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NLU

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JD Tech Talk
JD Tech Talk
Mar 5, 2025 · Artificial Intelligence

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

GLM introduces a unified pretraining framework that combines autoregressive blank‑filling with 2D positional encoding and span‑shuffle, achieving superior performance over BERT, T5 and GPT on a range of NLU and generation tasks such as SuperGLUE, text‑filling, and language modeling.

2D positional encodingNLUautoregressive
0 likes · 27 min read
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
Laiye Technology Team
Laiye Technology Team
Aug 29, 2022 · Artificial Intelligence

Evolution of Dialogue Management: From Rule‑Based to Data‑Driven Systems and Industrial Deployments

This article reviews the historical development of dialogue management—from early rule‑based and finite‑state approaches to modern data‑driven and reinforcement‑learning methods—and examines how major industry platforms such as Amazon Alexa, Amazon Lex, and RASA implement these techniques in practice.

Amazon AlexaDialogue ManagementNLU
0 likes · 16 min read
Evolution of Dialogue Management: From Rule‑Based to Data‑Driven Systems and Industrial Deployments
DataFunTalk
DataFunTalk
Dec 16, 2021 · Artificial Intelligence

OPPO XiaoBu Assistant: Building a Low‑Code, End‑to‑End Dialogue System Platform

This article presents OPPO's XiaoBu Assistant platform, detailing its low‑code workflow for business domain modeling, multi‑type NLU (model‑based, retrieval‑based, and QA), componentized core services, large‑scale text processing, vector retrieval, and flexible dialogue management that together enable a complete skill lifecycle from development to online optimization.

AINLUconversation management
0 likes · 18 min read
OPPO XiaoBu Assistant: Building a Low‑Code, End‑to‑End Dialogue System Platform
DataFunTalk
DataFunTalk
Nov 15, 2020 · Artificial Intelligence

Query Intent Recognition in Vertical Search: Challenges, Methods, and Case Studies

The article reviews the importance of query intent recognition in vertical search, outlines its definition, highlights practical challenges such as ambiguous input, multi‑intent queries, timeliness and cold‑start issues, and surveys common rule‑based, statistical, and machine‑learning solutions together with real‑world case studies.

Entity RecognitionNLUSearch
0 likes · 17 min read
Query Intent Recognition in Vertical Search: Challenges, Methods, and Case Studies
Ctrip Technology
Ctrip Technology
Nov 7, 2019 · Artificial Intelligence

Intelligent Customer Service in Travel: System Architecture and Key Technologies

This article explains the architecture and core technologies of Ctrip’s intelligent travel customer service, covering NLU, dialogue state tracking, policy learning, intent and slot extraction, multi‑round task bots, and the supporting platform for deployment and future multimodal extensions.

AIChatbotDialogue Management
0 likes · 12 min read
Intelligent Customer Service in Travel: System Architecture and Key Technologies
58 Tech
58 Tech
Oct 16, 2019 · Artificial Intelligence

Design and Implementation of Intent Recognition, Semantic Similarity Matching, and Slot Filling for a Voice Robot

This article details the architecture and algorithms behind a voice robot's natural language understanding module, covering single‑sentence intent classification with TextCNN, acoustic quality detection using VGGish‑BiLSTM, semantic similarity matching via DSSM and TextCNN‑Transformer, and slot‑filling with IDCNN‑CRF, along with performance results and future directions.

AINLUTextCNN
0 likes · 11 min read
Design and Implementation of Intent Recognition, Semantic Similarity Matching, and Slot Filling for a Voice Robot
58 Tech
58 Tech
Aug 14, 2019 · Artificial Intelligence

Design and Implementation of a Dialogue Management System for Intelligent Voice Robots

This article presents a comprehensive overview of an intelligent voice robot's dialogue management system, detailing its architecture, natural language understanding components, dialogue manager design, strategy handling, and workflow processes to achieve fluent multi‑turn interactions in telephone scenarios.

AIDialogue ManagementNLU
0 likes · 14 min read
Design and Implementation of a Dialogue Management System for Intelligent Voice Robots
Beike Product & Technology
Beike Product & Technology
May 23, 2019 · Artificial Intelligence

Applying Knowledge Graph Technology to Real Estate Search: Product Overview and Technical Architecture

This article introduces the "Kelu Fang" product, which leverages knowledge graph, NLU, and ranking technologies to enhance real‑estate search by adding commute‑based filtering and a local view of surrounding facilities, and discusses its architecture, implementation details, and future improvement directions.

AINLUReal Estate
0 likes · 11 min read
Applying Knowledge Graph Technology to Real Estate Search: Product Overview and Technical Architecture
360 Quality & Efficiency
360 Quality & Efficiency
May 10, 2019 · Artificial Intelligence

Smart Speaker Voice Interaction Platform: Concepts, Processes, and Testing Metrics

This article introduces the architecture of smart speaker voice interaction systems, covering wake‑word activation, automatic speech recognition (ASR), natural language understanding (NLU), skill processing, text‑to‑speech synthesis (TTS), and the key performance and testing metrics for each component.

ASRNLUTTS
0 likes · 11 min read
Smart Speaker Voice Interaction Platform: Concepts, Processes, and Testing Metrics
DataFunTalk
DataFunTalk
Jul 26, 2018 · Artificial Intelligence

Natural Language Understanding in the Music Domain: Architecture, Features, and Challenges

The article details the design and implementation of Xiaomi's music‑focused natural language understanding platform, covering its service architecture, intent extraction, knowledge‑base search, slot filling, personalization, and the specific data and modeling challenges encountered.

ASRMusicNLU
0 likes · 9 min read
Natural Language Understanding in the Music Domain: Architecture, Features, and Challenges