Abstract
In order to extract meaningful and hidden knowledge from semistructured documents such as HTML or XML files, methods for discovering frequent patterns or common characteristics in semistructured documents have been more and more important. We propose new methods for discovering maximally frequent tree structured patterns in semistructured Web documents by using tag tree patterns as hypotheses. A tag tree pattern is an edge labeled tree which has ordered or unordered children and structured variables. An edge label is a tag or a keyword in such Web documents, and a variable can match an arbitrary subtree, which represents a field of a semistructured document. As a special case, a contractible variable can match an empty subtree, which represents a missing field in a semistructured document. Since semistructured documents have irregularities such as missing fields, a tag tree pattern with contractible variables is suited for representing tree structured patterns in such semistructured documents. First, we present an algorithm for generating all maximally frequent ordered tag tree patterns with contractible variables. Second, we give an algorithm for generating all maximally frequent unordered tag tree patterns with contractible variables.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abiteboul, S., Buneman, P., Suciu, D.: Data on the Web: From Relations to Semistructured Data and XML. Morgan Kaufmann, San Francisco (2000)
Asai, T., Abe, K., Kawasoe, S., Arimura, H., Sakamoto, H., Arikawa, S.: Efficient substructure discovery from large semi-structured data. In: Proc. 2nd SIAM Int. Conf. Data Mining (SDM 2002), pp. 158–174 (2002)
Asai, T., Arimura, H., Uno, T., Nakano, S.: Discovery of frequent substructures in large unordered trees. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds.) DS 2003. LNCS (LNAI), vol. 2843, pp. 47–61. Springer, Heidelberg (2003)
Beyer, T., Hedetniemi, S.: Constant time generation of rooted trees. SIAM J. Comput. 9, 706–712 (1980)
Miyahara, T., Shoudai, T., Uchida, T., Takahashi, K., Ueda, H.: Discovery of frequent tree structured patterns in semistructured web documents. In: Cheung, D., Williams, G.J., Li, Q. (eds.) PAKDD 2001. LNCS (LNAI), vol. 2035, pp. 47–52. Springer, Heidelberg (2001)
Miyahara, T., Suzuki, Y., Shoudai, T., Uchida, T., Hirokawa, S., Takahashi, K., Ueda, H.: Extraction of tag tree patterns with contractible variables from irregular semistructured data. In: Proc. PAKDD 2003. LNCS (LNAI), vol. 2637, pp. 430–436. Springer, Heidelberg (2003)
Miyahara, T., Suzuki, Y., Shoudai, T., Uchida, T., Takahashi, K., Ueda, H.: Discovery of frequent tag tree patterns in semistructured web documents. In: Chen, M.-S., Yu, P.S., Liu, B. (eds.) PAKDD 2002. LNCS (LNAI), vol. 2336, pp. 341–355. Springer, Heidelberg (2002)
Nakano, S., Uno, T.: Efficient generation of rooted trees. NII Technical Report, NII-2003-005E, National Institute of Infomatics, Japan (2003)
Skarbek, W.: Generating ordered trees. Theoretical Computer Science 57, 153–159 (1988)
Suzuki, Y., Shoudai, T., Matsumoto, S., Uchida, T., Miyahara, T.: Efficient learning of ordered and unordered tree patterns with contractible variables. In: Gavaldá, R., Jantke, K.P., Takimoto, E. (eds.) ALT 2003. LNCS (LNAI), vol. 2842, pp. 114–128. Springer, Heidelberg (2003)
Wang, K., Liu, H.: Discovering structural association of semistructured data. IEEE Trans. Knowledge and Data Engineering 12, 353–371 (2000)
Washio, T., Motoda, H.: State of the art of graph-based data mining. SIGKDD Explorations 5, 59–68 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Miyahara, T., Suzuki, Y., Shoudai, T., Uchida, T., Takahashi, K., Ueda, H. (2004). Discovery of Maximally Frequent Tag Tree Patterns with Contractible Variables from Semistructured 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_17
Download citation
DOI: https://doi.org/10.1007/978-3-540-24775-3_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22064-0
Online ISBN: 978-3-540-24775-3
eBook Packages: Springer Book Archive