A New Email Retrieval Ranking Approach
Email Retrieval task has recently taken much attention to help the user retrieve the email(s) related to thesubmitted query. Up to our knowledge, existing email retrieval ranking approaches sort the retrievedemails based on some heuristic rules, which are either search clues or some predefined user criteriarooted in email fields. Unfortunately, the user usually does not know the effective rule that acquires bestranking related to his query. This paper presents a new email retrieval ranking approach to tackle thisproblem. It ranks the retrieved emails based on a scoring function that depends on crucial email fields,namely subject, content, and sender. The paper also proposes an architecture to allow every user in anetwork/group of users to be able, if permissible, to know the most important network senders who areinterested in his submitted query words. The experimental evaluation on Enron corpus prove that ourapproach outperforms known email retrieval ranking approaches.