Academic abstracts classification with Large Language Model
Transforming Research Publication Success with Cutting-Edge AI
Python Hugging Face Transformers FAISS Vector DB Fast API
An API based on pre-trained GPT model
Engagement model
Technology Partner
Academic publishing
AI Architects 1
Engineers 2
DevOps 1
Company name
Begell House inc.
Business activity
Academic Publishing

Academic abstracts classification with Large Language Model

Begell House, a prominent academic publisher renowned for its peer-reviewed journals and scientific publications, faces the challenge of efficiently classifying numerous incoming articles. With 50 existing journals to choose from, selecting the right publication venue becomes time-consuming and intricate. To streamline this process, we undertook the Academic Abstracts Classification project, creating an AI-powered solution called the Large Language Model (LLM).

Case highlights

Large Language Model
Streamlined Journal Recommendation
Personalized Research Guidance


Our valued client, a leading academic institution, sought to improve the efficiency of research discovery and classification. With a vast repository of academic abstracts covering diverse topics, manually categorizing and classifying these abstracts was time-consuming and resource-intensive.


To revolutionize the abstracts classification process, our software development team implemented a state-of-the-art Large Language Model (LLM) solution. Leveraging the power of cutting-edge natural language processing (NLP) algorithms, our LLM is trained to comprehend the nuances and context of academic abstracts, enabling accurate and efficient classification.
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