His XML framework research extends to the thematically linked field of World Wide Web. In his works, he conducts interdisciplinary research on XML framework and XML. His work blends XML and XML Signature studies together. Many of his studies involve connections with topics such as Document Structure Description and XML Signature. Yannis Papakonstantinou frequently studies issues relating to XML Encryption and Document Structure Description. His XML Encryption study frequently draws connections to other fields, such as XML validation. He combines XML validation and XML Schema Editor in his research. In his works, he undertakes multidisciplinary study on XML Schema Editor and Efficient XML Interchange. His Efficient XML Interchange study often links to related topics such as World Wide Web.
Yannis Papakonstantinou integrates Database and Operating system in his research. He undertakes interdisciplinary study in the fields of Operating system and Database through his works. He integrates many fields, such as Information retrieval and Data mining, in his works. In his works, he performs multidisciplinary study on Data mining and Information retrieval. World Wide Web is often connected to XQuery in his work. His research combines World Wide Web and XQuery. Yannis Papakonstantinou combines Programming language and Query language in his research. He undertakes multidisciplinary studies into Query language and Programming language in his work. His work blends XML and Efficient XML Interchange studies together.
Yannis Papakonstantinou conducted interdisciplinary study in his works that combined Data compression and Algorithm. In his works, he performs multidisciplinary study on Algorithm and Data compression. Yannis Papakonstantinou performs integrative study on Artificial intelligence and Inference. He integrates many fields, such as Inference and Artificial intelligence, in his works. His research links Bottleneck with Embedded system. His research ties Embedded system and Bottleneck together. With his scientific publications, his incorporates both Machine learning and Deep learning. Deep learning and Convolutional neural network are two areas of study in which he engages in interdisciplinary work. He integrates Convolutional neural network and Machine learning in his research.
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The TSIMMIS project: Integration of heterogeneous information sources
Sudarshan S. Chawathe;Hector Garcia-Molina;Joachim Hammer;Kelly Ireland.
Object exchange across heterogeneous information sources
Y. Papakonstantinou;H. Garcia-Molina;J. Widom.
international conference on data engineering (1995)
The TSIMMIS Approach to Mediation: Data Models and Languages
Hector Garcia-Molina;Yannis Papakonstantinou;Dallan Quass;Anand Rajaraman.
next generation information technologies and systems (1997)
Discover: keyword search in relational databases
Vagelis Hristidis;Yannis Papakonstantinou.
very large data bases (2002)
Big data and its technical challenges
H. V. Jagadish;Johannes Gehrke;Alexandros Labrinidis;Yannis Papakonstantinou.
Communications of The ACM (2014)
Efficient IR-style keyword search over relational databases
Vagelis Hristidis;Luis Gravano;Yannis Papakonstantinou.
very large data bases (2003)
Efficient keyword search for smallest LCAs in XML databases
Yu Xu;Yannis Papakonstantinou.
international conference on management of data (2005)
Objectrank: authority-based keyword search in databases
Andrey Balmin;Vagelis Hristidis;Yannis Papakonstantinou.
very large data bases (2004)
Query caching and optimization in distributed mediator systems
S. Adali;K. S. Candan;Y. Papakonstantinou;V. S. Subrahmanian.
international conference on management of data (1996)
PREFER: a system for the efficient execution of multi-parametric ranked queries
Vagelis Hristidis;Nick Koudas;Yannis Papakonstantinou.
international conference on management of data (2001)
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