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DataFunSummit
DataFunSummit
Dec 23, 2021 · Artificial Intelligence

User Clustering Techniques in Tencent KanDian: From Traditional Algorithms to N‑gram and action2vec

This article explains how Tencent KanDian analyzes user behavior by introducing the product, describing common clustering scenarios, reviewing traditional unsupervised methods, and detailing advanced path‑based approaches such as N‑gram and action2vec, while discussing their advantages, limitations, and practical applications.

AIN-gramTencent
0 likes · 12 min read
User Clustering Techniques in Tencent KanDian: From Traditional Algorithms to N‑gram and action2vec
DataFunTalk
DataFunTalk
Nov 8, 2021 · Artificial Intelligence

User Behavior Clustering in Tencent Kankan: From Traditional Unsupervised Methods to N‑gram and action2vec

This article introduces Tencent Kankan's product landscape and explores various user clustering techniques—including classic unsupervised algorithms, N‑gram based sequence clustering, and deep‑learning driven action2vec—detailing their implementation steps, advantages, limitations, and practical insights for product optimization.

N-gramTencentaction2vec
0 likes · 12 min read
User Behavior Clustering in Tencent Kankan: From Traditional Unsupervised Methods to N‑gram and action2vec
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Nov 1, 2019 · Artificial Intelligence

Improving International Hotel Room‑Type Merging with Text Similarity and Machine‑Learning Models

This article describes how a large‑scale international hotel platform reduced room‑type merging errors and user complaints by applying rule‑based methods, text‑similarity algorithms (Jaccard, LCS, N‑Gram) and supervised machine‑learning classifiers such as fastText to standardize and merge heterogeneous room‑type data.

N-gramfastTexthotel
0 likes · 9 min read
Improving International Hotel Room‑Type Merging with Text Similarity and Machine‑Learning Models