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Information Retrieval

113 articles · Page 2 of 2
DataFunTalk
DataFunTalk
Jul 30, 2018 · Artificial Intelligence

Enhancing Automated Process Services with Multi‑Turn Dialogue: Insights from Chatopera’s NLP Solutions

The article presents a technical overview of Chatopera’s multi‑turn dialogue platform, covering language model fundamentals, Chinese segmentation, word embeddings, information retrieval, and open‑source tools, while illustrating how these AI techniques enable low‑cost, scalable enterprise chatbot solutions.

Information RetrievalNLPmulti-turn dialogue
0 likes · 11 min read
Enhancing Automated Process Services with Multi‑Turn Dialogue: Insights from Chatopera’s NLP Solutions
IT Xianyu
IT Xianyu
Apr 17, 2018 · Fundamentals

The Origins of Internet Search: Archie and WAIS

Archie, created in 1989 by Peter Deutsch at McGill University, was the first internet search tool that indexed FTP sites, while WAIS, developed by Brewster Kahle at Thinking Machines, extended searchable databases worldwide, both highlighting early challenges in managing large communication traffic and user-friendly interfaces.

ArchieInformation RetrievalInternet History
0 likes · 3 min read
The Origins of Internet Search: Archie and WAIS
Architecture Digest
Architecture Digest
Feb 1, 2018 · Fundamentals

How Search Engines Work: Building Inverted Indexes

This article explains the core of search engine technology by describing what an inverted index is, how it is built using single‑pass memory and multi‑way merge methods, how indexes can be partitioned and incrementally updated, and how Hadoop can be used for large‑scale indexing.

HadoopIndexingInformation Retrieval
0 likes · 10 min read
How Search Engines Work: Building Inverted Indexes
21CTO
21CTO
Oct 12, 2017 · Artificial Intelligence

How Advanced Autocomplete Algorithms Boost Search Experience

This article explains the principles, algorithms, and practical challenges of search autocomplete (query suggestion), covering popularity‑based models, time‑sensitive methods, user‑aware and context‑aware approaches, data pipelines, indexing, ranking, personalization, and evaluation techniques used in e‑commerce search systems.

Information Retrievalautocompletee‑commerce
0 likes · 15 min read
How Advanced Autocomplete Algorithms Boost Search Experience
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.

Information RetrievalNatural Language ProcessingQuery Expansion
0 likes · 10 min read
How Do Search Engines Decode User Intent? Exploring Query Extension Techniques
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 7, 2017 · Artificial Intelligence

Probabilistic Pair Recommendations & IRGAN: Boosting E‑commerce Click‑Through

This article summarizes two SIGIR 2017 papers: one introduces a probabilistic latent‑class model for shopping‑pair push recommendations that improves e‑commerce click‑through rates by leveraging co‑purchase and view‑then‑purchase graphs, and the other presents IRGAN, a GAN‑based framework that unifies generative and discriminative information‑retrieval models, achieving state‑of‑the‑art results across web search, recommendation, and QA tasks.

GaNInformation Retrievale-commerce
0 likes · 9 min read
Probabilistic Pair Recommendations & IRGAN: Boosting E‑commerce Click‑Through
Alibaba Cloud Developer
Alibaba Cloud Developer
May 20, 2017 · Artificial Intelligence

How Alibaba’s AI‑Driven Information Retrieval Is Shaping E‑Commerce Futures

The second “Frontiers and Future of Information Retrieval” forum, co‑hosted by the Chinese Computer Society, Alibaba and academic committees, showcased how massive, structured e‑commerce data and AI algorithms are revolutionizing search, customer service, and research collaborations across the industry.

AlibabaInformation Retrievalbig data
0 likes · 4 min read
How Alibaba’s AI‑Driven Information Retrieval Is Shaping E‑Commerce Futures
21CTO
21CTO
Feb 15, 2017 · Fundamentals

How Twitter Evolved Its Search Engine: From MySQL to Earlybird and Beyond

This article explains the fundamentals of search engine architecture, covering text collection, indexing, ranking and evaluation, and then traces Twitter's internal search evolution from MySQL full‑text search to the Earlybird index server, Blender aggregation, and smart memory‑SSD strategies.

IndexingInformation RetrievalTwitter
0 likes · 8 min read
How Twitter Evolved Its Search Engine: From MySQL to Earlybird and Beyond
Architect
Architect
Feb 3, 2016 · Fundamentals

The Mathematics Behind Google’s PageRank Algorithm

This article explains how Google’s PageRank algorithm uses the web’s link structure, Markov processes, and stochastic matrix adjustments—including damping factor α—to overcome ranking challenges and provide a mathematically sound method for ordering search results.

GoogleInformation RetrievalMarkov chain
0 likes · 21 min read
The Mathematics Behind Google’s PageRank Algorithm
Architect
Architect
Nov 15, 2015 · Big Data

An Introduction to Search Engine Architecture and Core Technologies

This article provides a comprehensive overview of search engine fundamentals—including inverted indexing, tokenization, ranking, high‑concurrency infrastructure, caching, crawling strategies, query understanding, keyword rewriting, personalization, and knowledge‑base construction—highlighting the technical challenges that make modern search engines like Google superior to simpler implementations.

Information Retrievalcrawlingranking
0 likes · 14 min read
An Introduction to Search Engine Architecture and Core Technologies
Qunar Tech Salon
Qunar Tech Salon
Oct 10, 2015 · Fundamentals

Overview of Search Engine Architecture and Core Technologies

This article provides a comprehensive overview of search engine evolution, core technologies such as crawling, indexing, retrieval and link analysis, platform foundations including cloud storage and computing, and techniques for improving search results through anti‑spam, user‑intent analysis, deduplication and caching.

Cloud ComputingIndexingInformation Retrieval
0 likes · 15 min read
Overview of Search Engine Architecture and Core Technologies