[2N1-GS-4] Web intelligence:

[2N1-GS-4-03] Recommending Fanfic Works Based on Character Network Disparity Analysis

〇Xinru TIAN¹, Shin'ichi KONOMI¹ (1. Kyushu University)

[[Online]]

Keywords:Recommender System, Character Network, Natural Language Processing, Fanfic

This paper presents a novel character network-based approach for recommending fanfic works. Fanfic works are secondary creation based on original works of literature, painting, music and video, and, as such it is difficult to model users' interests in them by using conventional recommendation techniques. We propose a recommendation system based on character network analysis, which analyzes and compares a type of social networks in the fanfic works and the original work to derive the degree of relevance of the fanfic works to the original work and recommend fanfic works effectively.