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283 articles · Page 3 of 3
DataFunTalk
DataFunTalk
May 23, 2020 · Artificial Intelligence

iQIYI Deep Semantic Representation Learning Framework for Video Recommendation and Search

Based on academic and industry experience, iQIYI has designed a deep semantic representation learning framework that integrates multimodal side information and deep models such as Transformers and graph neural networks, improving recall, ranking, deduplication, diversity and semantic matching across recommendation and search scenarios.

MultimodalRecommendation Systemsdeep learning
0 likes · 27 min read
iQIYI Deep Semantic Representation Learning Framework for Video Recommendation and Search
Programmer DD
Programmer DD
May 16, 2020 · Databases

Master Elasticsearch SQL: From Basic Queries to Advanced DSL Translations

This article walks through using Elasticsearch SQL to query data, covering installation, loading sample datasets, describing index schemas, executing simple and complex SQL queries with functions, converting SQL to Elasticsearch DSL, reindexing, alias management, and performance considerations, all illustrated with code snippets.

ElasticsearchKibanaSQL
0 likes · 15 min read
Master Elasticsearch SQL: From Basic Queries to Advanced DSL Translations
iQIYI Technical Product Team
iQIYI Technical Product Team
May 15, 2020 · Artificial Intelligence

iQIYI Deep Semantic Representation Learning Framework: Design, Challenges, and Applications

iQIYI’s deep semantic representation learning framework integrates multimodal content, knowledge graphs, and user behavior through layered data, feature, strategy, and application components, employing early, late, and hybrid fusion with Transformers, GCNs, and other deep models to deliver high‑quality embeddings that boost recommendation, search, and streaming performance across dozens of business scenarios.

Multimodalgraph neural networksiQIYI
0 likes · 28 min read
iQIYI Deep Semantic Representation Learning Framework: Design, Challenges, and Applications
Big Data Technology Architecture
Big Data Technology Architecture
May 8, 2020 · Big Data

Comparative Analysis of Elasticsearch and Its Competing Products

This article provides a comprehensive comparison of Elasticsearch with its major competing technologies—including Lucene, Solr, relational databases, OpenTSDB, HBase, MongoDB, ClickHouse, and Druid—highlighting each product’s strengths, weaknesses, and suitable application scenarios, and concluding that Elasticsearch generally outperforms alternatives in search and many data use cases.

Data PlatformsElasticsearchproduct comparison
0 likes · 14 min read
Comparative Analysis of Elasticsearch and Its Competing Products
Youzan Coder
Youzan Coder
Apr 7, 2020 · Backend Development

Building Youzan's Enterprise Search Platform: Architecture, Indexing & Scaling

This article explores Youzan's enterprise search middle platform, detailing the challenges of siloed architectures, the concept of cognitive folding, comprehensive index design, write/read mechanisms, configuration-driven routing, monitoring, and practical implementations that enable scalable, reusable search capabilities across diverse business domains.

Backend ArchitectureIndexingScalable Systems
0 likes · 16 min read
Building Youzan's Enterprise Search Platform: Architecture, Indexing & Scaling
ITPUB
ITPUB
Mar 12, 2020 · Fundamentals

Master Precise GitHub Project Search: Tips, Filters, and Code Snippets

Learn how to efficiently locate high‑quality open‑source projects on GitHub by understanding project components, using targeted search qualifiers like name, stars, forks, README, description, language, and recent activity, and applying practical code examples to narrow results to the most relevant repositories.

FiltersGitHubcode
0 likes · 5 min read
Master Precise GitHub Project Search: Tips, Filters, and Code Snippets
Liangxu Linux
Liangxu Linux
Mar 9, 2020 · Fundamentals

How to Precisely Find Open‑Source Projects on GitHub

Learn step‑by‑step techniques to narrow down GitHub search results using filters like name, description, stars, forks, language, and last update date, so you can quickly locate high‑quality open‑source projects for practice.

FiltersREADMEforks
0 likes · 6 min read
How to Precisely Find Open‑Source Projects on GitHub
Programmer DD
Programmer DD
Feb 29, 2020 · Fundamentals

Master Precise GitHub Project Search: Tips, Filters, and Code Snippets

This guide teaches developers how to efficiently locate open‑source projects on GitHub by using advanced search qualifiers such as name, README, description, star/fork counts, language, and recent update dates, complete with practical code examples and visual results.

FiltersGitHubProject Discovery
0 likes · 6 min read
Master Precise GitHub Project Search: Tips, Filters, and Code Snippets
Python Programming Learning Circle
Python Programming Learning Circle
Feb 20, 2020 · Fundamentals

Binary Search Algorithm Explanation

This article explains the binary search algorithm for locating a target element in a sorted array, describing its midpoint‑starting process, halving of the search range, termination conditions, and includes a simple example with its output.

Algorithmbinary searchfundamentals
0 likes · 3 min read
Binary Search Algorithm Explanation
Liangxu Linux
Liangxu Linux
Feb 11, 2020 · Fundamentals

Master GitHub Search: Advanced Filters and Query Tricks

This guide explains how to use GitHub's advanced search syntax, including keyword filters, qualifiers, auxiliary qualifiers, and sorting options, with practical examples and code snippets that help you locate precise repositories, files, or issues efficiently.

Filterscodedeveloper tools
0 likes · 6 min read
Master GitHub Search: Advanced Filters and Query Tricks
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 20, 2020 · Big Data

Alibaba’s Secrets to High‑Throughput Full‑Load and Low‑Latency Search Processing

This article details how Alibaba migrated its massive Taobao‑Tmall search workload to the search offline platform, tackling challenges of massive data volume, one‑to‑many joins, and hotspot sellers through a series of performance optimizations—including local joins, salt‑based data sharding, dynamic aggregation jobs, and asynchronous processing—to achieve high‑throughput full loads and low‑latency incremental updates.

AlibabaBig DataFlink
0 likes · 15 min read
Alibaba’s Secrets to High‑Throughput Full‑Load and Low‑Latency Search Processing
Big Data Technology & Architecture
Big Data Technology & Architecture
Jan 19, 2020 · Big Data

Tencent's Elasticsearch Practices: Application Scenarios, Challenges, Optimizations, and Future Directions

This article details how Tencent leverages Elasticsearch for log analysis, search services, and time‑series data, outlines the specific challenges faced in high‑availability and cost‑efficiency, and presents the comprehensive optimization techniques and future open‑source contributions that improve performance, scalability, and reliability.

Big DataElasticsearchHigh Availability
0 likes · 16 min read
Tencent's Elasticsearch Practices: Application Scenarios, Challenges, Optimizations, and Future Directions
DataFunTalk
DataFunTalk
Jan 2, 2020 · Artificial Intelligence

Improving Zhihu Search: Query Understanding, Term Weighting, Synonym Expansion, Query Rewriting, and Semantic Retrieval

This article details Zhihu's search engineering advances over the past year, covering long‑tail query challenges, term‑weight calculation, synonym expansion, query rewriting with translation models and reinforcement learning, and semantic retrieval using BERT‑based embeddings, while outlining future research directions.

NLPQuery Rewritingquery understanding
0 likes · 14 min read
Improving Zhihu Search: Query Understanding, Term Weighting, Synonym Expansion, Query Rewriting, and Semantic Retrieval
Architect's Tech Stack
Architect's Tech Stack
Dec 25, 2019 · Backend Development

Elasticsearch Optimization Practices for Large-Scale Data Platforms

This article explains the architecture of Elasticsearch and Lucene, outlines common performance bottlenecks, and provides concrete indexing and query optimization techniques—including shard routing, refresh intervals, doc values, and hardware considerations—to achieve sub‑second query responses on billions of records.

ElasticsearchIndexingLucene
0 likes · 12 min read
Elasticsearch Optimization Practices for Large-Scale Data Platforms
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 27, 2019 · Artificial Intelligence

How Gaode Map Boosted Search Suggestions with Learning-to-Rank

Gaode Map revamped its search suggestion service by replacing rule‑based ranking with a Learning‑to‑Rank model, detailing challenges in sample construction, feature engineering, loss‑function tuning, and the resulting performance gains across millions of queries and diverse geographic regions.

Feature-EngineeringLBSLearning-to-Rank
0 likes · 11 min read
How Gaode Map Boosted Search Suggestions with Learning-to-Rank
HomeTech
HomeTech
Nov 13, 2019 · Artificial Intelligence

Sequence Labeling for Entity Recognition in Automotive Search: Techniques and Applications

This article examines how sequence labeling methods such as pattern matching, CRF, and deep‑learning models like BiLSTM‑CRF and BERT are applied to automotive search tasks—including car‑series, model, and location/entity recognition—detailing their development, implementation challenges, and performance results.

AutomotiveBERTCRF
0 likes · 11 min read
Sequence Labeling for Entity Recognition in Automotive Search: Techniques and Applications
Big Data Technology Architecture
Big Data Technology Architecture
Sep 26, 2019 · Databases

Elasticsearch Core Overview and Key Performance Metrics

This article provides a comprehensive guide to Elasticsearch’s architecture, node roles, data organization, and the most important performance metrics—including search, indexing, memory, JVM garbage collection, host‑level system metrics, cluster health, and resource saturation—offering practical advice on monitoring and tuning the cluster for reliability and efficiency.

Cluster ManagementElasticsearchIndexing
0 likes · 27 min read
Elasticsearch Core Overview and Key Performance Metrics
Youku Technology
Youku Technology
Sep 4, 2019 · Backend Development

Technical Deep Dive of Youku Media Asset Platform: Storage, Search, and Data Aggregation

The article details Youku’s new media‑asset platform, which replaces a fragmented MySQL‑based system with a domain‑driven entity model stored in Ali‑HBase, leverages Elasticsearch for flexible front‑and back‑end search, and adds an aggregation layer that unifies diverse data sources and reusable computation tasks, delivering high‑availability, low‑latency service for billions of daily API calls.

Elasticsearchdata aggregationmedia asset
0 likes · 9 min read
Technical Deep Dive of Youku Media Asset Platform: Storage, Search, and Data Aggregation
MaGe Linux Operations
MaGe Linux Operations
Sep 1, 2019 · Fundamentals

10 Must‑Know Hand‑Coding Interview Algorithms Every Developer Should Master

This article presents the ten most frequently asked hand‑coding interview problems—quick sort, binary search, climbing stairs, two‑sum, max drawdown, merging sorted arrays, maximum subarray, longest non‑repeating substring, permutations, and three‑sum—each with clear Python implementations, difficulty ratings, occurrence probabilities, and sample outputs to boost your interview success.

AlgorithmPythoncoding interview
0 likes · 13 min read
10 Must‑Know Hand‑Coding Interview Algorithms Every Developer Should Master
Architecture Digest
Architecture Digest
Jul 5, 2019 · Operations

The Story of Elasticsearch and the Elastic Stack: From Origins to ELK

This article narrates the origin and evolution of Elasticsearch, its underlying Lucene technology, the surrounding Elastic Stack components such as Logstash, Kibana, and Beats, and illustrates how they together provide powerful search, logging, monitoring, and analytics solutions for modern applications.

BeatsElastic StackKibana
0 likes · 11 min read
The Story of Elasticsearch and the Elastic Stack: From Origins to ELK
21CTO
21CTO
Jul 2, 2019 · Backend Development

Designing a Scalable Feed Stream System for Billions of Users

This article explains how to design a high‑performance feed‑stream architecture—including product definition, data modeling, storage choices, synchronization modes, metadata handling, commenting, likes, sorting, search, and deletion—so that a system can support tens of millions to billions of users while remaining reliable and scalable.

Metadatafeed streamscalability
0 likes · 21 min read
Designing a Scalable Feed Stream System for Billions of Users
Youzan Coder
Youzan Coder
Jun 28, 2019 · Mobile Development

Designing a Modular Retail POS System with Offline Synchronization and Search

The article outlines a modular retail POS architecture that separates store, transaction, product, and marketing components, stores product data locally for offline checkout, uses incremental synchronization and cross‑platform pinyin conversion for fuzzy search, and decouples modules via JSON protocols to ensure scalability and reliability.

Hardware integrationModular ArchitecturePOS
0 likes · 18 min read
Designing a Modular Retail POS System with Offline Synchronization and Search
Programmer DD
Programmer DD
Jun 28, 2019 · Backend Development

Master Elasticsearch with Jest: A Hands‑On Java Client Guide

This tutorial walks you through using Jest, a fluent Java HTTP client for Elasticsearch, covering Maven setup, creating a reusable client, performing CRUD operations, bulk and asynchronous requests, and showcases code examples that illustrate how to manage indices and documents efficiently.

ClientElasticsearchJest
0 likes · 12 min read
Master Elasticsearch with Jest: A Hands‑On Java Client Guide
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.

AIKnowledge GraphNLU
0 likes · 11 min read
Applying Knowledge Graph Technology to Real Estate Search: Product Overview and Technical Architecture
DataFunTalk
DataFunTalk
May 23, 2019 · Artificial Intelligence

AI Techniques in Xiaomi Mobile Search: Text Relevance, Intent Recognition, and Click‑Model Ranking

The article presents Xiaomi's mobile search system, detailing how AI methods such as deep learning, GBDT and DNN models are applied to text relevance calculation, intent detection with term‑weighting, and click‑through ranking models (PBM, Cascade, DBN) to improve user experience across heterogeneous result types.

AIRankingclick models
0 likes · 9 min read
AI Techniques in Xiaomi Mobile Search: Text Relevance, Intent Recognition, and Click‑Model Ranking
NetEase Game Operations Platform
NetEase Game Operations Platform
May 5, 2019 · Fundamentals

Fast Search Tools Comparison: ripgrep and Its Alternatives

This article compares the speed and features of various command‑line search utilities—including grep, The Platinum Searcher, ucg, ack, sift, The Silver Searcher, git‑grep and ripgrep—provides benchmark tables for directory and file searches, and outlines ripgrep's capabilities and editor integrations.

Command LineRegexripgrep
0 likes · 8 min read
Fast Search Tools Comparison: ripgrep and Its Alternatives
Suning Technology
Suning Technology
Apr 28, 2019 · Big Data

Unlocking Real-Time Big Data Insights: Suning’s Elastic-Powered Smart Retail Journey

The April 27 Elastic Nanjing Technical Exchange, co‑hosted by Suning Technology and the Elastic Chinese community, showcased how Suning leverages Elasticsearch, Logstash, Kibana and Beats for real‑time search, log analysis, security, and smart‑retail applications, featuring expert case studies and future big‑data strategies.

Smart Retailelasticlog analysis
0 likes · 6 min read
Unlocking Real-Time Big Data Insights: Suning’s Elastic-Powered Smart Retail Journey
DataFunTalk
DataFunTalk
Apr 19, 2019 · Artificial Intelligence

E-commerce Search and User Guidance: Concepts, Techniques, and Product Design

This article examines the role of search as a user guidance channel in e-commerce, outlining product requirements, user flow stages, and various algorithmic solutions—including query understanding, suggestion, rewriting, retrieval, and ranking—while also comparing implementations across major Chinese platforms.

Rankinge-commercemachine learning
0 likes · 29 min read
E-commerce Search and User Guidance: Concepts, Techniques, and Product Design
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 8, 2019 · Artificial Intelligence

How Alibaba Builds a Massive E‑Commerce Concept Graph to Power Search & Recommendation

This article explains how Alibaba’s Search & Recommendation team constructs a large‑scale e‑commerce concept graph—defining e‑commerce concepts, mining them from queries and titles, building an ontology, linking concepts to entities, and applying the graph to improve personalized search and recommendation.

Knowledge Graphconcept mininge-commerce
0 likes · 19 min read
How Alibaba Builds a Massive E‑Commerce Concept Graph to Power Search & Recommendation
System Architect Go
System Architect Go
Feb 9, 2019 · Backend Development

Elasticsearch Performance Optimization: General Recommendations, Indexing Speed, Search Speed, and Disk Usage

This guide presents comprehensive Elasticsearch tuning strategies—including limiting result sets, avoiding large documents, optimizing indexing with bulk requests and refresh intervals, enhancing search speed through field modeling and caching, and reducing disk usage via compression and shard management—to improve both indexing and query performance.

Indexingbackendsearch
0 likes · 13 min read
Elasticsearch Performance Optimization: General Recommendations, Indexing Speed, Search Speed, and Disk Usage
System Architect Go
System Architect Go
Jan 29, 2019 · Backend Development

Elasticsearch Query DSL Overview: Queries, Filters, and Advanced Types

This article provides a comprehensive overview of Elasticsearch's Query DSL, explaining its purpose, the distinction between leaf and compound queries, query versus filter contexts, and detailing a wide range of query types including full‑text, term‑level, compound, joining, geo, specialized, and span queries.

FiltersQuery DSLbackend
0 likes · 8 min read
Elasticsearch Query DSL Overview: Queries, Filters, and Advanced Types
58 Tech
58 Tech
Jan 25, 2019 · Backend Development

Search Engineering Architecture: Lessons from Zhihu and 58 Group

The article summarizes the evolution and redesign of Zhihu's search engine, details 58 Group's high‑performance uesearch architecture, real‑time indexing mechanisms, cloud‑native deployment with Kubernetes, and highlights key technical insights and future directions for large‑scale search systems.

KubernetesRustarchitecture
0 likes · 9 min read
Search Engineering Architecture: Lessons from Zhihu and 58 Group
MaGe Linux Operations
MaGe Linux Operations
Jan 23, 2019 · Big Data

How Bloom Filters Power Fast Big Data Searches with Python

This tutorial walks through building a simple Python search engine for big data, covering Bloom filter basics, tokenization with major and minor segmentation, inverted index creation, and implementing both simple and complex (AND/OR) queries, complete with code examples and visual illustrations.

AND/OR queriesBig DataBloom filter
0 likes · 15 min read
How Bloom Filters Power Fast Big Data Searches with Python
dbaplus Community
dbaplus Community
Jan 3, 2019 · Backend Development

Supercharging Elasticsearch for Billion-Row Queries: Practical Tips

This guide details how to optimize Elasticsearch for handling billions of daily records, covering core Lucene concepts, index and shard configuration, performance‑tuning parameters, and practical testing methods to achieve sub‑second query responses and long‑term data retention.

Big DataElasticsearchIndexing
0 likes · 13 min read
Supercharging Elasticsearch for Billion-Row Queries: Practical Tips
Qunar Tech Salon
Qunar Tech Salon
Dec 18, 2018 · Big Data

Practical Insights on Deploying and Operating Elasticsearch at Scale

This article shares extensive practical experience from Qunar's large‑scale Elasticsearch deployment, covering suitable use cases, index‑type design, document ID strategies, scaling considerations for index and data volume, hardware sizing, and storage architecture recommendations to help newcomers avoid common pitfalls.

Big DataElasticsearchIndexing
0 likes · 10 min read
Practical Insights on Deploying and Operating Elasticsearch at Scale
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 16, 2018 · Artificial Intelligence

How Alibaba’s Search Engine Evolved Over a Decade of Double‑11: From Offline Models to Real‑Time AI

This article traces the ten‑year evolution of Alibaba’s e‑commerce search system, detailing four major stages—from the early Pora streaming engine to dual‑link real‑time architectures, the integration of deep and reinforcement learning, and the shift to large‑scale online deep learning—while highlighting the technical drivers and future AI‑enabled search vision.

e-commercemachine learningonline learning
0 likes · 16 min read
How Alibaba’s Search Engine Evolved Over a Decade of Double‑11: From Offline Models to Real‑Time AI
Programmer DD
Programmer DD
Oct 6, 2018 · Big Data

Elastic Search IPO: What It Means for Search and Big Data

Elastic announced its IPO on the NYSE under ticker ESTC, highlighting its origins, rapid growth to over 5000 customers worldwide, a $160 million FY2018 revenue, and its Elastic Stack suite that powers search and analytics across industries, while investors celebrated the stock surge.

Big DataElasticsearchIPO
0 likes · 6 min read
Elastic Search IPO: What It Means for Search and Big Data
Alibaba Cloud Developer
Alibaba Cloud Developer
Sep 30, 2018 · Artificial Intelligence

How Alibaba’s Search & Recommendation Evolved: From Rules to Cognitive AI

This article reviews the evolution of Alibaba’s e‑commerce search and recommendation technologies, detailing Taobao’s unique challenges, the shift from rule‑based retrieval to large‑scale machine learning, real‑time online learning, deep learning and intelligent decision‑making, and outlines future directions toward cognitive intelligence.

cognitive AIdeep learninge-commerce
0 likes · 16 min read
How Alibaba’s Search & Recommendation Evolved: From Rules to Cognitive AI
58 Tech
58 Tech
Aug 17, 2018 · Cloud Computing

Design and Architecture of 58 Cloud Search Platform Using Kubernetes and Docker

The article describes how 58's search technology team standardized and modularized their vertical search services into a cloud-native platform, detailing the overall architecture, Kubernetes‑based deployment, service and deployment designs, stateful indexing challenges, and solutions for high‑availability and scalability.

Cloud ComputingDockerIndexing
0 likes · 10 min read
Design and Architecture of 58 Cloud Search Platform Using Kubernetes and Docker
JD Retail Technology
JD Retail Technology
May 31, 2018 · Industry Insights

Inside JD.com’s Review & Share System: Architecture, Challenges, and Lessons

JD.com’s review and share platform combines multi‑dimensional rating, text, image and video content with a modular middleware, MySQL/MongoDB/HBase storage, Solr search, Redis caching and a management backend, detailing its architecture, daily operations, component‑based design, scalability challenges and future enhancements.

ComponentizationMiddlewarecaching
0 likes · 21 min read
Inside JD.com’s Review & Share System: Architecture, Challenges, and Lessons
Architecture Digest
Architecture Digest
May 27, 2018 · Big Data

Installing Elasticsearch and Performing Data Aggregation Queries

This article walks through installing Elasticsearch 5.6.9, configuring system limits, creating indices, inserting and deleting documents, executing complex aggregation queries, and integrating Elasticsearch with Java using the TransportClient, providing a practical guide for building analytics on large‑scale data.

Big DataElasticsearchanalytics
0 likes · 12 min read
Installing Elasticsearch and Performing Data Aggregation Queries
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 28, 2018 · Artificial Intelligence

How Alibaba Uses AI to Power the New Retail Ecosystem

Alibaba’s recent Search and Computing Open Day revealed how AI, big‑data algorithms and multi‑objective optimization are reshaping its e‑commerce ecosystem, boosting commercial efficiency, supporting diverse merchants, and driving innovative retail experiences for billions of users.

AIAlgorithmsAlibaba
0 likes · 18 min read
How Alibaba Uses AI to Power the New Retail Ecosystem
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 19, 2018 · Artificial Intelligence

How Alibaba’s Smart Dialogue Platform Turns Search into AI‑Powered Conversations

This article details Alibaba’s Shenma Search intelligent dialogue system, covering its content taxonomy, platform architecture, TaskBot/QABot/ChatBot engines, knowledge‑graph infrastructure, production pipelines, and performance metrics that enable AI‑driven information services across devices like Tmall Genie.

AI dialogueAlibabaKnowledge Graph
0 likes · 18 min read
How Alibaba’s Smart Dialogue Platform Turns Search into AI‑Powered Conversations
ITPUB
ITPUB
Mar 7, 2018 · Fundamentals

Mastering grep: 12 Practical Linux Search Techniques

This guide walks you through twelve essential grep use‑cases on Linux, from installing the tool and listing packages to filtering files, displaying line numbers, counting matches, recursive searches, exact‑word matches, and working with compressed or regex‑based searches, all illustrated with clear command examples.

RegexTutorialcommand-line
0 likes · 9 min read
Mastering grep: 12 Practical Linux Search Techniques
Architect's Tech Stack
Architect's Tech Stack
Jan 18, 2018 · Databases

SolrCloud Introduction and Spring Boot Example with Code

This article introduces SolrCloud, explains its relationship with Lucene and Solr, provides environment setup instructions for a CentOS 7.3 cluster, details Maven dependencies, configuration files, and a comprehensive Java implementation using Spring Boot, including repository interfaces, utility classes, and extensive unit tests for adding, querying, and deleting documents.

DistributedSearchLuceneSolrCloud
0 likes · 8 min read
SolrCloud Introduction and Spring Boot Example with Code
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 8, 2017 · Cloud Computing

How Alibaba’s ‘Ali Inside‑Out’ Uses Cloud‑Native Architecture for Collaboration

Alibaba’s internal collaboration platform, Ali Inside‑Out, evolved from a simple portal in 2013 to a cloud‑native, AI‑enhanced ecosystem that unifies search, feed, and global deployment, leveraging Alibaba’s tech stack—including Spring Boot, ISEARCH, NEO4J, and worldwide ADNS—to boost employee productivity and cultural engagement.

Alibabacloud-nativecollaboration
0 likes · 10 min read
How Alibaba’s ‘Ali Inside‑Out’ Uses Cloud‑Native Architecture for Collaboration
Baixing.com Technical Team
Baixing.com Technical Team
Sep 11, 2017 · Artificial Intelligence

How Do Search Engines Decode User Intent? Exploring Query Extension Techniques

This article explains how modern search engines identify precise and broad user intents, examines real‑world query examples, and details extension modules such as synonym, pinyin, and correction that enhance query understanding using algorithms like Aho‑Corasick, Hidden Markov Models, and Levenshtein distance.

Query ExpansionUser Intentinformation retrieval
0 likes · 10 min read
How Do Search Engines Decode User Intent? Exploring Query Extension Techniques
21CTO
21CTO
Aug 6, 2017 · Artificial Intelligence

How YouTube’s Recommendation Engine Evolved: From Graph Walks to Deep Neural Networks

This article reviews YouTube’s recommendation system research from 2008 to 2016, detailing four development stages—user‑video graph walks, video‑video graph walks, search‑based methods with collaborative filtering, and deep neural networks—highlighting key algorithms, system architectures, and experimental results.

YouTubedeep learningmachine learning
0 likes · 17 min read
How YouTube’s Recommendation Engine Evolved: From Graph Walks to Deep Neural Networks
21CTO
21CTO
Jun 23, 2017 · Backend Development

How to Build High‑Performance Search Queries with SQL and Redis

This article explores three progressive implementations for a complex e‑commerce search interface, comparing a monolithic SQL solution, an optimized multi‑query approach, and a Redis‑based caching strategy that leverages sets and sorted sets for fast, scalable results.

RedisSQLbackend
0 likes · 8 min read
How to Build High‑Performance Search Queries with SQL and Redis
Meituan Technology Team
Meituan Technology Team
Jun 16, 2017 · Artificial Intelligence

Evolution of Meituan Travel Search Recall Strategies

Meituan‑Dianping’s travel search team tackles cross‑region queries and noisy data by iteratively refining a four‑step, case‑driven pipeline that classifies intent, segments queries, ranks results with distance and term‑importance models, and employs multi‑stage, parallel recall to steadily boost purchase rate, CTR, and user satisfaction.

RankingTravelintent classification
0 likes · 20 min read
Evolution of Meituan Travel Search Recall Strategies
21CTO
21CTO
Apr 19, 2017 · Artificial Intelligence

How Alibaba Transformed E‑Commerce Search with Real‑Time AI and Reinforcement Learning

Alibaba’s e‑commerce search engine evolved over three years from offline batch models to a sophisticated AI-driven system that integrates real‑time feature ingestion, online learning, deep and reinforcement learning, enabling dynamic personalization and decision‑making that boosts conversion during high‑traffic events like Double 11.

AIReal-Time Computinge-commerce
0 likes · 15 min read
How Alibaba Transformed E‑Commerce Search with Real‑Time AI and Reinforcement Learning
High Availability Architecture
High Availability Architecture
Apr 14, 2017 · Databases

Recent Improvements in Elasticsearch 5.x and Outlook for 6.0

This article reviews the latest Elasticsearch 5.x enhancements—including append‑only indexing, range fields, removal of the _all field, unified highlighter, keyword normalizer, multi‑word synonyms, field collapsing, cancellable searches, partitioned term aggregations, cluster allocation explain, Java REST client updates, cross‑cluster search, batched reduce phases—and previews the major features expected in Elasticsearch 6.0 such as sparse doc values, index sorting, sequence numbers, seamless rolling upgrades, type removal, index‑template inheritance, load‑aware shard routing, and X‑Pack extensions like SQL and machine learning.

Cluster ManagementData ModelingElasticsearch
0 likes · 15 min read
Recent Improvements in Elasticsearch 5.x and Outlook for 6.0
ITPUB
ITPUB
Mar 24, 2017 · Fundamentals

Master Binary Search Trees: Definitions, Traversals, and Core Operations

Binary Search Trees (BST) are ordered binary trees that enable fast search, insertion, and deletion of nodes; this guide explains their definition, properties, traversal methods, and core operations—including search, minimum/maximum, successor/predecessor, insertion, and deletion—complete with pseudocode and illustrative examples.

binary search treedata-structuresinsertion-deletion
0 likes · 16 min read
Master Binary Search Trees: Definitions, Traversals, and Core Operations
ITPUB
ITPUB
Mar 24, 2017 · Fundamentals

Master Binary Search Trees: Definitions, Traversals, and Core Operations

Binary Search Trees (BST) are ordered binary trees that enable fast search, insertion, and deletion of nodes; this guide explains their definition, key properties, traversal methods, and core algorithms—including search, minimum/maximum, successor/predecessor, insertion, and deletion—with pseudocode and illustrative examples.

DeletionInsertionbinary search tree
0 likes · 16 min read
Master Binary Search Trees: Definitions, Traversals, and Core Operations
ITPUB
ITPUB
Mar 22, 2017 · Backend Development

What Makes Taobao’s Massive Scale Demand Hundreds of Elite Engineers?

The article explains how a high‑traffic e‑commerce platform like Taobao relies on distributed storage, search engines, massive caching, load‑balancing, CDN, sophisticated advertising and analytics systems, all of which require large teams of top engineers to design, implement, and operate.

backendcachingdistributed systems
0 likes · 12 min read
What Makes Taobao’s Massive Scale Demand Hundreds of Elite Engineers?
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 7, 2016 · Artificial Intelligence

How Online AI Transforms Search and Recommendation Systems

At Alibaba's 2016 Double 11 Tech Forum, researcher Xu Yinghui presented how online AI technologies enhance search and recommendation on the e‑commerce platform, turning massive user behavior data into actionable insights that improve traffic allocation and maximize welfare for consumers, sellers, and the platform.

AIAlibabae-commerce
0 likes · 2 min read
How Online AI Transforms Search and Recommendation Systems
Qunar Tech Salon
Qunar Tech Salon
Mar 23, 2016 · Operations

Using grep with Regular Expressions on Linux and Unix Systems

This guide explains how to use the GNU grep tool on Linux and Unix to perform powerful text searches with basic and extended regular expressions, covering pattern matching, character classes, wildcards, logical operators, quantifiers, output formatting, and differences between grep and egrep.

LinuxRegexgrep
0 likes · 10 min read
Using grep with Regular Expressions on Linux and Unix Systems
Qunar Tech Salon
Qunar Tech Salon
Feb 24, 2016 · Artificial Intelligence

Overview and Architecture of Pora: A Real‑Time Personalization Analytics Platform

The article introduces Pora, a real‑time offline‑realtime analytics system for personalized search that combines high‑throughput stream processing, low‑latency computation, online learning algorithms, and a modular architecture to support continuous 24/7 operation and large‑scale performance optimizations.

AIReal-Time AnalyticsStream Processing
0 likes · 6 min read
Overview and Architecture of Pora: A Real‑Time Personalization Analytics Platform
ITPUB
ITPUB
Feb 23, 2016 · Fundamentals

Master 10 Essential Algorithms: From QuickSort to Naive Bayes

This guide introduces ten core algorithms—including QuickSort, HeapSort, MergeSort, Binary Search, BFPRT, DFS, BFS, Dijkstra, Dynamic Programming, and Naive Bayes—explaining their principles, step‑by‑step procedures, and typical use cases for efficient problem solving.

AlgorithmsGraphNaive Bayes
0 likes · 14 min read
Master 10 Essential Algorithms: From QuickSort to Naive Bayes
Efficient Ops
Efficient Ops
Dec 7, 2015 · Backend Development

Mastering the ELK Stack: From Lucene Indexing to ElasticSearch Queries

This article walks through the fundamentals of search engine architecture, explains Lucene's role as an indexing library, details ElasticSearch's distributed design, clustering, sharding, and plugins, and demonstrates practical RESTful API usage and query DSL techniques for effective log analysis.

IndexingLucenebackend
0 likes · 23 min read
Mastering the ELK Stack: From Lucene Indexing to ElasticSearch Queries
Ctrip Technology
Ctrip Technology
Nov 4, 2015 · Cloud Computing

Ctrip’s Technological Evolution: Infrastructure, Cloud, Search, Security, and Mobile Innovations

The article reviews Ctrip’s multi‑year technology journey, detailing its shift to distributed architecture, OpenStack‑based private cloud, custom asynchronous messaging, large‑scale search, security analytics, and mobile innovations, illustrating how strategic technical choices supported its dominance in online travel.

CtripDistributed Architecturemobile
0 likes · 7 min read
Ctrip’s Technological Evolution: Infrastructure, Cloud, Search, Security, and Mobile Innovations
Ctrip Technology
Ctrip Technology
Oct 30, 2015 · Backend Development

Highlights from the 4th ESCC Domestic Developer Conference in Shanghai

The fourth ESCC domestic developer conference held at Ctrip's headquarters in Shanghai gathered around 100 engineers to share ElasticSearch product roadmaps, core search system experiences, Kibana 4 features, and best practices for building high‑throughput ELK clusters.

ELKbackend developmentconference
0 likes · 2 min read
Highlights from the 4th ESCC Domestic Developer Conference in Shanghai
ITPUB
ITPUB
Aug 12, 2015 · Operations

Master Splunk: Install, Configure, and Search Logs on Linux and Windows

This guide walks you through installing Splunk on Linux or Windows, configuring automatic startup, indexing diverse log sources, and using Splunk’s powerful search, Boolean operators, and timeline features to troubleshoot and analyze system and network logs efficiently.

InstallationOperationsSplunk
0 likes · 15 min read
Master Splunk: Install, Configure, and Search Logs on Linux and Windows
Architect
Architect
Jul 27, 2015 · Backend Development

Design and Architecture of Specialized Search Services

The article explains the concept of specialized search, its service model, and detailed backend architecture considerations such as interface standards, traffic distribution, service invocation, and component reuse, illustrated with protobuf definitions and deployment diagrams.

Protobufbackendsearch
0 likes · 8 min read
Design and Architecture of Specialized Search Services
Qunar Tech Salon
Qunar Tech Salon
Apr 6, 2015 · Fundamentals

Branch and Bound Method vs Backtracking: Basic Description and Comparison

The article explains the branch and bound algorithm, comparing it with backtracking, describing its search strategies, general procedure, and key differences such as search order, node handling, and optimal solution finding, while providing a basic overview and illustrative diagram.

AlgorithmOptimizationbacktracking
0 likes · 6 min read
Branch and Bound Method vs Backtracking: Basic Description and Comparison
Qunar Tech Salon
Qunar Tech Salon
Mar 27, 2015 · Fundamentals

Classic Algorithms that Shaped Modern Computing

This article surveys a collection of seminal algorithms—including Huffman coding, public‑key encryption, Dijkstra's shortest‑path, binary search, quicksort, Karatsuba multiplication, Euclid's GCD, Bresenham's line drawing, and the fast inverse square‑root—explaining their origins, principles, and lasting impact on computer science.

Algorithmscomputer graphicscryptography
0 likes · 7 min read
Classic Algorithms that Shaped Modern Computing