TY - GEN
T1 - A relevance feedback model for fractal summarization
AU - Wang, Fu Lee
AU - Yang, Christopher C.
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2004.
PY - 2005
Y1 - 2005
N2 - As a result of the recent information explosion, there is an increasing demand for automatic summarization, and human abstractors often synthesize summaries that are based on sentences that have been extracted by machine. However, the quality of machine-generated summaries is not high. As a special application of information retrieval systems, the precision of automatic summarization can be improved by user relevance feedback, in which the human abstractor can direct the sentence extraction process and useful information can be retrieved efficiently. Automatic summarization with relevance feedback is a helpful tool to assist professional abstractors in generating summaries, and in this work we propose a relevance feedback model for fractal summarization. The results of the experiment show that relevance feedback effectively improves the performance of automatic fractal summarization.
AB - As a result of the recent information explosion, there is an increasing demand for automatic summarization, and human abstractors often synthesize summaries that are based on sentences that have been extracted by machine. However, the quality of machine-generated summaries is not high. As a special application of information retrieval systems, the precision of automatic summarization can be improved by user relevance feedback, in which the human abstractor can direct the sentence extraction process and useful information can be retrieved efficiently. Automatic summarization with relevance feedback is a helpful tool to assist professional abstractors in generating summaries, and in this work we propose a relevance feedback model for fractal summarization. The results of the experiment show that relevance feedback effectively improves the performance of automatic fractal summarization.
UR - http://www.scopus.com/inward/record.url?scp=35048825394&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-30544-6_14
DO - 10.1007/978-3-540-30544-6_14
M3 - Conference contribution
AN - SCOPUS:35048825394
SN - 9783540240303
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 368
EP - 377
BT - Digital Libraries
A2 - Miao, Qihao
A2 - Lim, Ee-peng
A2 - Chen, Zhaoneng
A2 - Fu, Yuxi
A2 - Chen, Hsinchun
A2 - Fox, Edward
T2 - 7th International Conference on Asian Digital Libraries, ICADL 2004
Y2 - 13 December 2004 through 17 December 2004
ER -