Enhancing Startup Resource Discovery- A Machine Learning Approach with Vector Embeddings

10 pages•Published: August 6, 2024

Varun Kumar V, Ruthvik S and Jinu Sophia J

Abstract

AI has emerged as a transformative force for startups across various industries. It offers automation, data-driven decision-making, personalization, and predictive analytics, enabling startups to improve efficiency, gain a competitive advantage, and scale their operations. The startup resource dashboard application uses Machine learning to scrape data from a variety of sources, such as government websites, industry publications, and social media. The application extends beyond simple data gathering by incorporating machine learning to craft an advanced matching algorithm. It uses Large Language Models trained exclusively on data relevant to the current economic information and other data that helps the startups to take data driven decision. Furthermore, vector embeddings are employed to enhance the context and relevance of the generated responses. Encoding the words and phrases in the High-dimensional vectors, the model gains a better undersign of the startup eco-system facilitating more accurate and insightful recommendations. By bridging the gap between Advanced AI technologies and specific needs of startups, this methodology improves the innovation and success within the startup environment.

Keyphrases: artificial intelligence, incubator, investment, investors, machine learning, natural language processing, startups

In: Rajakumar G (editor). Proceedings of 6th International Conference on Smart Systems and Inventive Technology, vol 19, pages 134-143.

Links:	https://easychair.org/publications/paper/1gml
	https://doi.org/10.29007/z9lp

BibTeX entry

@inproceedings{ICSSIT2024:Enhancing_Startup_Resource_Discovery,
  author    = {Varun Kumar V and Ruthvik S and Jinu Sophia J},
  title     = {Enhancing Startup Resource Discovery- A Machine Learning Approach with Vector Embeddings},
  booktitle = {Proceedings of 6th International Conference on Smart Systems and Inventive Technology},
  editor    = {Rajakumar G},
  series    = {Kalpa Publications in Computing},
  volume    = {19},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/1gml},
  doi       = {10.29007/z9lp},
  pages     = {134-143},
  year      = {2024}}

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