{'fraction_non_alphanumeric': 0.011555555555555555, 'fraction_numerical': 0.0, 'mean_word_length': 5.471264367816092, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Interpretation and Recommendation Tasks Supported by Ceres System

This article describes the interpretation and recommendation modules of the Ceres system, an Expert System that supports the interpretation of soil samples, recommendation for lime, fertilizer and data management using resources from expert system and database technologies. Among the requirements of the application domain, it is the information analysis resulting from the interpretation process, which has the purpose of finding the causes of productivity variation. This analysis makes possible human interaction in the sense of preserving proprieties that favor the developing of vegetables. In this way, the Ceres system has been proposed to assist experts on possible actions to be implemented to improve soil quality. The system is compound by several modules that implement tools to analyse the different soil properties. The focus of this paper is to analyze soil chemical aspects and the analysis tasks related to them. The modules proposed were conceived with a knowledge base formed by ontology, an inference engine and an interface for external