1C1-2 アンサンブル法によるブログフィード検索(機械学習)

概要

論文の詳細を見る
The previous work for blog feed search typically aggregates the contents of blog posts or the relevance of blog posts belonging to the same site to find relevant blog sites. As another approach, the present study focuses on an assumption that there are some characteristics shared among relevant blog sites and, based on the assumption, proposes a machine learning framework for feed search. More precisely, we adapt an ensemble framework, which combines multiple classifiers or their outputs, and treat retrieval models as pseudo classifiers.
一般社団法人日本機械学会の論文
2011-09-01