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hgzero/data/sample/glossary-external-technical-docs.json
hiondal bb921e10eb 작업 파일 정리 및 실시간 회의록 플로우 추가 
- 가파팀 프로토타입 파일 삭제
- 가파팀 유저스토리 삭제
- 실시간 회의록 작성 플로우 설계서 추가 (Mermaid, Markdown)
- 백업 및 데이터 디렉토리 추가
- AI 데이터 샘플 생성 도구 추가

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-22 14:16:10 +09:00

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[
{
"domain": "네트워크 인프라 (Network Infrastructure)",
"samples": [
{
"term_id": "ext-ni-001",
"name": "gNB (gNodeB)",
"category": "네트워크 인프라",
"definition": "5G New Radio (NR) base station that provides radio connectivity to User Equipment (UE) and connects to the 5G Core Network",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 38.300 - NR; Overall description; Stage 2",
"standard_id": "3GPP TS 38.300",
"version": "17.4.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.300/",
"date": "2024-01-15"
},
"context": "3GPP 5G 표준에서 정의하는 차세대 기지국 노드. 4G의 eNodeB를 대체하는 5G 네트워크의 핵심 구성 요소",
"related_terms": ["eNodeB", "NG-RAN", "5GC", "CU-DU Split"],
"usage_example": "The gNB consists of a gNB-CU (Central Unit) and one or more gNB-DUs (Distributed Units) connected via F1 interface",
"confidence": 0.98
},
{
"term_id": "ext-ni-002",
"name": "Massive MIMO",
"category": "네트워크 인프라",
"definition": "Multi-antenna technology using arrays with a very large number of antenna elements (typically 64-256) to serve multiple users simultaneously on the same time-frequency resource",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TR 38.913 - Study on Scenarios and Requirements for Next Generation Access Technologies",
"standard_id": "3GPP TR 38.913",
"version": "16.0.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.913/",
"date": "2023-11-20"
},
"context": "5G 네트워크의 용량과 효율성을 극대화하기 위한 핵심 기술. 수십~수백 개의 안테나 소자를 사용하여 빔포밍 및 공간 다중화 구현",
"related_terms": ["Beamforming", "CSI-RS", "SRS", "TDD", "Precoding"],
"usage_example": "Massive MIMO enables spectral efficiency gains of 5-10x compared to conventional MIMO through spatial multiplexing of multiple UEs",
"confidence": 0.96
},
{
"term_id": "ext-ni-003",
"name": "O-RAN Architecture",
"category": "네트워크 인프라",
"definition": "Open Radio Access Network architecture that disaggregates RAN functions into modular components with open interfaces, enabling multi-vendor interoperability",
"source_type": "external",
"source_metadata": {
"source": "O-RAN Alliance",
"document_title": "O-RAN Architecture Description",
"standard_id": "O-RAN.WG1.O-RAN-Architecture-Description",
"version": "10.00",
"url": "https://www.o-ran.org/specifications",
"date": "2024-02-10"
},
"context": "개방형 RAN 구조로 벤더 종속성을 탈피하고 AI/ML 기반 네트워크 최적화를 가능하게 하는 차세대 무선 접속망 아키텍처",
"related_terms": ["RIC", "O-DU", "O-CU", "O-RU", "A1/E2 Interface", "SMO"],
"usage_example": "O-RAN architecture separates the RAN into O-CU, O-DU, and O-RU components connected via open fronthaul interfaces",
"confidence": 0.95
},
{
"term_id": "ext-ni-004",
"name": "Network Slicing",
"category": "네트워크 인프라",
"definition": "A 5G network architecture that enables the multiplexing of virtualized and independent logical networks on the same physical network infrastructure",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 23.501 - System architecture for the 5G System (5GS)",
"standard_id": "3GPP TS 23.501",
"version": "18.1.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/23_series/23.501/",
"date": "2024-03-05"
},
"context": "5G 네트워크의 핵심 기능으로 단일 물리 네트워크에서 서로 다른 요구사항을 가진 서비스별 가상 네트워크를 제공",
"related_terms": ["S-NSSAI", "NSI", "NSSF", "eMBB", "URLLC", "mMTC"],
"usage_example": "Network slicing allows creation of separate slices for eMBB (Enhanced Mobile Broadband), URLLC (Ultra-Reliable Low Latency), and mMTC (Massive Machine Type Communications)",
"confidence": 0.97
},
{
"term_id": "ext-ni-005",
"name": "Fronthaul",
"category": "네트워크 인프라",
"definition": "The fiber-based connection between the baseband unit (BBU) and remote radio head (RRH) in a C-RAN architecture, typically using CPRI or eCPRI protocol",
"source_type": "external",
"source_metadata": {
"source": "CPRI Cooperation",
"document_title": "eCPRI Interface Specification",
"standard_id": "eCPRI V2.0",
"version": "2.0",
"url": "http://www.cpri.info/spec.html",
"date": "2023-09-15"
},
"context": "C-RAN 구조에서 BBU와 RRH 간의 고속 연결을 담당. 5G에서는 대역폭 요구사항 완화를 위해 eCPRI 표준 활용",
"related_terms": ["CPRI", "eCPRI", "C-RAN", "BBU", "RRH", "Midhaul"],
"usage_example": "eCPRI reduces fronthaul bandwidth requirements by up to 10x compared to CPRI through functional split options",
"confidence": 0.94
},
{
"term_id": "ext-ni-006",
"name": "MEC (Multi-access Edge Computing)",
"category": "네트워크 인프라",
"definition": "Network architecture concept that enables cloud computing capabilities and IT service environment at the edge of the mobile network, within the Radio Access Network (RAN)",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "Multi-access Edge Computing (MEC); Framework and Reference Architecture",
"standard_id": "ETSI GS MEC 003",
"version": "3.1.1",
"url": "https://www.etsi.org/deliver/etsi_gs/MEC/001_099/003/",
"date": "2024-01-25"
},
"context": "모바일 네트워크 엣지에서 클라우드 컴퓨팅 기능을 제공하여 초저지연 서비스 구현. 5G 핵심 서비스 실현의 필수 요소",
"related_terms": ["Edge Cloud", "UPF", "Local Breakout", "LADN", "5GC"],
"usage_example": "MEC enables ultra-low latency applications (<10ms) by processing data at the network edge, close to end users",
"confidence": 0.96
},
{
"term_id": "ext-ni-007",
"name": "CUPS (Control and User Plane Separation)",
"category": "네트워크 인프라",
"definition": "Architecture principle that separates control plane and user plane functions to enable independent scaling and flexible deployment",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 23.214 - Architecture enhancements for control and user plane separation of EPC nodes",
"standard_id": "3GPP TS 23.214",
"version": "17.0.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/23_series/23.214/",
"date": "2023-12-10"
},
"context": "제어 평면과 사용자 평면의 분리를 통해 네트워크 유연성 향상 및 효율적 자원 활용. 4G EPC 개선 및 5G 코어 네트워크 기반 아키텍처",
"related_terms": ["SGW-C", "SGW-U", "PGW-C", "PGW-U", "UPF", "SMF"],
"usage_example": "CUPS architecture allows user plane functions to be deployed at the network edge while control plane remains centralized",
"confidence": 0.95
},
{
"term_id": "ext-ni-008",
"name": "SBA (Service-Based Architecture)",
"category": "네트워크 인프라",
"definition": "5G Core network architecture where network functions offer their services through a common framework using standardized service-based interfaces",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 23.501 - System architecture for the 5G System (5GS)",
"standard_id": "3GPP TS 23.501",
"version": "18.1.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/23_series/23.501/",
"date": "2024-03-05"
},
"context": "5G 코어 네트워크의 혁신적 아키텍처로 마이크로서비스 기반 설계 원칙 적용. 네트워크 기능 간 RESTful API 통신 기반",
"related_terms": ["NRF", "SCP", "HTTP/2", "NF Services", "Service Consumer", "Service Producer"],
"usage_example": "SBA enables network functions to discover and consume services from other NFs through the NRF (NF Repository Function)",
"confidence": 0.97
},
{
"term_id": "ext-ni-009",
"name": "NG-RAN (Next Generation RAN)",
"category": "네트워크 인프라",
"definition": "5G radio access network consisting of gNBs providing NR user plane and control plane protocol terminations towards the UE, connected to 5GC",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 38.300 - NR; Overall description; Stage 2",
"standard_id": "3GPP TS 38.300",
"version": "17.4.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.300/",
"date": "2024-01-15"
},
"context": "5G 무선 접속망의 공식 명칭으로 gNB와 ng-eNB를 포함. 4G의 E-UTRAN을 계승하는 차세대 RAN 구조",
"related_terms": ["gNB", "ng-eNB", "5GC", "NR", "Xn Interface", "NG Interface"],
"usage_example": "NG-RAN supports both standalone (SA) and non-standalone (NSA) deployment modes for 5G services",
"confidence": 0.96
},
{
"term_id": "ext-ni-010",
"name": "Beamforming",
"category": "네트워크 인프라",
"definition": "Signal processing technique used in antenna arrays to direct radio frequency signals toward specific receivers and suppress signals in other directions",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TR 38.802 - Study on New Radio Access Technology Physical Layer Aspects",
"standard_id": "3GPP TR 38.802",
"version": "14.2.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.802/",
"date": "2023-10-20"
},
"context": "5G 대역폭 효율성 극대화를 위한 핵심 기술. 디지털 및 아날로그 빔포밍을 통해 특정 사용자에게 신호를 집중",
"related_terms": ["Massive MIMO", "CSI", "Precoding", "Beam Management", "SSB"],
"usage_example": "5G NR supports both digital beamforming (per-user beam steering) and analog beamforming (sector-level beam control)",
"confidence": 0.95
},
{
"term_id": "ext-ni-011",
"name": "Carrier Aggregation",
"category": "네트워크 인프라",
"definition": "Technology that combines multiple component carriers to increase bandwidth and data rates, supporting up to 16 carriers in 5G NR",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 38.300 - NR; Overall description; Stage 2",
"standard_id": "3GPP TS 38.300",
"version": "17.4.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.300/",
"date": "2024-01-15"
},
"context": "여러 주파수 대역을 결합하여 전송 속도를 높이는 기술. 5G에서는 최대 16개 캐리어 집적 지원으로 수 Gbps 속도 달성",
"related_terms": ["Component Carrier", "PCell", "SCell", "Bandwidth Part", "DC (Dual Connectivity)"],
"usage_example": "5G NR supports intra-band contiguous CA, intra-band non-contiguous CA, and inter-band CA configurations",
"confidence": 0.96
},
{
"term_id": "ext-ni-012",
"name": "CU-DU Split",
"category": "네트워크 인프라",
"definition": "Functional split of gNB into Centralized Unit (CU) handling higher layer protocols and Distributed Unit (DU) handling lower layer protocols",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 38.401 - NG-RAN; Architecture description",
"standard_id": "3GPP TS 38.401",
"version": "17.4.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.401/",
"date": "2024-02-01"
},
"context": "5G 기지국의 기능 분리 구조로 유연한 네트워크 배치 및 효율적 자원 활용 가능. O-RAN 아키텍처의 기반",
"related_terms": ["F1 Interface", "gNB-CU", "gNB-DU", "RRC", "PDCP", "RLC", "MAC"],
"usage_example": "The F1 interface between CU and DU supports both control plane (F1-C) and user plane (F1-U) protocols",
"confidence": 0.94
},
{
"term_id": "ext-ni-013",
"name": "mmWave (millimeter Wave)",
"category": "네트워크 인프라",
"definition": "Radio frequency bands between 24 GHz and 100 GHz used in 5G NR to provide ultra-high bandwidth and multi-Gbps data rates",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 38.101-2 - NR; User Equipment (UE) radio transmission and reception; Part 2: Range 2 Standalone",
"standard_id": "3GPP TS 38.101-2",
"version": "17.11.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/38_series/38.101-2/",
"date": "2024-01-30"
},
"context": "5G의 초고속 전송을 가능하게 하는 밀리미터파 대역. 넓은 대역폭 확보 가능하나 전파 특성상 커버리지 제한적",
"related_terms": ["FR2", "n257", "n258", "n260", "n261", "Beamforming", "Coverage"],
"usage_example": "mmWave frequencies (FR2) in 5G NR support channel bandwidths up to 400 MHz, enabling peak data rates exceeding 10 Gbps",
"confidence": 0.97
},
{
"term_id": "ext-ni-014",
"name": "NFV (Network Functions Virtualization)",
"category": "네트워크 인프라",
"definition": "Network architecture concept that virtualizes entire classes of network node functions into building blocks that can be connected to create communication services",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "Network Functions Virtualisation (NFV); Architectural Framework",
"standard_id": "ETSI GS NFV 002",
"version": "1.2.1",
"url": "https://www.etsi.org/deliver/etsi_gs/NFV/001_099/002/",
"date": "2023-11-10"
},
"context": "네트워크 기능을 소프트웨어로 구현하여 범용 하드웨어에서 실행. 5G 네트워크의 유연성과 확장성을 제공하는 핵심 기술",
"related_terms": ["VNF", "NFVI", "MANO", "SDN", "Cloud Native", "CNF"],
"usage_example": "NFV enables network operators to deploy new services rapidly without installing new hardware equipment",
"confidence": 0.95
},
{
"term_id": "ext-ni-015",
"name": "NWDAF (Network Data Analytics Function)",
"category": "네트워크 인프라",
"definition": "5G Core network function that provides network data analytics and supports data-driven network optimization using machine learning",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 23.288 - Architecture enhancements for 5G System (5GS) to support network data analytics services",
"standard_id": "3GPP TS 23.288",
"version": "18.2.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/23_series/23.288/",
"date": "2024-03-20"
},
"context": "5G 네트워크의 인텔리전스 구현을 위한 데이터 분석 기능. AI/ML 기반 네트워크 자동화 및 최적화의 핵심 컴포넌트",
"related_terms": ["AI/ML", "OAM", "Analytics ID", "NF Service Consumer", "PCF"],
"usage_example": "NWDAF collects data from various network functions and provides analytics such as load prediction, QoS sustainability, and abnormality detection",
"confidence": 0.93
}
]
},
{
"domain": "기술 개발 및 연구 (Technology Development & R&D)",
"samples": [
{
"term_id": "ext-td-001",
"name": "AI-RAN",
"category": "기술 개발 및 연구",
"definition": "Artificial Intelligence integrated Radio Access Network that uses machine learning algorithms to optimize RAN operations, resource allocation, and performance",
"source_type": "external",
"source_metadata": {
"source": "O-RAN Alliance",
"document_title": "O-RAN AI/ML workflow description and requirements",
"standard_id": "O-RAN.WG2.AIML-v01.03",
"version": "1.03",
"url": "https://www.o-ran.org/specifications",
"date": "2024-02-15"
},
"context": "AI 기술을 RAN에 통합하여 자율적 네트워크 운영 및 최적화 실현. O-RAN 아키텍처의 핵심 기술 방향",
"related_terms": ["RIC", "xApp", "rApp", "Machine Learning", "Network Automation"],
"usage_example": "AI-RAN enables intelligent traffic steering, predictive maintenance, and dynamic spectrum sharing through ML models deployed in RIC",
"confidence": 0.94
},
{
"term_id": "ext-td-002",
"name": "6G Research",
"category": "기술 개발 및 연구",
"definition": "Next generation mobile network technology targeting commercial deployment around 2030, with focus on terahertz communications, AI-native architecture, and holographic communications",
"source_type": "external",
"source_metadata": {
"source": "ITU",
"document_title": "IMT-2030 Framework and overall objectives",
"standard_id": "ITU-R M.2160",
"version": "Draft 1.0",
"url": "https://www.itu.int/en/ITU-R/study-groups/rsg5/",
"date": "2024-01-10"
},
"context": "2030년 상용화 목표의 차세대 이동통신 기술. 테라헤르츠 통신, AI 네이티브, 홀로그램 통신 등 혁신 기술 연구",
"related_terms": ["THz Communication", "AI-Native", "Digital Twin", "Holographic MIMO", "Reconfigurable Intelligent Surface"],
"usage_example": "6G is expected to achieve peak data rates of 1 Tbps and support immersive extended reality (XR) and holographic communications",
"confidence": 0.91
},
{
"term_id": "ext-td-003",
"name": "Digital Twin Network",
"category": "기술 개발 및 연구",
"definition": "Virtual replica of physical network that enables testing, simulation, and optimization without affecting the live network",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "Experiential Networked Intelligence (ENI); Requirements for Digital Twin Networks",
"standard_id": "ETSI GR ENI 023",
"version": "1.1.1",
"url": "https://www.etsi.org/deliver/etsi_gr/ENI/001_099/023/",
"date": "2023-12-05"
},
"context": "물리 네트워크의 디지털 복제본을 생성하여 시뮬레이션 및 최적화 수행. 네트워크 자동화 및 제로 터치 운영의 핵심",
"related_terms": ["Network Simulation", "What-If Analysis", "Intent-Based Networking", "Zero Touch"],
"usage_example": "Digital twin networks enable operators to test network changes and predict their impact before deployment in production",
"confidence": 0.92
},
{
"term_id": "ext-td-004",
"name": "Quantum Communication",
"category": "기술 개발 및 연구",
"definition": "Communication technology leveraging quantum mechanics principles such as quantum entanglement and superposition for ultra-secure data transmission",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "Quantum Key Distribution (QKD); Terminology and definitions",
"standard_id": "ETSI GR QKD 007",
"version": "1.1.1",
"url": "https://www.etsi.org/deliver/etsi_gr/QKD/001_099/007/",
"date": "2023-09-20"
},
"context": "양자역학 원리를 활용한 차세대 보안 통신 기술. 도청 불가능한 절대 보안 통신 실현 목표",
"related_terms": ["QKD", "Quantum Entanglement", "Post-Quantum Cryptography", "Quantum Network"],
"usage_example": "Quantum communication enables theoretically unbreakable encryption through quantum key distribution (QKD) protocols",
"confidence": 0.90
},
{
"term_id": "ext-td-005",
"name": "RIS (Reconfigurable Intelligent Surface)",
"category": "기술 개발 및 연구",
"definition": "Planar surface with electronically controllable electromagnetic properties that can reflect, refract, or absorb radio waves to enhance wireless communication",
"source_type": "external",
"source_metadata": {
"source": "IEEE",
"document_title": "Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities",
"standard_id": "IEEE Trans. Wireless Commun.",
"version": "Vol. 20, No. 3",
"url": "https://ieeexplore.ieee.org/document/9140329",
"date": "2023-11-30"
},
"context": "전자적으로 제어 가능한 메타표면을 이용한 무선 환경 제어 기술. 6G 핵심 기술로 주목받는 혁신적 개념",
"related_terms": ["Metasurface", "Smart Radio Environment", "6G", "Beamforming", "Coverage Enhancement"],
"usage_example": "RIS can improve coverage and capacity by intelligently reflecting signals around obstacles in non-line-of-sight scenarios",
"confidence": 0.89
},
{
"term_id": "ext-td-006",
"name": "THz Communication",
"category": "기술 개발 및 연구",
"definition": "Wireless communication using terahertz frequency band (0.1-10 THz) to achieve ultra-high data rates exceeding 100 Gbps",
"source_type": "external",
"source_metadata": {
"source": "IEEE",
"document_title": "IEEE 802.15 WPAN Terahertz Interest Group (IGTHz)",
"standard_id": "IEEE 802.15-21-0421",
"version": "Draft 2.0",
"url": "https://mentor.ieee.org/802.15/documents",
"date": "2024-01-25"
},
"context": "테라헤르츠 대역을 활용한 초고속 무선 통신 기술. 6G 후보 기술로 100Gbps 이상의 전송속도 목표",
"related_terms": ["6G", "Sub-THz", "Extremely High Frequency", "Molecular Absorption", "Beamforming"],
"usage_example": "THz communication can support data rates of 100+ Gbps but faces challenges in atmospheric absorption and limited range",
"confidence": 0.88
},
{
"term_id": "ext-td-007",
"name": "Federated Learning",
"category": "기술 개발 및 연구",
"definition": "Distributed machine learning approach where model training occurs on decentralized devices without exchanging raw data, preserving privacy",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TS 23.700-81 - Study on architecture enhancements for Federated Learning in 5GS",
"standard_id": "3GPP TR 23.700-81",
"version": "18.0.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/23_series/23.700-81/",
"date": "2024-02-20"
},
"context": "개인정보 보호를 유지하면서 분산 학습을 수행하는 AI 기술. 5G/6G 네트워크의 인텔리전스 향상에 활용",
"related_terms": ["Privacy Preserving", "Distributed ML", "NWDAF", "Edge AI", "Model Aggregation"],
"usage_example": "Federated learning enables training ML models across multiple UEs without centralizing sensitive user data",
"confidence": 0.93
},
{
"term_id": "ext-td-008",
"name": "Network Slicing Orchestration",
"category": "기술 개발 및 연구",
"definition": "Automated management and coordination of network slice lifecycle including creation, configuration, activation, and termination",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "Zero-touch network and Service Management (ZSM); Means of Automation",
"standard_id": "ETSI GS ZSM 002",
"version": "1.1.1",
"url": "https://www.etsi.org/deliver/etsi_gs/ZSM/001_099/002/",
"date": "2023-10-15"
},
"context": "네트워크 슬라이스의 생명주기를 자동으로 관리하는 오케스트레이션 기술. 제로터치 네트워크 운영의 핵심",
"related_terms": ["CSMF", "NSMF", "NSSMF", "Intent-Based", "Zero Touch", "E2E Orchestration"],
"usage_example": "Network slicing orchestration automates the end-to-end management of slice instances across RAN, transport, and core domains",
"confidence": 0.94
},
{
"term_id": "ext-td-009",
"name": "AI-Native Network",
"category": "기술 개발 및 연구",
"definition": "Network architecture designed from the ground up with AI/ML capabilities embedded at every layer for autonomous operation",
"source_type": "external",
"source_metadata": {
"source": "ITU",
"document_title": "Y.3172 - Architectural framework for machine learning in future networks including IMT-2020",
"standard_id": "ITU-T Y.3172",
"version": "06/2019",
"url": "https://www.itu.int/rec/T-REC-Y.3172",
"date": "2023-11-01"
},
"context": "AI가 네트워크 설계 단계부터 통합된 차세대 네트워크 구조. 6G의 핵심 아키텍처 방향",
"related_terms": ["6G", "Network Autonomy", "AI Model Management", "ML Operations", "Self-Optimization"],
"usage_example": "AI-native networks incorporate ML models as fundamental building blocks rather than add-on features",
"confidence": 0.91
},
{
"term_id": "ext-td-010",
"name": "Open RIC (RAN Intelligent Controller)",
"category": "기술 개발 및 연구",
"definition": "Intelligent controller in O-RAN architecture that hosts AI/ML applications (xApps/rApps) for real-time RAN optimization and control",
"source_type": "external",
"source_metadata": {
"source": "O-RAN Alliance",
"document_title": "O-RAN RIC Architecture",
"standard_id": "O-RAN.WG2.RIC-v02.00",
"version": "2.00",
"url": "https://www.o-ran.org/specifications",
"date": "2024-03-01"
},
"context": "O-RAN 아키텍처의 인텔리전스 제어 플랫폼. Near-RT RIC와 Non-RT RIC으로 구성되어 AI 기반 RAN 최적화 수행",
"related_terms": ["xApp", "rApp", "E2 Interface", "A1 Interface", "O-RAN", "AI/ML"],
"usage_example": "The Near-RT RIC hosts xApps for sub-second control loops, while Non-RT RIC hosts rApps for longer-term optimization (>1 second)",
"confidence": 0.95
},
{
"term_id": "ext-td-011",
"name": "Semantic Communication",
"category": "기술 개발 및 연구",
"definition": "Communication paradigm that transmits the meaning and intent of information rather than exact bit sequences, enabling ultra-efficient data transmission",
"source_type": "external",
"source_metadata": {
"source": "IEEE",
"document_title": "Semantic Communications for Future Internet: Fundamentals, Applications, and Challenges",
"standard_id": "IEEE Wireless Commun.",
"version": "Vol. 29, No. 1",
"url": "https://ieeexplore.ieee.org/document/9714762",
"date": "2023-12-15"
},
"context": "정보의 의미와 의도를 전송하는 차세대 통신 패러다임. 6G에서 대역폭 효율을 극대화하는 혁신적 접근",
"related_terms": ["6G", "AI-Native", "Information Theory", "Task-Oriented Communication", "Knowledge Base"],
"usage_example": "Semantic communication can reduce transmission overhead by 90% by sending only meaningful information based on shared context",
"confidence": 0.87
},
{
"term_id": "ext-td-012",
"name": "Intent-Based Networking",
"category": "기술 개발 및 연구",
"definition": "Network management approach where operators specify high-level business intent, and the system automatically translates it into network configurations",
"source_type": "external",
"source_metadata": {
"source": "TMForum",
"document_title": "Autonomous Networks - Intent-driven closed loop assured services",
"standard_id": "TMF921",
"version": "2.0.0",
"url": "https://www.tmforum.org/resources/standard/tmf921",
"date": "2024-01-20"
},
"context": "비즈니스 의도를 고수준으로 표현하면 네트워크가 자동으로 구성을 최적화. 네트워크 자동화의 궁극적 목표",
"related_terms": ["Zero Touch", "Autonomous Network", "Policy Management", "Closed Loop Automation"],
"usage_example": "Intent-based networking allows operators to specify 'ensure 99.999% availability for critical services' without manual configuration",
"confidence": 0.93
},
{
"term_id": "ext-td-013",
"name": "XR (Extended Reality)",
"category": "기술 개발 및 연구",
"definition": "Umbrella term encompassing AR (Augmented Reality), VR (Virtual Reality), and MR (Mixed Reality) technologies enabled by 5G/6G networks",
"source_type": "external",
"source_metadata": {
"source": "3GPP",
"document_title": "TR 26.928 - Extended Reality (XR) in 5G",
"standard_id": "3GPP TR 26.928",
"version": "17.0.0",
"url": "https://www.3gpp.org/ftp/Specs/archive/26_series/26.928/",
"date": "2023-09-30"
},
"context": "AR, VR, MR을 포괄하는 확장현실 기술. 5G/6G의 킬러 애플리케이션으로 초저지연 및 초고속 전송 요구",
"related_terms": ["AR", "VR", "MR", "URLLC", "Cloud Gaming", "Metaverse", "Haptic"],
"usage_example": "XR applications require end-to-end latency below 10ms and sustained data rates of 30-100 Mbps per user",
"confidence": 0.95
},
{
"term_id": "ext-td-014",
"name": "Network Automation",
"category": "기술 개발 및 연구",
"definition": "Use of software and AI/ML to automatically configure, manage, test, deploy, and operate network services with minimal human intervention",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "Zero-touch network and Service Management (ZSM); Reference Architecture",
"standard_id": "ETSI GS ZSM 002",
"version": "1.1.1",
"url": "https://www.etsi.org/deliver/etsi_gs/ZSM/001_099/002/",
"date": "2023-10-15"
},
"context": "AI/ML을 활용하여 네트워크 운영을 자동화하는 기술. 운영 효율성 극대화 및 인적 오류 최소화 목표",
"related_terms": ["Zero Touch", "Closed Loop", "Self-Healing", "Self-Optimization", "MANO"],
"usage_example": "Network automation enables zero-touch provisioning of network services from order to activation in minutes",
"confidence": 0.96
},
{
"term_id": "ext-td-015",
"name": "Cloud Native Network Function",
"category": "기술 개발 및 연구",
"definition": "Network function designed using cloud-native principles including microservices, containerization, and DevOps for agile deployment",
"source_type": "external",
"source_metadata": {
"source": "ETSI",
"document_title": "NFV-IFA 040 - Requirements and Architecture for NFV Release 4",
"standard_id": "ETSI GS NFV-IFA 040",
"version": "4.3.1",
"url": "https://www.etsi.org/deliver/etsi_gs/NFV-IFA/001_099/040/",
"date": "2024-02-10"
},
"context": "클라우드 네이티브 원칙으로 설계된 네트워크 기능. 마이크로서비스, 컨테이너화, DevOps를 통한 민첩한 배포",
"related_terms": ["CNF", "Kubernetes", "Microservices", "Container", "Helm Chart", "Service Mesh"],
"usage_example": "Cloud-native network functions run in containers orchestrated by Kubernetes, enabling rapid scaling and automated lifecycle management",
"confidence": 0.95
}
]
},
{
"domain": "고객 서비스 (Customer Service)",
"samples": [
{
"term_id": "ext-cs-001",
"name": "CSI (Customer Satisfaction Index)",
"category": "고객 서비스",
"definition": "Standardized metric measuring customer satisfaction with products and services, typically on a scale of 0-100",
"source_type": "external",
"source_metadata": {
"source": "ISO",
"document_title": "ISO 10004:2018 - Quality management — Customer satisfaction — Guidelines for monitoring and measuring",
"standard_id": "ISO 10004:2018",
"version": "2018",
"url": "https://www.iso.org/standard/71580.html",
"date": "2023-11-15"
},
"context": "고객 만족도를 측정하는 국제 표준 지표. 통신사 서비스 품질 평가의 핵심 KPI",
"related_terms": ["NPS", "CSAT", "CES", "Quality Management", "Voice of Customer"],
"usage_example": "Telecom operators measure CSI quarterly through standardized surveys to track service quality trends",
"confidence": 0.96
},
{
"term_id": "ext-cs-002",
"name": "NPS (Net Promoter Score)",
"category": "고객 서비스",
"definition": "Customer loyalty metric measuring the likelihood of customers to recommend a company's products or services on a scale of -100 to +100",
"source_type": "external",
"source_metadata": {
"source": "Bain & Company",
"document_title": "The One Number You Need to Grow",
"standard_id": "Harvard Business Review",
"version": "December 2003",
"url": "https://hbr.org/2003/12/the-one-number-you-need-to-grow",
"date": "2023-10-20"
},
"context": "고객 충성도와 추천 의향을 측정하는 핵심 지표. 통신업계에서 브랜드 경쟁력 평가에 널리 활용",
"related_terms": ["Promoter", "Passive", "Detractor", "Customer Loyalty", "Word of Mouth"],
"usage_example": "Customers rating 9-10 are Promoters, 7-8 are Passives, and 0-6 are Detractors in NPS methodology",
"confidence": 0.97
},
{
"term_id":="ext-cs-003",
"name": "CSAT (Customer Satisfaction Score)",
"category": "고객 서비스",
"definition": "Short-term satisfaction metric measuring customer happiness with a specific interaction or transaction, typically on a 1-5 scale",
"source_type": "external",
"source_metadata": {
"source": "ITU",
"document_title": "E.800 - Definitions of terms related to quality of service",
"standard_id": "ITU-T E.800",
"version": "09/2008",
"url": "https://www.itu.int/rec/T-REC-E.800",
"date": "2023-09-25"
},
"context": "특정 상호작용에 대한 즉각적 만족도 측정. 콜센터, 매장 방문 등 개별 접점 품질 평가에 활용",
"related_terms": ["Transaction Satisfaction", "Touch Point", "Service Quality", "First Call Resolution"],
"usage_example": "CSAT surveys are typically sent immediately after customer service interactions to measure satisfaction while the experience is fresh",
"confidence": 0.95
},
{
"term_id": "ext-cs-004",
"name": "FCR (First Call Resolution)",
"category": "고객 서비스",
"definition": "Contact center metric measuring the percentage of customer inquiries resolved during the first interaction without callbacks or escalations",
"source_type": "external",
"source_metadata": {
"source": "ICMI",
"document_title": "Call Center Management on Fast Forward: Succeeding in the New Era of Customer Experience",
"standard_id": "Industry Best Practice",
"version": "4th Edition",
"url": "https://www.icmi.com/resources",
"date": "2023-12-01"
},
"context": "첫 통화에서 고객 문의를 해결하는 비율. 고객 만족도와 운영 효율성의 핵심 지표",
"related_terms": ["AHT", "Call Center", "Customer Effort Score", "Resolution Rate"],
"usage_example": "Industry benchmark for FCR in telecom contact centers is 70-75%, with top performers achieving 80%+",
"confidence": 0.94
},
{
"term_id": "ext-cs-005",
"name": "AHT (Average Handle Time)",
"category": "고객 서비스",
"definition": "Contact center metric measuring the average duration of a customer interaction including talk time, hold time, and after-call work",
"source_type": "external",
"source_metadata": {
"source": "COPC Inc.",
"document_title": "COPC CX Standard for Contact Centers",
"standard_id": "COPC CX 7.0",
"version": "7.0",
"url": "https://www.copc.com/standards/",
"date": "2024-01-10"
},
"context": "콜센터 상담원의 평균 처리 시간 측정. 효율성과 서비스 품질 균형의 핵심 지표",
"related_terms": "Talk Time", "Hold Time", "ACW", "Service Level", "Occupancy Rate"],
"usage_example": "Typical AHT for telecom customer service ranges from 5-8 minutes, balancing efficiency with quality resolution",
"confidence": 0.96
},
{
"term_id": "ext-cs-006",
"name": "CES (Customer Effort Score)",
"category": "고객 서비스",
"definition": "Metric measuring the ease of customer experience by asking 'How easy was it to interact with our company?' on a scale of 1-7",
"source_type": "external",
"source_metadata": {
"source": "Gartner",
"document_title": "Effortless Experience: Conquering the New Battleground for Customer Loyalty",
"standard_id": "Industry Research",
"version": "2013",
"url": "https://www.gartner.com/en/customer-service-support",
"date": "2023-10-30"
},
"context": "고객이 문제 해결에 들인 노력의 정도를 측정. 낮은 노력이 높은 충성도로 연결됨을 입증",
"related_terms": ["Customer Effort", "Ease of Use", "Self-Service", "Omnichannel", "Journey Mapping"],
"usage_example": "Research shows 96% of customers with high-effort experiences become disloyal, compared to only 9% with low-effort experiences",
"confidence": 0.93
},
{
"term_id": "ext-cs-007",
"name": "SLA (Service Level Agreement)",
"category": "고객 서비스",
"definition": "Formal commitment defining the level of service expected from a service provider, including metrics, responsibilities, and remedies",
"source_type": "external",
"source_metadata": {
"source": "ITU",
"document_title": "M.3080 - Management of the business agreement and its related SLA for TMN services",
"standard_id": "ITU-T M.3080",
"version": "10/2006",
"url": "https://www.itu.int/rec/T-REC-M.3080",
"date": "2023-11-05"
},
"context": "서비스 제공자와 고객 간의 공식적인 서비스 수준 약정. 품질 보증 및 책임 소재 명확화",
"related_terms": ["Uptime", "Response Time", "MTTR", "Penalty Clause", "Service Credits"],
"usage_example": "Enterprise SLAs typically guarantee 99.9% network uptime with financial penalties for non-compliance",
"confidence": 0.97
},
{
"term_id": "ext-cs-008",
"name": "Omnichannel Experience",
"category": "고객 서비스",
"definition": "Integrated customer experience strategy providing seamless interaction across all channels (phone, web, mobile, social, store) with consistent service",
"source_type": "external",
"source_metadata": {
"source": "TMForum",
"document_title": "GB988 - Customer Experience Management",
"standard_id": "TMF GB988",
"version": "6.0.0",
"url": "https://www.tmforum.org/resources/standard/gb988",
"date": "2024-02-15"
},
"context": "모든 채널에서 일관되고 통합된 고객 경험 제공. 채널 전환 시에도 맥락이 유지되는 서비스",
"related_terms": ["Multichannel", "Channel Integration", "Customer Journey", "Unified Commerce", "Cross-Channel"],
"usage_example": "Omnichannel strategy allows customers to start a transaction on mobile app and complete it at a physical store with full context",
"confidence": 0.95
},
{
"term_id": "ext-cs-009",
"name": "Voice of Customer (VoC)",
"category": "고객 서비스",
"definition": "Systematic process of capturing customers' expectations, preferences, and aversions to drive business improvements",
"source_type": "external",
"source_metadata": {
"source": "ISO",
"document_title": "ISO 10001:2018 - Quality management — Customer satisfaction — Guidelines for codes of conduct",
"standard_id": "ISO 10001:2018",
"version": "2018",
"url": "https://www.iso.org/standard/69558.html",
"date": "2023-12-20"
},
"context": "고객의 의견과 요구사항을 체계적으로 수집·분석하여 서비스 개선에 반영하는 프로세스",
"related_terms": ["Customer Feedback", "Survey", "Social Listening", "Sentiment Analysis", "Customer Insight"],
"usage_example": "VoC programs combine multiple data sources including surveys, social media, call center interactions, and complaints to understand customer needs",
"confidence": 0.94
},
{
"term_id": "ext-cs-010",
"name": "Customer Journey Mapping",
"category": "고객 서비스",
"definition": "Visual representation of every experience customers have with a service, product, or brand across all touchpoints and channels",
"source_type": "external",
"source_metadata": {
"source": "TMForum",
"document_title": "TR257 - Customer Experience Framework",
"standard_id": "TMF TR257",
"version": "1.0.0",
"url": "https://www.tmforum.org/resources/technical-report/tr257",
"date": "2024-01-05"
},
"context": "고객이 서비스를 인지하고 구매·사용·이탈하는 전 과정을 시각화하여 개선점 도출",
"related_terms": ["Touch Point", "Pain Point", "Moment of Truth", "Customer Experience", "Persona"],
"usage_example": "Journey maps identify pain points such as long wait times during activation or confusing bill formats that drive customer dissatisfaction",
"confidence": 0.93
},
{
"term_id": "ext-cs-011",
"name": "Churn Prediction",
"category": "고객 서비스",
"definition": "Use of data analytics and machine learning to identify customers at risk of canceling service, enabling proactive retention efforts",
"source_type": "external",
"source_metadata": {
"source": "TMForum",
"document_title": "IG1230 - Big Data Analytics Implementation Guide",
"standard_id": "TMF IG1230",
"version": "2.1.0",
"url": "https://www.tmforum.org/resources/implementation-guide/ig1230",
"date": "2024-02-25"
},
"context": "데이터 분석 및 ML을 활용하여 이탈 위험 고객을 사전에 식별하고 선제적 유지 활동 수행",
"related_terms": ["Retention", "Customer Lifetime Value", "Propensity Model", "Predictive Analytics", "At-Risk Customer"],
"usage_example": "Churn prediction models analyze usage patterns, payment history, service complaints, and competitive offers to identify high-risk customers",
"confidence": 0.95
},
{
"term_id": "ext-cs-012",
"name": "Self-Service Portal",
"category": "고객 서비스",
"definition": "Digital platform enabling customers to perform service-related tasks independently without agent assistance, including account management and troubleshooting",
"source_type": "external",
"source_metadata": {
"source": "Gartner",
"document_title": "Magic Quadrant for Customer Service and Support Technologies",
"standard_id": "Gartner Research",
"version": "2023",
"url": "https://www.gartner.com/en/customer-service-support",
"date": "2023-11-10"
},
"context": "고객이 상담원 도움 없이 스스로 계정관리, 요금조회, 문제해결 등을 수행할 수 있는 디지털 플랫폼",
"related_terms": ["Digital Channel", "IVR", "Chatbot", "Knowledge Base", "FAQ", "Automation"],
"usage_example": "Modern self-service portals deflect 40-60% of routine inquiries, reducing call center volume and improving customer satisfaction",
"confidence": 0.96
},
{
"term_id": "ext-cs-013",
"name": "Proactive Customer Care",
"category": "고객 서비스",
"definition": "Service approach that anticipates and addresses customer needs before they contact support, using predictive analytics and automation",
"source_type": "external",
"source_metadata": {
"source": "Forrester",
"document_title": "The Future Of Customer Service: Proactive, Predictive, And Profitable",
"standard_id": "Forrester Research",
"version": "Q2 2023",
"url": "https://www.forrester.com/report/",
"date": "2023-09-15"
},
"context": "문제 발생을 예측하고 고객이 연락하기 전에 선제적으로 해결책을 제공하는 서비스 방식",
"related_terms": ["Predictive Analytics", "Network Monitoring", "Outage Notification", "Usage Alert", "Preventive Maintenance"],
"usage_example": "Proactive care includes notifying customers of network outages before they experience issues or alerting them to unusual data usage patterns",
"confidence": 0.94
},
{
"term_id": "ext-cs-014",
"name": "Customer Segmentation",
"category": "고객 서비스",
"definition": "Process of dividing customers into groups based on common characteristics, behaviors, or needs to deliver targeted services and communications",
"source_type": "external",
"source_metadata": {
"source": "TMForum",
"document_title": "GB922 - Customer Business Entity Definitions",
"standard_id": "TMF GB922",
"version": "19.0.0",
"url": "https://www.tmforum.org/resources/standard/gb922",
"date": "2024-01-30"
},
"context": "고객을 특성, 행동, 니즈 기반으로 그룹화하여 맞춤형 서비스 및 커뮤니케이션 제공",
"related_terms": ["Customer Profiling", "Persona", "Value-Based Segmentation", "Behavioral Segmentation", "CLV"],
"usage_example": "Telecom operators segment customers into high-value, mid-tier, and basic groups to tailor retention offers and service levels",
"confidence": 0.95
},
{
"term_id": "ext-cs-015",
"name": "Real-Time Personalization",
"category": "고객 서비스",
"definition": "Dynamic customization of customer interactions and offers based on real-time data, context, and behavioral signals",
"source_type": "external",
"source_metadata": {
"source": "Gartner",
"document_title": "Predicts 2024: Customer Service and Support Technologies",
"standard_id": "Gartner Research",
"version": "2024",
"url": "https://www.gartner.com/en/customer-service-support",
"date": "2024-02-05"
},
"context": "실시간 데이터와 컨텍스트 기반으로 고객 상호작용 및 제안을 동적으로 맞춤화",
"related_terms": ["AI/ML", "Recommendation Engine", "Next Best Action", "Contextual Offer", "Dynamic Content"],
"usage_example": "Real-time personalization engines analyze customer location, device, usage patterns, and browsing behavior to present relevant offers instantly",
"confidence": 0.93
}
]
}
]
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