Library

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Filters: First Letter Of Title is F and Author is Amit Sheth  [Clear All Filters]
1989
Amit Sheth. Fault Tolerance in a Very Large Database System: A Strawman Analysis. In Fault Tolerance in a Very Large Database System: A Strawman Analysis. 1989.  (790.3 KB)
2004
John Miller, Kaarthik Sivashanmugam, Amit Sheth, Kunal Verma. Framework for Semantic Web Process Composition. Special Issue: Semantic Web Services and Their Role in Enterprise Application Integration and E-Commerce. 2004 ;.  (345.14 KB)
2006
Amit Sheth, Krzysztof Kochut, Cartic Ramakrishnan. A Framework for Schema-Driven Relationship Discovery from Unstructured Text. In A Framework for Schema-Driven Relationship Discovery from Unstructured Text. Athens, GA, USA; 2006.  (888.84 KB)
2010
Prateek Jain, Pascal Hitzler, Amit Sheth. Flexible Bootstrapping-Based Ontology Alignment. In The Fifth International Workshop on Ontology Matching collocated with the 9th International Semantic Web Conference ISWC-2010, November 7, 2010; 2010.  (62.44 KB)
2016
Lakshika Balasuriya, Sanjaya Wijeratne, Derek Doran, Amit Sheth. Finding Street Gang Members on Twitter. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016). San Francisco, CA, USA; 2016. p. 685-692.  (2.02 MB)
Vinh Nguyen, Jyoti Leeka, Olivier Bodenreider, Amit Sheth. A Formal Graph Model for RDF and Its Implementation. CoRR. 2016 ;abs/1606.00480.  (701.27 KB)
2018
Amit Sheth, Hong Yung Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, Revathy Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra. Feasibility of Recording Sleep Quality And Sleep Duration Using Fitbit in Children with Asthma. 32nd Annual Meeting of the Associated Professional Sleep Societies (SLEEP), 2-6 June 2018, Baltimore, MD; 2018.  (650.88 KB)
Sanjaya Wijeratne, Amit Sheth, Shreyansh Bhatt, Lakshika Balasuriya, Hussein S. Al-Olimat, Manas Gaur, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan. Feature Engineering for Twitter-based Applications. In Feature Engineering for Machine Learning and Data Analytics. New York: Chapman and Hall. Data Mining and Knowledge Discovery Series; 2018. p. 359-393.  (684.81 KB)