{"title":"Intelligent Form Generator Using Expert Systems","authors":"Kgh Piumali, B. Hettige","doi":"10.29322/ijsrp.13.01.2023.p13313","DOIUrl":null,"url":null,"abstract":"ion - Forms play an integral part in modern living. People fill and handle forms to accomplish various tasks in day today life. There are various developed technologies related to form handling. However, in some instances, these existing form-filling, and handling technologies are not sufficient to provide the best solutions with clear guidance for the users. The main objective of this research paper is to design, and development of a web-based forms generation solution named “Interllib Forms” that can be considered as an expert in filling forms. This proposed solution will be helpful to reduce uncertainties faced by applicants during form filling. This system was built as an expert system builder tool. Also, Interllib forms are built as a platform with the facility to create new form components, each with modules that represent the main functionalities of an expert system builder tool. Thus, ”Add Questions”, and” Add Results“ modules were built to provide a knowledge acquisition functionality. The “Map and Submit” module was built to map each “Questions and Results” and build rules using a specific calculation. API keys and Links module was built to generate a unique API key for each form component which is embedded in all the Questions and Results. Also, a specific logic was used for inferencing mapped rules relevant to the applicant’s queries. This acts as an intelligent feature. The “Interllib Forms” -web application is tested with user support and can be concluded that 70.8% of end users have positive feedback regarding the acceptable level. And 53.3% of knowledge experts have moderate feedback regarding the logic used in Question and Results mapping which will be subjected to be modified with an advanced algorithm in the future.","PeriodicalId":14290,"journal":{"name":"International Journal of Scientific and Research Publications (IJSRP)","volume":"1 4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Scientific and Research Publications (IJSRP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29322/ijsrp.13.01.2023.p13313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
ion - Forms play an integral part in modern living. People fill and handle forms to accomplish various tasks in day today life. There are various developed technologies related to form handling. However, in some instances, these existing form-filling, and handling technologies are not sufficient to provide the best solutions with clear guidance for the users. The main objective of this research paper is to design, and development of a web-based forms generation solution named “Interllib Forms” that can be considered as an expert in filling forms. This proposed solution will be helpful to reduce uncertainties faced by applicants during form filling. This system was built as an expert system builder tool. Also, Interllib forms are built as a platform with the facility to create new form components, each with modules that represent the main functionalities of an expert system builder tool. Thus, ”Add Questions”, and” Add Results“ modules were built to provide a knowledge acquisition functionality. The “Map and Submit” module was built to map each “Questions and Results” and build rules using a specific calculation. API keys and Links module was built to generate a unique API key for each form component which is embedded in all the Questions and Results. Also, a specific logic was used for inferencing mapped rules relevant to the applicant’s queries. This acts as an intelligent feature. The “Interllib Forms” -web application is tested with user support and can be concluded that 70.8% of end users have positive feedback regarding the acceptable level. And 53.3% of knowledge experts have moderate feedback regarding the logic used in Question and Results mapping which will be subjected to be modified with an advanced algorithm in the future.