G.4. Information Storage and Retrieval
1. RRLUFF: Ranking function based on Reinforcement Learning using User Feedback and Web Document Features

V. Derhami; J. Paksima; H. Khajeh

Volume 7, Issue 3 , Summer 2019, , Pages 421-442

Abstract
  Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking ...  Read More

G.4. Information Storage and Retrieval
2. Web pages ranking algorithm based on reinforcement learning and user feedback

V. Derhami; J. Paksima; H. Khajah

Volume 3, Issue 2 , Summer 2015, , Pages 157-168

Abstract
  The main challenge of a search engine is ranking web documents to provide the best response to a user`s query. Despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ...  Read More