@inproceedings{bdef8ab745364533a2945657ff5ab2be,
title = "A comparative study of answer-contained snippets and traditional snippets",
abstract = "Almost every text search engine uses snippets to help users quickly assess the relevance of retrieved items in the ranked list. Although answer-contained snippets can help to improve the effectiveness of search intuitively, quantitative study of such intuition remains untouched. In this paper, we first propose a simple answer-contained snippet method for community-based Question and Answer (cQA) search, and then compare our method with the state-of-the-art traditional snippet algorithms. The experimental results show that the answer-contained snippet method significantly outperforms the state-of-the-art traditional methods, considering relevance judgements and information satisfaction evaluations.",
keywords = "Answer-contained snippet, CQA, Information retrieval, Quantitative study",
author = "Mao, \{Xian Ling\} and Dan Wang and Hao, \{Yi Jing\} and Wenqing Yuan and Heyan Huang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 12th Asia Information Retrieval Societies Conference, AIRS 2016 ; Conference date: 30-11-2016 Through 02-12-2016",
year = "2016",
doi = "10.1007/978-3-319-48051-0\_5",
language = "English",
isbn = "9783319480503",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "56--67",
editor = "Yi Chang and Ji-Rong Wen and Zhicheng Dou and Xin Zhao and Shaoping Ma and Yiqun Liu and Min Zhang",
booktitle = "Information Retrieval Technology - 12th Asia Information Retrieval Societies Conference, AIRS 2016, Proceedings",
address = "Germany",
}