Results 121 to 130 of about 8,324 (219)

Market Reactions to Old Innovation News: Evidence From Patent Disclosures in China

International Review of Finance, Volume 26, Issue 2, June 2026.
ABSTRACT This paper examines how investors' past inattention affects market reactions to corporate innovation announcements, leveraging a unique setting in China where many publicly listed firms voluntarily disclose patent grants—information already public via the Patent Gazette.
Junbiao Yu, Ji‐Chai Lin, Feng Tian
wiley   +1 more source

A hybrid model integrating RoBERTa, TF-IDF, and attention mechanism for medical query intent classification. [PDF]

Sci Rep
Liang Z, Zhao Y, Xu H, Huang H, Chen L.
europepmc   +1 more source

Features extraction based on Naive Bayes algorithm and TF-IDF for news classification. [PDF]

PLoS One
Zhang L.
europepmc   +1 more source

Single cell RNA-seq data clustering using TF-IDF based methods. [PDF]

BMC Genomics, 2018
Moussa M, Măndoiu II.
europepmc   +1 more source

The Method dynavic TF-IDF

International Journal of Emerging Trends in Engineering Research, 2020
openaire   +1 more source

Transforming aged care in China: insights from a TF-IDF-based data mining analysis of national policies (2018-2022). [PDF]

BMC Geriatr
Liu Z, Li H, Zhang Z, Ping L, Gu W, Yao Y.   +5 more
europepmc   +1 more source

Spam Detection With Naïve Bayes And TF-IDF

This paper, titled "Spam Detection With Naïve Bayes And TF-IDF," explores an approach to detecting spam emails by applying Natural Language Processing (NLP) techniques combined with machine learning methods. The study used a balanced dataset of 2,000 emails (1,000 spam and 1,000 non-spam) collected from Kaggle.
Oruc, Reyyan, Senyurek, Edip
openaire   +2 more sources

Emotion-Aware RoBERTa enhanced with emotion-specific attention and TF-IDF gating for fine-grained emotion recognition. [PDF]

Sci Rep
Alqarni F, Sagheer A, Alabbad A, Hamdoun H.   +3 more
europepmc   +1 more source

Text classification algorithm of tourist attractions subcategories with modified TF-IDF and Word2Vec. [PDF]

PLoS One
Xiao L, Li Q, Ma Q, Shen J, Yang Y, Li D.   +5 more
europepmc   +1 more source

Investigating response behavior through TF-IDF and Word2vec text analysis: A case study of PISA 2012 problem-solving process data. [PDF]

Heliyon
Zhou J, Ye Z, Zhang S, Geng Z, Han N, Yang T.   +5 more
europepmc   +1 more source