button> </h3> <h4 id="complete-example-academic-knowledge-graph" class="position-relative d-flex align-items-center group"> Complete Example: Academic Knowledge Graph <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="complete-example-academic-knowledge-graph" aria-haspopup="dialog" aria-label="Share link: Complete Example: Academic Knowledge Graph"> Share link </button> </h4><div class="highlight"><pre tabindex="0" class="chroma"><code class="language-gql" data-lang="gql">-- Create research entities CREATE GRAPH AcademicKnowledgeGraph; USE AcademicKnowledgeGraph; -- Authors CREATE (:Person {id: 'p1', name: 'Dr. Alice Johnson', field: 'Machine Learning'}), (:Person {id: 'p2', name: 'Prof. Bob Smith', field: 'Graph Theory'}), (:Person {id: 'p3', name: 'Dr. Carol White', field: 'Databases'}); -- Papers CREATE (:Paper {id: 'paper1', title: 'Graph Neural Networks', year: 2022, citations: 150}), (:Paper {id: 'paper2', title: 'Knowledge Graph Embeddings', year: 2023, citations: 75}), (:Paper {id: 'paper3', title: 'Scalable Graph Databases', year: 2021, citations: 200}); -- Topics CREATE (:Topic {id: 't1', name: 'Graph Neural Networks'}), (:Topic {id: 't2', name: 'Knowledge Graphs'}), (:Topic {id: 't3', name: 'Graph Databases'}); -- Authorship MATCH (p1:Person {id: 'p1'}), (paper1:Paper {id: 'paper1'}) CREATE (p1)-[:AUTHORED {contribution: 'primary'}]->(paper1); MATCH (p2:Person {id: 'p2'}), (paper1:Paper {id: 'paper1'}) CREATE (p2)-[:AUTHORED {contribution: 'secondary'}]->(paper1); -- Topics MATCH (paper1:Paper {id: 'paper1'}), (t1:Topic {id: 't1'}) CREATE (paper1)-[:ABOUT]->(t1); -- Find related researchers MATCH (p1:Person)-[:AUTHORED]->(paper1:Paper)-[:ABOUT]->(topic:Topic), (topic)<-[:ABOUT]-(paper2:Paper)<-[:AUTHORED]-(p2:Person) WHERE p1 <> p2 RETURN p1.name, p2.name, collect(DISTINCT topic.name) AS common_topics, count(DISTINCT topic) AS topic_overlap ORDER BY topic_overlap DESC; </code></pre></div> <h3 id="next-steps" class="position-relative d-flex align-items-center group"> Next Steps <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="next-steps" aria-haspopup="dialog" aria-label="Share link: Next Steps"> Share link </button> </h3><ul> <li><a href="/docs/analytics/graph-algorithms/" >Graph Algorithms</a> - Analyze knowledge graph structure</li> <li><a href="/docs/tutorials/vector-search-tutorial/" >Vector Search Tutorial</a> - Semantic similarity with embeddings</li> <li><a href="/docs/query/indexing-and-optimization/" >Full-Text Search</a> - BM25 ranking for text queries</li> <li><a href="/docs/analytics/real-time-analytics/" >Real-Time Analytics</a> - Streaming knowledge graph updates</li> </ul> <h3 id="references" class="position-relative d-flex align-items-center group"> References <button type="button" class="h-share btn btn-link p-0 text-decoration-none link-secondary opacity-50 hover-opacity-100 transition-all ms-1" data-share-target="references" aria-haspopup="dialog" aria-label="Share link: References"> Share link </button> </h3><ul> <li><a href="/docs/model/data-model-and-types/" >Data Model Guide</a> - Property graph concepts</li> <li><a href="/docs/gql/guide/" >GQL Guide</a> - Query language reference</li> <li><a href="/docs/query/indexing-and-optimization/" >Indexing Guide</a> - Performance optimization</li> <li><a href="/docs/guides/migration-guide/" >Migration Guide</a> - Import from RDF/Neo4j</li> </ul> <hr> License: Apache License 2.0 Copyright: 2024-2025 CodePros Last Updated: January 2026