Agribot: agriculture-specific question answer system
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866918150375735296 |
|---|---|
| author | Jain, Naman Jain, Pranjali Kayal, Pratik Sahit, Jayakrishna Pachpande, Soham Choudhari, Jayesh Singh, Mayank |
| author_facet | Jain, Naman Jain, Pranjali Kayal, Pratik Sahit, Jayakrishna Pachpande, Soham Choudhari, Jayesh Singh, Mayank |
| contents | India is an agro-based economy and proper information about agricultural practices is the key to optimal agricultural growth and output. In order to answer the queries of the farmer, we have build an agricultural chatbot based on the dataset from Kisan Call Center. This system is robust enough to answer queries related to weather, market rates, plant protection and government schemes. This system is available 24* 7, can be accessed through any electronic device and the information is delivered with the ease of understanding. The system is based on a sentence embedding model which gives an accuracy of 56%. After eliminating synonyms and incorporating entity extraction, the accuracy jumps to 86%. With such a system, farmers can progress towards easier information about farming related practices and hence a better agricultural output. The job of the Call Center workforce would be made easier and the hard work of various such workers can be redirected to a better goal. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_21535 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Agribot: agriculture-specific question answer system Jain, Naman Jain, Pranjali Kayal, Pratik Sahit, Jayakrishna Pachpande, Soham Choudhari, Jayesh Singh, Mayank Computation and Language Artificial Intelligence Machine Learning India is an agro-based economy and proper information about agricultural practices is the key to optimal agricultural growth and output. In order to answer the queries of the farmer, we have build an agricultural chatbot based on the dataset from Kisan Call Center. This system is robust enough to answer queries related to weather, market rates, plant protection and government schemes. This system is available 24* 7, can be accessed through any electronic device and the information is delivered with the ease of understanding. The system is based on a sentence embedding model which gives an accuracy of 56%. After eliminating synonyms and incorporating entity extraction, the accuracy jumps to 86%. With such a system, farmers can progress towards easier information about farming related practices and hence a better agricultural output. The job of the Call Center workforce would be made easier and the hard work of various such workers can be redirected to a better goal. |
| title | Agribot: agriculture-specific question answer system |
| topic | Computation and Language Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2509.21535 |