Home › Entities › academia › BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification

BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification

Research article (Arabian Journal for Science and Engineering, 2021) · cited 29× · AI/ML
academia openalex:W3130398963
Press Enter · cited answer in seconds

BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification

Summary

BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification is a scholarly article[1].

Key Facts

  • BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

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.

APA 4ort.xyz Knowledge Graph. (2026). BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification. Retrieved May 24, 2026, from https://4ort.xyz/entity/blstm-api-bi-lstm-recurrent-neural-network-based-approach-for-arabic-paraphrase-identification
MLA “BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/blstm-api-bi-lstm-recurrent-neural-network-based-approach-for-arabic-paraphrase-identification.
BibTeX @misc{4ortxyz_blstm-api-bi-lstm-recurrent-neural-network-based-approach-for-arabic-paraphrase-identification_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification}}, year = {2026}, url = {https://4ort.xyz/entity/blstm-api-bi-lstm-recurrent-neural-network-based-approach-for-arabic-paraphrase-identification}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification — https://4ort.xyz/entity/blstm-api-bi-lstm-recurrent-neural-network-based-approach-for-arabic-paraphrase-identification (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/blstm-api-bi-lstm-recurrent-neural-network-based-approach-for-arabic-paraphrase-identification · Last refreshed: