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DataFunTalk
DataFunTalk
Oct 13, 2021 · Artificial Intelligence

Intelligent Recruitment: Deep Semantic Matching, Interview Assistance, and Text Representation

This article explores how AI techniques such as deep semantic matching, attention mechanisms, variational autoencoders, and neural topic models can transform traditional recruitment by improving person‑job matching, interview assistance, and text representation, supported by experiments on real‑world hiring data.

AI recruitmentTopic ModelingVAE
0 likes · 18 min read
Intelligent Recruitment: Deep Semantic Matching, Interview Assistance, and Text Representation
DataFunTalk
DataFunTalk
May 25, 2020 · Artificial Intelligence

NLP Techniques for Financial Investment Analysis: Case Studies from Two Sigma, BlackRock, UC Berkeley and Others

This article reviews how natural language processing is used in financial investment analysis, summarizing case studies from Two Sigma, BlackRock, UC Berkeley and other institutions that apply topic modeling, event extraction and sentiment analysis to improve portfolio performance and achieve excess returns.

Event ExtractionInvestment AnalysisNLP
0 likes · 17 min read
NLP Techniques for Financial Investment Analysis: Case Studies from Two Sigma, BlackRock, UC Berkeley and Others
Meitu Technology
Meitu Technology
Jul 17, 2018 · Artificial Intelligence

Video Clustering Techniques for Personalized Recommendation in Meipai

Meipai’s personalized recommendation system leverages massive user‑behavior data to build behavior‑driven video clusters—evolving from TopicModel through Item2vec and Keyword Propagation to a DSSM deep model—boosting ranking AUC, enhancing UI diversity, similar‑video search, niche discovery, and feature engineering.

DSSMTopic Modelingitem2vec
0 likes · 22 min read
Video Clustering Techniques for Personalized Recommendation in Meipai