Research
Proposal of a Ranking Method for Comments in Social Media Using Ratings of Comment Posters
Many social media adopt a ranking method in which comments are ranked in the order of the number of ratings attached to each comment. However, this method has the disadvantage of ratings being concentrated on comments posted at an early stage. Even if there are high-quality comments posted later, most of them are buried without being noticed. This paper proposes a ranking method that considers not only the ratings for each comment but also the previous ratings the comment poster has received. The effectiveness of the proposed method is evaluated through a simulation. We demonstrate that with the proposed method, high-quality comments are displayed in the higher positions regardless of the posting period.
Proposal of a Flooding-based Flexible Search Method for Chord Networks
Recently, peer-to-peer (P2P) network models have been attracting considerable attention. P2P models can be classified into structured and unstructured P2P models. Representative search methods for structured and unstructured P2P networks are Chord and Flooding, respectively. It is difficult to realize flexible search in Chord networks. On the other hand, a large number of query transmissions are required for Flooding. In this study, we propose a Flooding-based search method for Chord networks. Our method works separately from the traditional search method for Chord networks. It suppresses the transmission of redundant queries by considering the topological properties of the structured networks and enables flexible search in Chord networks. Through simulation experiments, we evaluate the performance of the proposed search method and show its effectiveness.
