Data & Knowledge Engineering, Volume 52, 2005

Volume 52, Number 1, January 2005

• Maria E. Orlowska, Shazia W. Sadiq:
  Collaborative business process technologies. 1-3
  
• Björn Decker, Jörg Rech, Klaus-Dieter Althoff, Andreas Klotz, Edda Leopold, Angi Voß:
  eParticipative Process Learning - process-oriented experience management and conflict solving. 5-31
  
• Hamada Ghenniwa, Michael N. Huhns, Weiming Shen:
  eMarketplaces for enterprise and cross enterprise integration. 33-59
  
• Thomas B. Hodel-Widmer, Klaus R. Dittrich:
  Concept and prototype of a collaborative business process environment for document processing. 61-120
  
• Günter Preuner, Michael Schrefl:
  Requester-centered composition of business processes from internal and external services. 121-155
  
• Satwik Seshasai, Amar Gupta, Ashwani Kumar:
  An integrated and collaborative framework for business design: A knowledge engineering approach. 157-179
  

Volume 52, Number 2, February 2005

• Sanjay Kumar Madria:
  XML schema and data management. 181-183
  
• Alex Dekhtyar, Ionut Emil Iacob:
  A framework for management of concurrent XML markup. 185-208
  
• Jyoti Jacob, Alpa Sachde, Sharma Chakravarthy:
  CX-DIFF: a change detection algorithm for XML content and change visualization for WebVigiL. 209-230
  
• Shiyong Lu, Yezhou Sun, Mustafa Atay, Farshad Fotouhi:
  On the consistency of XML DTDs. 231-247
  
• Yang Song, Sourav S. Bhowmick, Sanjay Kumar Madria:
  Bio2X: a rule-based approach for semi-automatic transformation of semi-structured biological data to XML. 249-271
  

Volume 52, Number 3, March 2005

• Denis Shestakov, Sourav S. Bhowmick, Ee-Peng Lim:
  DEQUE: querying the deep web. 273-311
  
• Faruq A. Al-Omari, Mohammad A. Al-Jarrah:
  Query by image and video content: a colored-based stochastic model approach. 313-332
  
• Zaher Al Aghbari:
  Array-index: a plug&search K nearest neighbors method for high-dimensional data. 333-352
  
• Ioannis N. Kouris, Christos Makris, Athanasios K. Tsakalidis:
  Using Information Retrieval techniques for supporting data mining. 353-383
  

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