Ethnobotanical Studies from Amaravathy Range of Indira Gandhi Wildlife Sanctuary, Western Ghats, Coimbatore District, Southern India

The ethnobotanical studies were carried out in the Amaravathy Range of India Gandhi Wildlife Sanctuary, Anamalais, the Western. Ghats, Tamilnadu during June 2005 – May 2006. Puliyars and Muthuvars are the two dominant tribes who inhabit the dense jungles of this range; they have a fair knowledge on the indigenous flora. Due to intensive and extensive explorations have resulted in the collection of information on ninety four plant species; out of which, 73 are wild and the rest are cultivated; within the wild plants 24 are used as edible fruits; 12 species as a leafy vegetable; 23 species are having medicinal value and 18 species utilized for miscellaneous uses and the same is provided

Identifying Features and Predicting Consumer Helpfulness of Product Reviews

Major corporations utilize data from online platforms to make user product or service recommendations. Companies like Netflix, Amazon, Yelp, and Spotify rely on purchasing trends, user reviews, and helpfulness votes to make content recommendations. This strategy can increase user engagement on a company\u27s platform. However, misleading and/or spam reviews significantly hinder the success of these recommendation strategies. The rise of social media has made it increasingly difficult to distinguish between authentic content and advertising, leading to a burst of deceptive reviews across the marketplace. The helpfulness of the review is subjective to a voting system. As such, this study aims to predict product reviews that are helpful and enable strategies to moderate a user review post to improve the helpfulness quality of a review. The prediction of review helpfulness will utilize NLP methods against Amazon product review data. Multiple machine learning principles of different complexities will be implemented in this review to compare the results and ease of implementation (e.g., Naïve Bayes and BERT) to predict a product review\u27s helpfulness. The result of this study concludes that review helpfulness can be effectively predicted through the deployment of model features. The removal of duplicate reviews, the imputing of review helpfulness based on word count, and the inclusion of lexical elements are recommended to be included in review analysis. The results of this research indicate that the deployment of these features results in a high F1-Score of 0.83 for predicting helpful Amazon product reviews

Rainfall and Elevation Influence the Local-Scale Distribution of Tree Community in the Southern Region of Western Ghats Biodiversity Hotspot (India)

The present study characterises the tree communities with respect to topographic and climatic variables and identifies the most important environmental correlate of species richness in the southern region of Western Ghats Biodiversity Hotspot, India. Digitally derived environmental variables in combination with tree species richness information were analysed using Canonical Correspondence Analysis (CCA) to characterise the communities. Multiple regression technique based on stepwise backward elimination was used to identify the most important environment correlate of species richness. Canonical correspondence analysis results in six major tree communities along the first and second axes. Rainfall is the dominant environmental gradient influencing vegetation patterns on the first CCA axis while elevation showed the highest correlation with the second CCA axis. Backward elimination regression technique yielded rainfall as the most important environmental correlate of species richness. Results were in agreement with the observations in the Neotropics that rainier areas maintain high species diversity