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transaction databases
E. J. Cameron, L. A. Ness, Amit Sheth. An Executor for Multidatabase Transactions which Achieves Maximal Parallelism. 1st International Workshop on Interoperability in Multidatabase Systems (IMS 1991). Kyoto, Japan: IEEE; 1991. p. 288 - 291.  (329.28 KB)
training data
Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit Sheth. Harnessing Twitter ‘Big Data’ for Automatic Emotion Identification. 2012 International Conference on Social Computing (SocialCom). Amsterdam, The Netherlands: IEEE; 2012. p. 587-592.  (156.44 KB)
Training
Andrew Buck, Tanvi Banerjee, James Keller. Evolving a Fuzzy Goal-Driven Strategy for the Game of Geister. 2014 IEEE Congress on Evolutionary Computation (CEC). Beijing, China: IEEE; 2014. p. 28 - 35.
Traffic events
Roopteja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth. A Knowledge Graph Framework for Detecting Traff€ic Events Using Stationary Cameras. In Industrial Knowledge Graphs 2017 Workshop (co-located with 9th International ACM Web Science Conference 2017). Troy, NY; 2017.  (3.03 MB)
traffic dynamics
Pramod Anantharam, Krishnaprasad Thirunarayan, Surendra Marupudi, Amit Sheth, Tanvi Banerjee. Understanding City Traffic Dynamics Utilizing Sensor and Textual Observations. In 30th AAAI Conference on Artificial Intelligence (AAAI-16). Phoenix, Arizona; 2016.  (2.05 MB) (5.96 MB)
traffic analytics
Pramod Anantharam, Payam Barnaghi, Amit Sheth. Data Processing and Semantics for Advanced Internet of Things (IoT) Applications: modeling, annotation, integration, and perception. International Conference on Web Intelligence, Mining, and Semantics (WIMS '13). Madrid, Spain: ACM; 2013.  (154.65 KB)
Amit Sheth, Pramod Anantharam. Physical Cyber Social Computing: An Early 21st Century Approach to Computing for Human Experience. In International Conference on Web Intelligence, Mining and Semantics (WIMS '13). Madrid, Spain; 2013.  (1.53 MB)
Pramod Anantharam, Krishnaprasad Thirunarayan, Amit Sheth. Traffic Analytics using Probabilistic Graphical Models Enhanced with Knowledge Bases. In 2nd International Workshop on Analytics for Cyber-Physical Systems (ACS-2013) at SIAM International Conference on Data Mining (SDM 2013). Austin, Texas; 2013.  (1.45 MB)
traditional cluster validation techniques based on geometric shapes and density distributions are not appropriate for categorical data. In this paper
Ling Liu, Keke Chen. Best K: the Critical Clustering Structures in Categorical Data. 2008 ;.  (0 bytes)
Tractable Reasoning with Ontologies
Gary Berg-Cross, Isabel Cruz, Mike Dean, Timothy Finin, Pascal Hitzler, Hook Hua, Mark Gahegan, Krzysztof Janowicz, Naicong Li, Philip Murphy, Bryce Nordgren, Leo Obrst, Mark Schildhauer, Amit Sheth, Krishna Sinha, Anne Thessen, Nancy Wiegand, Ilya Zaslavsky. Semantics and Ontologies for EarthCube. In: Krzysztof Janowicz, Carsten Keßler, Tomi Kauppinen, Dave Kolas, Simon Scheider. Workshop on GIScience in the Big Data Age, in conjunction with the 7th International Conference on Geographic Information Science 2012 (GIScience 2012). Columbus, OH; 2012. p. 11-16.  (62.78 KB)
tractability
Markus Krotzsch, Frederick Maier, Adila Alfa Krisnadhi, Pascal Hitzler. A Better Uncle For OWL - Nominal Schemas for Integrating Rules and Ontologies. In International World Wide Web Conference (WWW2011). New York: Proceedings of the 20th International World Wide Web Conference (WWW2011); 2011.  (406.28 KB)
Topic modeling
Soon Jye Kho, Yalamanchili HBindu, Raymer ML, Amit Sheth. A Novel Approach for Classifying Gene Expression Data using Topic Modeling. In 8th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. Boston, MA: ACM; 2017.  (754.03 KB)
topic Indexing
Pablo Mendes. Adaptive Semantic Annotation of Entity and Concept Mentions in Text. Department of Engineering and Computer Science . [Dayton]: Wright State University; 2013.  (1.81 MB)
Time-Space Variant
Utkarshani Jaimini, V. Panchal. Swarm Intelligence computational paradigm. 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA). Bangalore, India: IEEE; 2013. p. 1 - 8.
Time-Space Invariant
Utkarshani Jaimini, V. Panchal. Swarm Intelligence computational paradigm. 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA). Bangalore, India: IEEE; 2013. p. 1 - 8.
time series
Pramod Anantharam, Krishnaprasad Thirunarayan, Surendra Marupudi, Amit Sheth, Tanvi Banerjee. Understanding City Traffic Dynamics Utilizing Sensor and Textual Observations. In 30th AAAI Conference on Artificial Intelligence (AAAI-16). Phoenix, Arizona; 2016.  (2.05 MB) (5.96 MB)
three-level fuzzy inference
Tanvi Banerjee, James Keller, Marjorie Skubie. Building a framework for recognition of activities of daily living from depth images using fuzzy logic. 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Beijing, China: IEEE; 2014. p. 540 - 547.
three-layered FIS model
Tanvi Banerjee, James Keller, Marjorie Skubie. Building a framework for recognition of activities of daily living from depth images using fuzzy logic. 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Beijing, China: IEEE; 2014. p. 540 - 547.
those articles selected by the Surgical Oncology Society. <br /><b>Results</b>: Our results showed that CCPY outperforms CC and JIF
Ling Liu, Keke Chen. Document Clustering and Ranking System for Exploring MEDLINE Citations. 2007 ;.  (0 bytes)
this study developed an approach that retrieved and organized MEDLINE citations into different topical groups and prioritized important citations in each group. <br /> <b>Design</b>: A text mining system framework for automatic document clustering and ra
Ling Liu, Keke Chen. Document Clustering and Ranking System for Exploring MEDLINE Citations. 2007 ;.  (0 bytes)
there is an astounding growth in the amount of data produced and made available through the cyberspace. Efficient and high quality clustering of large datasets continues to be one of the most important problems in largescale data analysis. A commonly use
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
The problem of determining the optimal number of clusters is important but mysterious in cluster analysis. In this paper
Hua Yan, Keke Chen, Ling Liu. Determining the Best K for Clustering Transactional Datasets: A Coverage Density-based Approach. 2008 ;.  (536 KB)
The Internet of Things
Charu Aggarwal, Naveen Ashish, Amit Sheth. The Internet of Things: A Survey from the Data-Centric Perspective. In: Charu Aggarwal. Managing and Mining Sensor Data. New York: Springer US; 2012. p. 383-428.
The Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition (DSM-5)
Amanuel Alambo, Manas Gaur, Usha Lokala, Ugur Kursuncu, Thirunarayam K, Amelie Gyrard, Randall Hand, Jyotishman Pathak, Amit Sheth. Question Answering for Suicide Risk Assessment using Reddit. In 13th IEEE International Conference on Semantic Computing. Newport Beach, California: IEEE; 2019.  (553.39 KB)
The demand on cluster analysis for categorical data continues to grow over the last decade. A well-known problem in categorical clustering is to determine the best K number of clusters. Although several categorical clustering algorithms have been develope
Ling Liu, Keke Chen. Best K: the Critical Clustering Structures in Categorical Data. 2008 ;.  (0 bytes)
The authors propose that an organic workflow-process technology will power the evolution of information system architectures. The authors outline three likely stages of architectural evolution in the context of a networked economy and discuss critical gap
Amit Sheth, Wil Van Der Aalst, Ismailcem Budak Arpinar. Processes Driving the Networked Economy. IEEE Concurrency. 1999 ;.  (691.75 KB)
textual data
Pramod Anantharam, Krishnaprasad Thirunarayan, Surendra Marupudi, Amit Sheth, Tanvi Banerjee. Understanding City Traffic Dynamics Utilizing Sensor and Textual Observations. In 30th AAAI Conference on Artificial Intelligence (AAAI-16). Phoenix, Arizona; 2016.  (2.05 MB) (5.96 MB)
Text-Mining
Swapnil Soni. Domain-specific Document Retrieval Framework on Near Real-time Social Health Data. Department of Computer Science and Engineering. [Dayton]: Wright State University; 2015. p. 63.  (649.25 KB)
text mining
Ashutosh Jadhav, Swapnil Soni, Amit Sheth. Social Health Signals. In International Semantic Web Conference 2015 (ISWC 2015). Bethlehem, Pennsylvania; 2015.  (183.28 KB)
Delroy Cameron, Pablo Mendes, Amit Sheth, Krishnaprasad Thirunarayan, Ramakanth Kavuluru, Olivier Bodenreider. Semantic Predications for Complex Information Needs in Biomedical Literature. 2011 IEEE International Conference on Bioinformatics and Biomedicine. Atlanta, GA: IEEE; 2011.
Cartic Ramakrishnan, Meenakshi Nagarajan, Amit Sheth. Text Analytics for Semantic Computing - the good, the bad and the ugly. International Conference on Semantic Computing, 2008; 2008.  (12.09 MB)
Ramakanth Kavuluru, Christopher Thomas, Amit Sheth, Victor Chan, Wenbo Wang, Gary Alan Smith. An Up-to-date Knowledge-Based Literature Search and Exploration Framework for Focused Bioscience Domains. In IHI 2012- 2nd ACM SIGHIT International Health Informatics Symposium. Miami Florida; 2012.  (1.3 MB)
Delroy Cameron, Ramakanth Kavuluru, Olivier Bodenreider, Pablo Mendes, Amit Sheth, Krishnaprasad Thirunarayan. Semantic Predications for Complex Information Needs in Biomedical Literature. In 5th International Conference on Bioinformatics and Biomedicine (BIBM2011). Atlanta GA: 2011 IEEE International Conference on Bioinformatics and Biomedicine; 2011.  (471.3 KB)
Cartic Ramakrishnan. Extracting, Representing and Mining Semantic Metadata from Text: Facilitating Knowledge Discovery in Biomedicine. 2008.  (39.68 MB)
Text Analytics
Amit Sheth, M. Fisher. Semantic Enterprise Content Management. In 2004.  (381.38 KB)
Ashutosh Jadhav. Knowledge-driven Search Intent Mining. Department of Computer Science & Engineering. [Dayton]: Wright State University; 2016. p. 180.  (11.11 MB)
Tensorflow
Amit Sheth, Thirunarayan Krishnaprasad, Michael R. Partin. Knowledge-empowered real-time event-centric situational analysis. NSF I/UCRC, Center for Surveillance Research Advisory Board meeting, August 7th, 2018; 2018.  (1.61 MB)
temporal selection
Matthew Perry, Prateek Jain, Amit Sheth. SPARQL-ST: Extending SPARQL to Support Spatiotemporal Queries. In Geospatial Semantics and the Semantic Web. New York: Springer; 2011. p. 61-86.  (518.48 KB)

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