@inproceedings{84e34c9d44bd4b5490ce39ed6d34914a,
title = "Semantic frame-based natural language understanding for intelligent topic detection agent",
abstract = "Detecting the topic of documents can help readers construct the background of the topic and facilitate document comprehension. In this paper, we proposed a semantic frame-based method for topic detection that simulates such process in human perception. We took advantage of multiple knowledge sources and identified discriminative patterns from documents through frame generation and matching mechanisms. Results demonstrated that our novel approach can effectively detect the topic of a document by exploiting the syntactic structures, semantic association, and the context within the text. Moreover, it also outperforms well-known topic detection methods.",
keywords = "Partial Matching, Semantic Class, Semantic Frame, Sequence Alignment, Topic Detection",
author = "Chang, {Yung Chun} and Hsieh, {Yu Lun} and Chen, {Cen Chieh} and Hsu, {Wen Lian}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 27th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014 ; Conference date: 03-06-2014 Through 06-06-2014",
year = "2014",
month = jan,
day = "1",
doi = "10.1007/978-3-319-07455-9_36",
language = "English",
isbn = "9783319074542",
volume = "8481",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 1",
pages = "339--348",
editor = "Moonis Ali and Jeng-Shyang Pan and Mong-Fong Horng and Shyi-Ming Chen",
booktitle = "Modern Advances in Applied Intelligence - 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014, Proceedings",
address = "Germany",
edition = "PART 1",
}