Home ›
Entities
› academia
› Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models
Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models
Research article (International Journal of Information Technology, 2023) · cited 13× · AI/ML
Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models
Summary
Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models is a scholarly article[1].
Key Facts
Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models. Retrieved May 24, 2026, from https://4ort.xyz/entity/enhancing-sentiment-analysis-in-hindi-for-e-commerce-companies-a-cnn-lstm-approach-with-cbow-and-tf-idf-word-embedding-m
MLA“Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/enhancing-sentiment-analysis-in-hindi-for-e-commerce-companies-a-cnn-lstm-approach-with-cbow-and-tf-idf-word-embedding-m.
BibTeX@misc{4ortxyz_enhancing-sentiment-analysis-in-hindi-for-e-commerce-companies-a-cnn-lstm-approach-with-cbow-and-tf-idf-word-embedding-m_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models}}, year = {2026}, url = {https://4ort.xyz/entity/enhancing-sentiment-analysis-in-hindi-for-e-commerce-companies-a-cnn-lstm-approach-with-cbow-and-tf-idf-word-embedding-m}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Enhancing sentiment analysis in Hindi for E-commerce companies: a CNN-LSTM approach with CBoW and TF-IDF word embedding models — https://4ort.xyz/entity/enhancing-sentiment-analysis-in-hindi-for-e-commerce-companies-a-cnn-lstm-approach-with-cbow-and-tf-idf-word-embedding-m (retrieved 2026-05-24)
