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Kapetanios, Epaminondas
Faculty of Science and Technology
London, United Kingdom
 
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Epaminondas Kapetanios has spent many years investigating ways to improve the tasks of interpreting, explaining, and understanding computational artifacts (for example, algorithms, data, knowledge) with a variety of user types and personas. Some notable results of this explorative journey have been the design and implementation of a metadata-driven visual query language, a human-computer interactive automaton and parser for predicting user query intent, and a language and model for adaptive ontologies.

His research culminated in prototypes applicable to a variety of disciplines and real-world projects, including the retrieval of scientific and statistical databases for ozone hole research over the Arctic, natural language-based querying and processing, as well as web-based decision trees as an e-consultation system in healthcare. Epaminondas has also applied web and text mining techniques for competitive business intelligence within the context of an initiative funded by Innovate UK.

Epaminondas is currently affiliated with the School of Physics, Engineering and Computer Science, at the University of Hertfordshire. His work focuses on responsible and trustworthy AI. Specifically, he is investigating human-oriented explainable and interpretable artificial intelligence (AI) and machine learning, such as natural language (conversational, dialogue) based systems and knowledge discovery from source code mining.

Epaminondas has been a reviewer for Computing Reviews since 2014.

 
 
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- 10 of 27 reviews

   
   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 discussion...

Jul 13 2021  
   ELSA: a multilingual document summarization algorithm based on frequent itemsets and latent semantic analysis
Cagliero L., Garza P., Baralis E. ACM Transactions on Information Systems 37(2): 1-33, 2019.  Type: Article, Reviews: (2 of 2)

“You shall know a word by the company it keeps” is perhaps the most famous quotation attributed to J. R. Firth [1]. Searching for ways to automate natural language understanding (NLU), statistical natural language p...

Nov 16 2020  
   Understand, manage, and prevent algorithmic bias: a guide for business users and data scientists
Baer T., Apress, New York, NY, 2019. 260 pp.  Type: Book (978-1-484248-84-3)

This is one of the most enlightening books about the hidden risks of applying machine learning techniques, and particularly algorithms, in decision making. The book unveils the many potential sources of algorithmic bias, raising seriou...

Aug 25 2020  
  Humans and machines at work: monitoring, surveillance and automation in contemporary capitalism
Moore P., Upchurch M., Whittaker X., Palgrave Macmillan, Cham, Switzerland, 2018. 260 pp.  Type: Book (978-3-319582-31-3)

The unprecedented pace of the so-called fourth industrial revolution, which is characterized by the fusion of technologies and automation with humans, thus forming new physical, digital, and biological spheres for cognitive and manual ...

Dec 12 2019  
   The seven tools of causal inference, with reflections on machine learning
Pearl J. Communications of the ACM 62(3): 54-60, 2019.  Type: Article, Reviews: (2 of 3)

This is one of the most influential and eye-opening articles I’ve read in the last two or three years. The author, an ACM Turing Award recipient, makes clear distinctions between machine learning (ML), artificial intelligence...

Jul 2 2019  
   Individual and collective graph mining: principles, algorithms, and applications
Koutra D., Faloutsos C., Morgan&Claypool Publishers, San Rafael, CA, 2018. 206 pp.  Type: Book (978-1-681730-39-4)

Having recently finished my course on web intelligence, with topics such as knowledge graphs, social network analysis, and web mining, as well as supervising a PhD candidate on graph-based querying and pattern matching for linked open ...

Feb 11 2019  
  Matrix algebra: theory, computations and applications in statistics (2nd ed.)
Gentle J., Springer International Publishing, New Yokr, NY, 2017. 648 pp.  Type: Book (978-3-319648-66-8), Reviews: (2 of 2)

Business and industry leaders are often faced with discussions about the future of artificial intelligence (AI), machine learning, and data science. Similarly, they often engage in complex problem solving, for example, computer vision ...

Nov 9 2018  
   Toward the robots of science fiction
Aaron D. Ames. YouTube, 00:49:33, published on Dec 7, 2017, Caltech, https://www.youtube.com/watch?v=ZL8ddCQFuXU. Type: Video

It was a pleasure to watch this presentation about the future of robotics, a hotly debated topic fueled by the controversy between robots defeating humans and robots augmenting and assisting humans, for example, prostheses and exoskele...

Sep 12 2018  
  Mining urban events from the tweet stream through a probabilistic mixture model
Capdevila J., Cerquides J., Torres J. Data Mining and Knowledge Discovery 32(3): 764-786, 2018.  Type: Article

If you are curious about how probabilistic models can be used to analyze tweets for local event detection, this paper is a good start....

Jul 5 2018  
   Cognitive approach to natural language processing
Sharp B., Sedes F., Lubaszewski W., ISTE Press - Elsevier, London, UK, 2017. 234 pp.  Type: Book (978-1-785482-53-3)

Did you ever ask yourself about the wonder of natural language processing (NLP) as an innate part of human civilization? Do you wish to unlock some of the secrets of natural language understanding in minds and machines alike? Do you wi...

Dec 15 2017  
 
 
 
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