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Bilibili Tech
Bilibili Tech
Feb 18, 2024 · Artificial Intelligence

Bilibili Personal Attack Content Governance: Background, Goals, Methods, and Effectiveness

Bilibili combats personal‑attack and trolling comments by combining sector‑specific keyword databases, user‑group analysis, advanced word‑matching (including pinyin and homophone detection) and multiple NLP/graph models, which has cut personal‑attack reports in entertainment, film and gaming by about 32 % and trolling reports by roughly 25 % between June and December 2023.

BilibiliNatural Language ProcessingText Classification
0 likes · 12 min read
Bilibili Personal Attack Content Governance: Background, Goals, Methods, and Effectiveness
Sohu Tech Products
Sohu Tech Products
Sep 6, 2023 · Mobile Development

Building an iOS SMS Spam Filter App with CoreML

This tutorial walks through creating a custom iOS SMS spam filter app, covering extraction of personal SMS data from an iPhone backup, training a CoreML text‑classification model with CreateML, implementing a Message Filter Extension in Xcode, and exploring advanced update strategies.

App ExtensionCoreMLSMS filtering
0 likes · 12 min read
Building an iOS SMS Spam Filter App with CoreML
Sohu Tech Products
Sohu Tech Products
Jun 7, 2023 · Artificial Intelligence

Multiscale PU Learning for Detecting AI‑Generated Text

Researchers from Peking University and Huawei present a multiscale positive‑unlabeled learning framework that significantly improves detection of AI‑generated short and long texts, addressing the difficulty of distinguishing AI‑written content from human writing and outperforming existing baselines on multiple benchmarks.

AI detectionPu-LearningText Classification
0 likes · 8 min read
Multiscale PU Learning for Detecting AI‑Generated Text
Bitu Technology
Bitu Technology
Jul 8, 2022 · Artificial Intelligence

Applying NLP and Machine Learning to Classify Tubi User Feedback

This article explains how Tubi leverages natural‑language processing, sentence embeddings (USE and BERT), and LightGBM models to automatically categorize large volumes of Net Promoter Score comments and customer‑support tickets, enabling data‑driven product decisions and workflow automation.

EmbeddingsLightGBMNLP
0 likes · 11 min read
Applying NLP and Machine Learning to Classify Tubi User Feedback
DataFunSummit
DataFunSummit
Jun 11, 2022 · Artificial Intelligence

Transforming Regular Expressions into Neural Networks for Text Classification and Slot Filling

This article explains how regular expressions can be converted into equivalent neural network models—FA‑RNN for classification and FST‑RNN for slot filling—by leveraging finite‑state automata, tensor decomposition, and pretrained word embeddings, achieving zero‑shot performance and strong results in low‑resource scenarios.

FA-RNNText Classificationneural networks
0 likes · 17 min read
Transforming Regular Expressions into Neural Networks for Text Classification and Slot Filling
DataFunTalk
DataFunTalk
Mar 17, 2022 · Artificial Intelligence

A Survey of Text Classification and Intent Recognition: Industrial and Research Perspectives

This article reviews recent developments in text classification and intent recognition, comparing industrial practices such as business‑coupled feature engineering with research trends like pretrained language models, and provides references and practical insights for building effective NLP solutions.

NLPText Classificationindustry applications
0 likes · 13 min read
A Survey of Text Classification and Intent Recognition: Industrial and Research Perspectives
IEG Growth Platform Technology Team
IEG Growth Platform Technology Team
Feb 14, 2022 · Artificial Intelligence

Multimodal Evolution and Application in Tencent Game Advertising System

This article describes the end‑to‑end multimodal modeling pipeline—covering text, image, and video understanding, model evolution from shallow to deep networks, key‑frame extraction, fine‑tuning, and multimodal fusion—used in Tencent's game ad exchange platform, along with practical deployment challenges and solutions.

CNNText ClassificationTransformer
0 likes · 22 min read
Multimodal Evolution and Application in Tencent Game Advertising System
DataFunSummit
DataFunSummit
Jan 16, 2022 · Artificial Intelligence

Multimodal Text and Speech Emotion Analysis: Overview, MSCNN‑SPU Model, and Domain Adaptation

This talk presents an overview of text‑plus‑speech multimodal emotion analysis, covering background, single‑modal text and audio models, the MSCNN‑SPU multimodal architecture, domain‑adaptation techniques, and future directions, with detailed model explanations, experimental results, and practical deployment insights.

Audio ProcessingSpeech RecognitionText Classification
0 likes · 40 min read
Multimodal Text and Speech Emotion Analysis: Overview, MSCNN‑SPU Model, and Domain Adaptation
ByteDance Terminal Technology
ByteDance Terminal Technology
Jan 7, 2022 · Information Security

Graph-Based Detection of Malicious Webpages: Methods, Experiments, and Future Directions

This article presents a comprehensive study on detecting malicious webpages by constructing heterogeneous graphs from URL redirection and textual features, applying Graph Convolutional Networks and Cluster‑Text‑GCN models, detailing optimization techniques for large‑scale deployment, and outlining future research directions.

GCNGraph Neural NetworksInformation Security
0 likes · 11 min read
Graph-Based Detection of Malicious Webpages: Methods, Experiments, and Future Directions
DataFunTalk
DataFunTalk
Aug 14, 2021 · Artificial Intelligence

Multimodal Advertisement Detection System for WeChat "KanKan" Articles

This article introduces a multimodal advertisement detection framework for WeChat KanKan that decomposes the problem into text, image, and article‑structure dimensions, presents novel models for ad text and image recognition, and describes how sequence classification and visualisation are used to filter severe ad‑spam articles.

Text ClassificationWeChatadvertisement detection
0 likes · 16 min read
Multimodal Advertisement Detection System for WeChat "KanKan" Articles
58 Tech
58 Tech
Aug 10, 2021 · Artificial Intelligence

Active Learning and Model Enhancements for Semantic Tag Mining in 58.com Voice Data

This article presents a comprehensive study on extracting semantic tags from 58.com voice data, detailing the use of active learning to address cold‑start problems, comparing keyword matching, XGBoost, TextCNN, CRNN, and an improved Wide&Deep model, and demonstrating significant reductions in labeling effort and superior F1 scores across multiple experiments.

CRNNText Classificationactive learning
0 likes · 15 min read
Active Learning and Model Enhancements for Semantic Tag Mining in 58.com Voice Data
Ctrip Technology
Ctrip Technology
Jul 29, 2021 · Artificial Intelligence

NLP Techniques for Classifying Ctrip Ticket Customer Service Conversations

This article presents the background, problem analysis, data preprocessing, modeling approaches and optimization results of applying various NLP methods—including statistical models, word embeddings, attention mechanisms and pretrained language models such as BERT—to improve the accuracy of classifying Ctrip ticket customer service dialogues.

BERTNLPText Classification
0 likes · 13 min read
NLP Techniques for Classifying Ctrip Ticket Customer Service Conversations
NetEase Media Technology Team
NetEase Media Technology Team
Apr 13, 2021 · Artificial Intelligence

Applying BERT for News Timeliness Classification at NetEase

The article describes how NetEase adapts a pre‑trained BERT model to classify news articles into ultra‑short, short, or long timeliness categories by combining rule‑based strong and weak time cues, key‑sentence extraction, domain‑embedding fusion and multi‑layer semantic aggregation, achieving accurate and interpretable predictions for its platform.

Artificial IntelligenceBERTModel Fusion
0 likes · 12 min read
Applying BERT for News Timeliness Classification at NetEase
58 Tech
58 Tech
Mar 1, 2021 · Artificial Intelligence

Intelligent QABot for 58.com: Classification and Retrieval Model Exploration

This article describes how 58.com’s AI Lab built and continuously improved the QABot intelligent customer‑service system by designing classification and retrieval models, evaluating FastText, LSTM‑DSSM, BERT and a self‑developed SPTM framework, and finally fusing them to boost answer rates and user experience.

AI chatbotBERTModel Fusion
0 likes · 9 min read
Intelligent QABot for 58.com: Classification and Retrieval Model Exploration
58 Tech
58 Tech
Jan 27, 2021 · Artificial Intelligence

Model Iteration and Architecture of the BangBang Intelligent Customer Service QABot

This article details the BangBang intelligent customer service system's overall architecture, core capabilities, knowledge‑base construction, and successive model upgrades—from FastText to TextCNN, Bi‑LSTM, and model fusion—showing how each iteration improved accuracy, recall, and F1 scores toward a stable 95% performance level.

AILSTMModel Fusion
0 likes · 12 min read
Model Iteration and Architecture of the BangBang Intelligent Customer Service QABot
58 Tech
58 Tech
Jan 15, 2021 · Artificial Intelligence

Exploring Text Pre‑training Models for Dialogue Classification in Information Security: From TextCNN to RoBERTa and Knowledge Distillation

This article presents a systematic exploration of text pre‑training models for dialogue classification in information‑security scenarios, comparing baseline TextCNN, an enhanced TextCNN_role, RoBERTa with domain‑adaptive pre‑training, and a distilled mini‑model, and discusses their performance, trade‑offs, and future directions.

Dialog ModelingInformation SecurityNLP
0 likes · 13 min read
Exploring Text Pre‑training Models for Dialogue Classification in Information Security: From TextCNN to RoBERTa and Knowledge Distillation
58 Tech
58 Tech
Sep 21, 2020 · Artificial Intelligence

58.com AI Algorithm Competition: Winning Teams and Their Technical Solutions

The 58.com AI Algorithm Competition showcased intelligent customer‑service technology, with 158 teams competing on text classification and matching tasks, and the top five teams presenting detailed BERT, ELECTRA, focal‑loss and multi‑model fusion solutions along with award ceremonies, video recordings and PPT resources.

AIBERTELECTRA
0 likes · 9 min read
58.com AI Algorithm Competition: Winning Teams and Their Technical Solutions
58 Tech
58 Tech
Aug 14, 2020 · Artificial Intelligence

Using SPTM in qa_match for the 58 City AI Competition: Data Preparation, Model Training, and Prediction

This article provides a step‑by‑step guide on preparing data, pre‑training the SPTM lightweight model, fine‑tuning a text‑classification model with qa_match, and generating competition‑ready predictions for the 58 City AI Algorithm Contest, including all required shell commands and parameter explanations.

AIPretrainingSPTM
0 likes · 9 min read
Using SPTM in qa_match for the 58 City AI Competition: Data Preparation, Model Training, and Prediction
58 Tech
58 Tech
Aug 12, 2020 · Artificial Intelligence

Guide to Using SPTM (Simple Pre-trained Model) with qa_match for an AI Competition

This article provides a step‑by‑step tutorial on preparing data, pre‑training the SPTM language model, fine‑tuning a text‑classification model, generating predictions, and creating a submission file for the 58.com AI algorithm competition using the open‑source qa_match toolkit.

AINLPSPTM
0 likes · 9 min read
Guide to Using SPTM (Simple Pre-trained Model) with qa_match for an AI Competition