Research Area: Machine Learning
Semantic analysis is a particular technique, which is an interesting area of research that associates with Natural Language Processing (NLP), artificial intelligence, opinion mining, text clustering, and classification. Numerous text processing techniques are being used to find out sentiments from the comments, such as social media tweets, hoax, fiction, nonfiction, novels, books, movies, health care, and stock exchange. Agrarian experts’ opinions play a vital role in the agriculture sector that yields good crop productivity. This paper presents a descriptive analysis of agriculture experts’ opinions through machine learning methods based on textual data collection. The data has been collected by surveying various academia, research institute, and industry of Punjab, Pakistan. The impact of various agricultural inputs such as seed quality, soil quality, soil-intensive tillage, climate changes, water shortage, synthetic fertilizer, and precision technologies on crop productivity have been collected through questionnaires. This research provides a descriptive analysis of collected agrarians experts opinions to increase the crop yield by providing awareness regarding current agriculture inputs to farmers by using machine learning. The current research provides a cohesive expert guideline for improving crop productivity, useful for agricultural policymaking, and conveys adequate farmers’ knowledge. Consequently, the proposed method is an innovative way of discovering recommendations of agrarians through sentiment analysis in survey data using machine learning methods. Furthermore, to the best of our knowledge, agrarians experts opinions on enhancing crop productivity have been considered for the first time in Pakistan.
Keywords:
Semantics Analysis
Agricultural
Crop Productivity
Machine Learning
Natural Language Processing (NLP)
artificial intelligence
opinion mining
text clustering
classification
Author(s) Name: Mehak Rehman, Abdul Razzaq, Irfan Ahmad Baig, Javeria Jabeen, Muhammad Hammad Nadeem Tahir, Umar Ijaz Ahmed, Adnan Altaf, Touqeer Abbas
Journal name: Applied Artificial Intelligence
Conferrence name:
Publisher name: Taylor and Francis
DOI: 10.1080/08839514.2021.2012055
Volume Information: Volume 36, 2022 - Issue 1
