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  Browse All Reviews > Information Systems (H) > Database Management (H.2) > Logical Design (H.2.1) > Data Models (H.2.1...)  
  1-10 of 151 Reviews about "Data Models (H.2.1...)": Date Reviewed
   Bayesian synthesis of probabilistic programs for automatic data modeling
Saad F., Cusumano-Towner M., Schaechtle U., Rinard M., Mansinghka V. Proceedings of the ACM on Programming Languages 3(POPL): 1-32, 2019.  Type: Article

Somewhat overshadowed by neural networks (NN) is another thread in machine learning: the Bayesian-based approach. Less data hungry, it also has the promise of being closer to explainable artificial intelligence (XAI), although it hasn&...

Jun 3 2020
  Analyzing sentiments in one go: a supervised joint topic modeling approach
Hai Z., Cong G., Chang K., Cheng P., Miao C. IEEE Transactions on Knowledge and Data Engineering 29(6): 1172-1185, 2017.  Type: Article

The so-called “crowd wisdom” phenomenon took on a whole new dimension with the advent of the web and the emergence of myriads of online product reviews written by both happy and (more often than not) angry customers...

Jan 17 2018
  Information-theoretic caching: sequential coding for computing
Wang C., Lim S., Gastpar M. IEEE Transactions on Information Theory 62(11): 6393-6406, 2016.  Type: Article

Streaming video sequences can be encoded in real time by applying a variable of some average rate of bits per symbol. Such a technique stores both the data sequence and the request sequence simultaneously for updated visual information...

Jun 21 2017
  Crowdsourced data management: a survey
Li G., Wang J., Zheng Y., Franklin M. IEEE Transactions on Knowledge and Data Engineering 28(9): 2296-2319, 2016.  Type: Article

Many data management and analytics tasks, notably entity resolution, sentiment analysis, and image recognition, cannot always be fulfilled through automated software processes alone, but also require the application of human cognition....

Apr 18 2017
  Dimensional enrichment of statistical linked open data
Varga J., Vaisman A., Romero O., Etcheverry L., Pedersen T., Thomsen C. Journal of Web Semantics 40(C): 22-51, 2016.  Type: Article

As with most consolidated analysis techniques, online analytical processing (OLAP) usually assumes a local data environment (for example, analysis within an organization) in which multidimensional datasets are modeled according to prop...

Feb 16 2017
  Querying graphs with data
Libkin L., Martens W., Vrgoč D. Journal of the ACM 63(2): 1-53, 2016.  Type: Article

Various approaches to querying so-called graphs with data are described very comprehensively in this paper. In principle, this category of graphs is called (labeled) property graphs in the graph database community. Concerning queries i...

Oct 25 2016
  Analytic queries over geospatial time-series data using distributed hash tables
Malensek M., Pallickara S., Pallickara S. IEEE Transactions on Knowledge and Data Engineering 28(6): 1408-1422, 2016.  Type: Article

This paper explores the advantages and complications of using a novel indexing scheme for managing big data and geospatial attributes. The indexing system is built with the goal of an optimal compromise among scalability, expressivenes...

Jul 21 2016
  Interactive data visualization: foundations, techniques, and applications (2nd ed.)
Ward M., Grinstein G., Keim D., A. K. Peters, Ltd., Natick, MA, 2015. 558 pp.  Type: Book (978-1-482257-37-3)

The explosion of data raises significant challenges to processing, analyzing, and giving meaning to a sustainable flow of information. This book is a great reference in the field of data visualization. The motivation given by the autho...

May 10 2016
  Who’s #1?: The science of rating and ranking
Langville A., Meyer C., Princeton University Press, Princeton, NJ, 2012. 272 pp.  Type: Book (978-0-691162-31-7)

The ranking/rating process is deeply embedded in human nature and our everyday lives. Whenever we need to make a decision that involves more than one alternative, such as buying a product, voting for a candidate, presenting a list of w...

Aug 13 2014
  Modeling techniques in predictive analytics: business problems and solutions with R
Miller T., Pearson Education, Upper Saddle River, NJ, 2013. 352 pp.  Type: Book (978-0-133412-93-2)

Predictive analysis and the recent industry trend toward big data have considerably increased the audience for textbooks related to analytics, modeling, and distributed data processing. This book is a timely newcomer to this growing li...

Jan 3 2014
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