# Assessing the Relevance of Opinions in Uncertainty and Info-Incompleteness Conditions
## 7 Conclusions and Future Work  
In the present study, the problem of assessing the best opinion in conditions of uncertainty and info-incompleteness was addressed. To achieve this objective, we proposed a solution that provides a learning model that, starting from the observations related to Probability, Plausibility, Credibility, and Possibility, together with other relevant characteristics, provides the weights associated with the considered set of opinions. The proposed model minimizes the error of the results provided by the best price function, defined as the weighted sum of the considered opinions. The experiment was performed on a real case study concerning the market evaluation of soccer players by building a dataset based on the information sources of Transfermarkt, Football Manager, and FIFA21. The input space concerns features acquired one year before the subsequent transfer, while the ground truth is represented by the cost of the actual transfer. The experiments were carried out for a total of 398 occurrences by varying the set of opinions acquired for taking decisions, both in conditions of info-completeness and info-incompleteness; in the first case, the Probability was considered, while, in the second case, we limited the hypotheses to the set of Plausibility, Credibility, and Possibility only.  
The results prove the consistency to the prodromal study taken as reference and that it is possible to reach an error for the price prediction of 0.86 MBPE (0.61% of normalized error) and \(2.47\pm 0.188\) MBPE (\(1.89\pm 0.15\%\) of normalized error) on the test set in conditions of info-completeness and info-incompleteness, respectively. Furthermore, from the analysis of statistical significance, it was found that the Probability opinion is fundamental in conditions of info-completeness; instead, in conditions of info-incompleteness, it is possible to adopt any set that considers Plausibility, Credibility, and Possibility. Finally, it was found that the employment of the Credibility-Possibility pair represents a better choice compared to the assumption involving the Possibility opinion only.  
A possible future work regards the extension of the present study for the assessment of opinions' relevance by minimizing the occurrence and reliability functions in conditions of uncertainty and info-incompleteness. Regarding a real-world application, it is possible to define a decision support system to assist the Atmosphere Arc model [23], which brings the real economy into the digital economy through a Decentralized Content Management System (DCMS) and an Oracle. The DCMS contains the documentation of human work, while the Oracle analyzes the documentation and distributes a blockchain token. The proposed model can be employed to support token production and the documentation of the activities concerning a soccer society, providing a better estimation of the value.  
All authors contributed equally to the present work. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.