ICTNET at Temporal Summarization Track TREC 2014
Lei Chen, Hainan Zhang, Siying Li, Zhiyuan Ji, Qian Liu, Yue Liu, Dayong Wu, Xueqi Cheng · Text REtrieval Conference · 2014
Abstract : In this paper, we describe our solutions of the Session Track at TREC 2014. Our main idea is to re-rank the documents the official supplies as RL1. In order to get good results of the re-ranked documents, we implement the learning to rank model which needs to extract some features. We use the relevance judgments of Session Track TREC 2013 as training set this year and also we use it as testing set by 5 -fold cross-validation. The rest of this paper is organized as follows. We detail our models in section 2. Section 3 describes our experiments, including our evaluation results. Conclusions are made in the last session.