Abstract
Many electronic documents such as SGML/HTML/XML files and LaTeX files have tree structures. Such documents are called tree-structured documents. Many tree-structured documents contain large plain texts. In order to extract structural features among words from tree-structured documents, we consider the problem of finding frequent structured patterns among words in tree-structured documents. Let k≥ 2 be an integer and (W 1,W 2,...,W k ) a list of words which are sorted in lexicographical order. A consecutive path pattern on (W 1 , W 2 ,..., W k ) is a sequence 〈t 1;t 2;...,t k − 1〉 of labeled rooted ordered trees such that, for i=1,2,...,k-1, (1) t i consists of only one node having the pair (W i ,W i + 1) as its label, or (2) t i has just two nodes whose degrees are one and which are labeled with W i and W i + 1, respectively. We present a data mining algorithm for finding all frequent consecutive path patterns in tree-structured documents. Then, by reporting experimental results on our algorithm, we show that our algorithm is efficient for extracting structural features from tree-structured documents.
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Uchida, T., Mogawa, T., Nakamura, Y. (2004). Finding Frequent Structural Features among Words in Tree-Structured Documents. In: Dai, H., Srikant, R., Zhang, C. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science(), vol 3056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_43
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DOI: https://doi.org/10.1007/978-3-540-24775-3_43
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