The purpose of this work aims is to automatically build top-k(the number of suggested results)light weight service based systems(LitSBSs)on the basis of user-given keywords.Compared with our previous work,we use a sco...The purpose of this work aims is to automatically build top-k(the number of suggested results)light weight service based systems(LitSBSs)on the basis of user-given keywords.Compared with our previous work,we use a score(oscore)to evaluate the keyword matching degree and QoS performance of a service so that we could find top-k LitSBSs with both high keyword matching degree and great QoS performance at the same time.In addition,to guarantee the quality of found top-k LitSBSs and improve the time efficiency,we redesign the database-driven algorithm(LitDB).We add the step of referential services selecting into the process of the LitDB,which could prioritize services with high quality(high keyword matching degree and great QoS performance).We design comprehensive experiments to demonstrate the great time performance of LitDB.展开更多
文摘The purpose of this work aims is to automatically build top-k(the number of suggested results)light weight service based systems(LitSBSs)on the basis of user-given keywords.Compared with our previous work,we use a score(oscore)to evaluate the keyword matching degree and QoS performance of a service so that we could find top-k LitSBSs with both high keyword matching degree and great QoS performance at the same time.In addition,to guarantee the quality of found top-k LitSBSs and improve the time efficiency,we redesign the database-driven algorithm(LitDB).We add the step of referential services selecting into the process of the LitDB,which could prioritize services with high quality(high keyword matching degree and great QoS performance).We design comprehensive experiments to demonstrate the great time performance of LitDB.
