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2016 | OriginalPaper | Buchkapitel

Structure-Oriented Techniques for XML Document Partitioning

verfasst von : Gianni Costa, Riccardo Ortale

Erschienen in: Novel Applications of Intelligent Systems

Verlag: Springer International Publishing

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Abstract

Focusing on only one type of structural component in the process of clustering XML documents may produce clusters with a certain extent of inner structural inhomogeneity, due either to uncaught differences in the overall logical structures of the available XML documents or to inappropriate choices of the targeted structural component. To overcome these limitations, two approaches to clustering XML documents by multiple heterogeneous structures are proposed. An approach looks at the simultaneous occurrences of such structures across the individual XML documents. The other approach instead combines multiple clusterings of the XML documents, separately performed with respect to the individual types of structures in isolation. A comparative evaluation over both real and synthetic XML data proved that the effectiveness of the devised approaches is at least on a par and even superior with respect to the effectiveness of state-of-the-art competitors. Additionally, the empirical evidence also reveals that the proposed approaches outperform such competitors in terms of time efficiency.

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Literatur
1.
Zurück zum Zitat S. Abiteboul, P. Buneman, D. Suciu, Data on the Web: From Relations to Semistructured Data and XML (Morgan Kaufmann, 2000) S. Abiteboul, P. Buneman, D. Suciu, Data on the Web: From Relations to Semistructured Data and XML (Morgan Kaufmann, 2000)
2.
3.
Zurück zum Zitat C.C. Aggarwal et al., XProJ: a framework for projected structural clustering of XML documents, in Proceedings of SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) (2007), pp. 46–55 C.C. Aggarwal et al., XProJ: a framework for projected structural clustering of XML documents, in Proceedings of SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) (2007), pp. 46–55
4.
Zurück zum Zitat R.A. Baeza-Yates, N. Fuhr, Y. Andamaarek, Special issue on XML retrieval. ACM Trans. Inf. Syst. 24(4) (2006) R.A. Baeza-Yates, N. Fuhr, Y. Andamaarek, Special issue on XML retrieval. ACM Trans. Inf. Syst. 24(4) (2006)
5.
Zurück zum Zitat L. Denoyer, P. Gallinari, Overview of the INEX 2008 XML mining track, in Advances in Focused Retrieval (2009), pp. 401–411 L. Denoyer, P. Gallinari, Overview of the INEX 2008 XML mining track, in Advances in Focused Retrieval (2009), pp. 401–411
6.
Zurück zum Zitat T. Asai et al., Efficient substructure discovery from large semi-structured data, in Proceedings of Siam Conference on Data Mining (SDM) (2002), pp. 158–174 T. Asai et al., Efficient substructure discovery from large semi-structured data, in Proceedings of Siam Conference on Data Mining (SDM) (2002), pp. 158–174
7.
Zurück zum Zitat K. Wang, H. Liu, Discovering typical structures of documents: a road map approach, in Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (1998), pp. 146–154 K. Wang, H. Liu, Discovering typical structures of documents: a road map approach, in Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (1998), pp. 146–154
8.
Zurück zum Zitat A. Algergawy, M. Mesiti, R. Nayak, G. Saake, XML data clustering: an overview. ACM Comput. Surv. 43(4), 25:1–25:41 (2011)CrossRef A. Algergawy, M. Mesiti, R. Nayak, G. Saake, XML data clustering: an overview. ACM Comput. Surv. 43(4), 25:1–25:41 (2011)CrossRef
9.
Zurück zum Zitat L. Denoyer, P. Gallinari, Report on the XML mining track at INEX 2007: categorization and clustering of XML documents. ACM SIGIR Forum 42(1), 22–28 (2008)CrossRef L. Denoyer, P. Gallinari, Report on the XML mining track at INEX 2007: categorization and clustering of XML documents. ACM SIGIR Forum 42(1), 22–28 (2008)CrossRef
10.
Zurück zum Zitat G. Demartini et al., Report on the XML mining track at INEX 2008: categorization and clustering of XML documents. ACM SIGIR Forum 43(1), 17–36 (2009)CrossRef G. Demartini et al., Report on the XML mining track at INEX 2008: categorization and clustering of XML documents. ACM SIGIR Forum 43(1), 17–36 (2009)CrossRef
11.
Zurück zum Zitat R. Nayak et al., Overview of the INEX 2009 XML mining track: clustering and classification of XML documents, in Focused Retrieval and Evaluation (2010), pp. 366–378 R. Nayak et al., Overview of the INEX 2009 XML mining track: clustering and classification of XML documents, in Focused Retrieval and Evaluation (2010), pp. 366–378
12.
Zurück zum Zitat M.N. Garofalakis et al., XTRACT: a system for extracting document type descriptors from XML documents, in Proceedings of International Conference on Management of Data (SIGMOD) (2000), pp. 165–176 M.N. Garofalakis et al., XTRACT: a system for extracting document type descriptors from XML documents, in Proceedings of International Conference on Management of Data (SIGMOD) (2000), pp. 165–176
13.
Zurück zum Zitat S. Nestorov, S. Abiteboul, R. Motwani, Extracting schema from semistructured data, in Proceedings of ACM SIGMOD International Conference on Management of Data (SIGMOD) (1998), pp. 295–306 S. Nestorov, S. Abiteboul, R. Motwani, Extracting schema from semistructured data, in Proceedings of ACM SIGMOD International Conference on Management of Data (SIGMOD) (1998), pp. 295–306
14.
Zurück zum Zitat S. Bergamaschi, S. Castano, M. Vincini, Semantic integration of semistructured and structured data sources. SIGMOD Record 28(1), 54–59 (1999)CrossRef S. Bergamaschi, S. Castano, M. Vincini, Semantic integration of semistructured and structured data sources. SIGMOD Record 28(1), 54–59 (1999)CrossRef
15.
Zurück zum Zitat G. Costa, G. Manco, R. Ortale, A. Tagarelli, A tree-based approach to clustering XML documents by structure, in Proceedings of International Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (2004), pp. 137–148 G. Costa, G. Manco, R. Ortale, A. Tagarelli, A tree-based approach to clustering XML documents by structure, in Proceedings of International Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (2004), pp. 137–148
16.
Zurück zum Zitat S. Joshi, N. Agrawal, R. Krishnapuram, S. Negi, A bag of paths model for measuring structural similarity in web documents, in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2003), pp. 577–582 S. Joshi, N. Agrawal, R. Krishnapuram, S. Negi, A bag of paths model for measuring structural similarity in web documents, in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2003), pp. 577–582
17.
Zurück zum Zitat G. Costa, R. Ortale, E. Ritacco, Effective XML classification using content and structural information via rule learning, in IEEE International Conference on Tools with Artificial Intelligence (2011), pp. 102–109 G. Costa, R. Ortale, E. Ritacco, Effective XML classification using content and structural information via rule learning, in IEEE International Conference on Tools with Artificial Intelligence (2011), pp. 102–109
18.
Zurück zum Zitat G. Costa, R. Ortale, On effective XML clustering by path commonality: an efficient and scalable algorithm, in IEEE International Conference on Tools with Artificial Intelligence (2012), pp. 389–396 G. Costa, R. Ortale, On effective XML clustering by path commonality: an efficient and scalable algorithm, in IEEE International Conference on Tools with Artificial Intelligence (2012), pp. 389–396
19.
Zurück zum Zitat G. Costa, R. Ortale, E. Ritacco, X-class: associative classification of XML documents by structure. ACM Trans. Inf. Syst. 31(1), 3:1–3:40 (2013)CrossRef G. Costa, R. Ortale, E. Ritacco, X-class: associative classification of XML documents by structure. ACM Trans. Inf. Syst. 31(1), 3:1–3:40 (2013)CrossRef
20.
Zurück zum Zitat T. Dalamagas, T. Cheng, K.-J. Winkel, T.K. Sellis, A methodology for clustering XML documents by structure. Inf. Syst. 31(3), 187–228 (2006)CrossRef T. Dalamagas, T. Cheng, K.-J. Winkel, T.K. Sellis, A methodology for clustering XML documents by structure. Inf. Syst. 31(3), 187–228 (2006)CrossRef
21.
Zurück zum Zitat F.D. Francesca, G. Gordano, R. Ortale, A. Tagarelli, Distance-based clustering of XML documents, in International ECML/PKDD Workshop on Mining Graphs, Trees and Sequences (2003), pp. 75–78 F.D. Francesca, G. Gordano, R. Ortale, A. Tagarelli, Distance-based clustering of XML documents, in International ECML/PKDD Workshop on Mining Graphs, Trees and Sequences (2003), pp. 75–78
22.
Zurück zum Zitat M.J. Zaki, C.C. Aggarwal, Xrules: an effective structural classifier for XML data, in Proceedings of SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), (2003) pp. 316–325 M.J. Zaki, C.C. Aggarwal, Xrules: an effective structural classifier for XML data, in Proceedings of SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), (2003) pp. 316–325
23.
Zurück zum Zitat W. Lian, D.W.-L. Cheung, N. Mamoulis, S.-M. Yiu, An efficient and scalable algorithm for clustering XML documents by structure. IEEE Trans. Knowl. Data Eng. 16(1), 82–96 (2004)CrossRef W. Lian, D.W.-L. Cheung, N. Mamoulis, S.-M. Yiu, An efficient and scalable algorithm for clustering XML documents by structure. IEEE Trans. Knowl. Data Eng. 16(1), 82–96 (2004)CrossRef
24.
Zurück zum Zitat G. Costa, G. Manco, R. Ortale, E. Ritacco, Hierarchical clustering of XML documents focused on structural components. Data Knowl. Eng. 84, 26–46 (2013)CrossRef G. Costa, G. Manco, R. Ortale, E. Ritacco, Hierarchical clustering of XML documents focused on structural components. Data Knowl. Eng. 84, 26–46 (2013)CrossRef
25.
Zurück zum Zitat G. Costa, R. Ortale, Structure-oriented clustering of XML documents: a transactional approach, in IEEE International Conference on Intelligent Systems (2012), pp. 188–193 G. Costa, R. Ortale, Structure-oriented clustering of XML documents: a transactional approach, in IEEE International Conference on Intelligent Systems (2012), pp. 188–193
26.
Zurück zum Zitat M.J. Zaki, Efficiently mining frequent trees in a forest: algorithms and applications. IEEE Trans. Knowl. Data Eng. 17(8), 1021–1035 (2005)CrossRef M.J. Zaki, Efficiently mining frequent trees in a forest: algorithms and applications. IEEE Trans. Knowl. Data Eng. 17(8), 1021–1035 (2005)CrossRef
27.
Zurück zum Zitat E. Cesario, G. Manco, R. Ortale, Top-down parameter-free clustering of high-dimensional categorical data. IEEE Trans. Knowl. Data Eng. 19(12), 1607–1624 (2007)CrossRef E. Cesario, G. Manco, R. Ortale, Top-down parameter-free clustering of high-dimensional categorical data. IEEE Trans. Knowl. Data Eng. 19(12), 1607–1624 (2007)CrossRef
28.
Zurück zum Zitat T. Li, M. Ogihara, S. Ma, On combining multiple clusterings: an overview and a new perspective. Appl. Intell. 33(2), 207–219 (2010)CrossRef T. Li, M. Ogihara, S. Ma, On combining multiple clusterings: an overview and a new perspective. Appl. Intell. 33(2), 207–219 (2010)CrossRef
29.
Zurück zum Zitat R. Baeza-Yates, B. Ribeiro-Neto, Modern Information Retrieval (Addison-Wesley, Boston, 1999) R. Baeza-Yates, B. Ribeiro-Neto, Modern Information Retrieval (Addison-Wesley, Boston, 1999)
30.
Zurück zum Zitat G. Costa, G. Manco, R. Ortale, A hierarchical model-based approach to co-clustering high-dimensional data, in Proceedings of ACM Symposium on Applied Computing (2008), pp. 886–890 G. Costa, G. Manco, R. Ortale, A hierarchical model-based approach to co-clustering high-dimensional data, in Proceedings of ACM Symposium on Applied Computing (2008), pp. 886–890
31.
Zurück zum Zitat G. Costa, G. Manco, R. Ortale, An incremental clustering scheme for data de-duplication. Data Min. Knowl. Disc. 20(1), 152–187 (2010)CrossRefMathSciNet G. Costa, G. Manco, R. Ortale, An incremental clustering scheme for data de-duplication. Data Min. Knowl. Disc. 20(1), 152–187 (2010)CrossRefMathSciNet
Metadaten
Titel
Structure-Oriented Techniques for XML Document Partitioning
verfasst von
Gianni Costa
Riccardo Ortale
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-14194-7_9