Mining E-Documents to Uncover Structures

An e-Document, D, coded in HTML is comprised of a body and a head. The body includes the contents of the e-document, and the head includes, among other things, metadata.

[1]  Chia-Chu Chiang,et al.  Text data mining: a case study , 2005, International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II.

[2]  M. F. Porter,et al.  An algorithm for suffix stripping , 1997 .

[3]  Steffen Staab,et al.  Knowledge Technologies for the Semantic Web , 2001, WebNet.

[5]  Azita Bahrami,et al.  Ontology-Based Identification of Explicit and Implicit Metadata Terms , 2007, CSREA EEE.

[6]  Kyuseok Shim,et al.  SPIRIT: Sequential Pattern Mining with Regular Expression Constraints , 1999, VLDB.

[7]  Azita Bahrami.  An L-Tree Based Analysis of E-lessons , 2007, Fourth International Conference on Information Technology (ITNG'07).

[8]  Azita A. Bahrami.  A Framework for Development and Management of E-Lessons in E-Learning , 2005, WEBIST.

[9]  Tsau Young Lin,et al.  Granular Computing and Modeling the Human Thoughts in Web Documents , 2007, IFSA.

[10]  Ian Witten,et al.  Data Mining , 2000 .

[11]  Valter Crescenzi,et al.  RoadRunner: Towards Automatic Data Extraction from Large Web Sites , 2001, VLDB.

[12]  James A. Hendler,et al.  The Semantic Web" in Scientific American , 2001 .

[13]  Tsau Young Lin,et al.  Granular computing: examples, intuitions and modeling , 2005, 2005 IEEE International Conference on Granular Computing.

[14]  Stefanos D. Kollias,et al.  A String Metric for Ontology Alignment , 2005, SEMWEB.

[15]  Azita Bahrami.  Structural Discovery of E-lessons , 2006, CSREA EEE.

[16]  Willem Robert van Hage,et al.  A Method to Combine Linguistic Ontology-Mapping Techniques , 2005, SEMWEB.

[17]  Eugene Agichtein,et al.  Mining reference tables for automatic text segmentation , 2004, KDD.