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  Browse All Reviews > Information Systems (H) > Database Management (H.2) > Database Applications (H.2.8) > Data Mining (H.2.8...)  
 
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  1-10 of 584 Reviews about "Data Mining (H.2.8...)": Date Reviewed
  Next and next new POI recommendation via latent behavior pattern inference
Li X., Han D., He J., Liao L., Wang M.  ACM Transactions on Information Systems 37(4): 1-28, 2019. Type: Article

The objective of a recommender system is to suggest relevant items or preferences to users. Similar to other recommendations, for example, for products, movies or books, point-of-interest (POI) recommendations can help travelers and tourists find ...

Jan 25 2022
  Integrating runtime data with development data to monitor external quality: challenges from practice
Aghabayli A., Pfahl D., Martínez-Fernández S., Trendowicz A.  SQUADE 2019 (Proceedings of the 2nd ACM SIGSOFT International Workshop on Software Qualities and Their Dependencies, Tallinn, Estonia,  Aug 26, 2019) 20-26, 2019. Type: Proceedings

Aghabayli et al. describe a case study that integrates “software runtime data with development data in order to understand and predict” whether or not problems that occur “during the use of the software (external quality)” ...

Jan 18 2022
  Mining imperfect data: with examples in R and Python (2nd ed.)
Pearson R.,  SIAM, Philadelphia, PA, 2020. 184 pp. Type: Book (978-1-611976-26-7)

Data analysis--including both data mining and machine learning--has made a lot of progress in the past decade. Both the R and Python programming languages have been used to analyze data. The Achilles’ heel in this task is the handl...

Nov 19 2021
  Process mining in action: principles, use cases and outlook
Reinkemeyer L.,  Springer International Publishing, New York, NY, 2020. 229 pp. Type: Book (978-3-030401-71-9)

Process mining in action is an edited collection of papers on process mining. The papers are divided into three parts. The book should interest academics, executives, and professionals with an interest in the topic....

Oct 13 2021
  Multidimensional mining of massive text data
Zhang C., Shu K.,  Morgan&Claypool Publishers, 2019. 198 pp. Type: Book (978-1-681735-19-1)

This edited book on mining massive text data stands out by putting the concept of a “cube” center stage: a multi-dimensional space in which massive text data analysis should take place. As such, it offers discussions at the crossroads ...

Jul 13 2021
   High-utility pattern mining: theory, algorithms and applications
Fournier-Viger P., Lin J., Nkambou R., Vo B., Tseng V.,  Springer International Publishing, New York, NY, 2019. 337 pp. Type: Book (978-3-030049-20-1)

Finding frequently occurring patterns of transactions in transactional databases, such as products that customers often purchase together, can be extremely useful in identifying bestselling products and co-promoting products. However, “frequ...

Jun 24 2021
  Modern data mining algorithms in C++ and CUDA C
Masters T.,  Apress, New York, NY, 2020. 228 pp. Type: Book (978-1-484259-87-0)

In his earlier book from 2018, Data mining algorithms in C++ [1], the author indicated that a “volume 2 will appear some day.” This is it. It builds on the techniques and tools of the earlier book and follows a similar style of ...

May 5 2021
  Aspect aware learning for aspect category sentiment analysis
Zhu P., Chen Z., Zheng H., Qian T.  ACM Transactions on Knowledge Discovery from Data 13(6): 1-21, 2019. Type: Article

Do you like (or dislike) “fruit flies like a banana,” but not “time flies like an arrow”? How should humans and computerized systems accurately distinguish between predefined and undefined categories of words used in senten...

Apr 6 2021
  Evolutionary decision trees in large-scale data mining
Kretowski M.,  Springer International Publishing, New York, NY, 2019. 180 pp. Type: Book (978-3-030218-50-8)

Decision trees are valuable counterparts to neural networks in data mining--the book confirms this statement. Evolutionary decision trees in large-scale data mining is a didactic introduction to, and overview of, the almost two-decade-...

Feb 15 2021
  Learning from sets of items in recommender systems
Sharma M., Harper F., Karypis G.  ACM Transactions on Interactive Intelligent Systems 9(4): 1-26, 2019. Type: Article

Recommender systems are sets of computer algorithms or methods, implemented to provide suggestions or recommendations of relevant items to users. With the intensification of web services, from e-commerce to online advertising, recommender systems ...

Jan 25 2021
 
 
 
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