I am really excited with my invitation to be speaker at the 1st International Congress of Systems Engineering and Computation within Universidad Peruana de Ciencias Aplicadas. I was invited by Prof. Dr. Carlos Raymundo through my colleague Prof. Hernán Sagastegui Chigne. I will be the lecturer on Wednesday and Thursday of the next week (7th and 8th of November) and the talk will be about “Researching in Semantic Web Technologies”, you can see the full schedule here.
My intention is to provide a good introduction to the Semantic Web and Linked Data initiatives apart from providing an in-depth review of existing works. I would also like take part of the time to organize a think-tank session in which the audience can collaborate giving opinions about specific open issues and make a discussion to launch some actions such as a hackathon or similar in next weeks but it is just a thought…
Last Tuesday I was interviewed by RPA about the participation of the WESO Research Group in this project. It was my first apparition in the radio and I believe the result was pretty good. You can listen the audio here. Moreover our head Labra was interviewed in other media such as newspaper and other radios and these contents can be accesed via the official communication portal at the University of Oviedo.
On the other hand and following with the Webindex it is my intention to provide data and methods to calculate values using R. I think this is a real way to open and encourage the reutilization of data, at least in statistics.
Finally, I am also involved in my distributed reasoner and preparing some proposals to mix computational linguistics, computational social choice theory, etc. I will update the blog with my outcomes. I also started this week to teach “Software Design” with my colleagues Benjamín López, César Acebal and Raúl Izquierdo, I am very excited with this topic because I love design patterns, software architectures, etc. I hope to do my best!
Keep in touch!
During June and July, I have participated in the creation of a “Reading List” for the Emerald Publishing Group in collaboration with Prof. Patricia Ordoñez de Pablos. The objective of this task is to create a list of relevant publications for a target journal or topic, in this case the main topic was “Knowledge management and organizational learning in the workplace” and it was an interesting research activity because I could extend my background in these areas reading some papers.
I have to say I consider the creation of a reading list as something very relevant in order to help authors to focus on a journal’s topic or to ease the access to the most adequated references. Besides the methodology followed by Emerald is very professional and they are aware of any change in your selected papers and can help you in any step of the process. Finally, could this practice considered as “crowd-reading-list-assistance”? Yes, it could! “Crowds and Power” is changing the way you perform your work!
With regards to the list, it is available at this link, if you any comment or doubt, please do not hesitate to contact me at anytime,
I just finished an introduction to social choice theory as the formal study of mechanisms for collective decision making. The article presents all the required background to start in this discipline. I reached this paper through the website of UVA and I consider that the concepts presented in the paper could be applied to a lot of use cases, for instance matchmaking of organizations and public contracts or maybe to mediation in Linked Data. Now I am also very interested in works related to “The Wisdom of Crowds” and, on the best of my knowledge, this kind of research and tools can help to validate the results generated by a crowd. There are also other relevant concepts and definitions I did not know (in this context) such as: dictatorship, liberalism, positive responsiveness or manipulation among others . Furthermore, author presents somo logic concepts that have emerged to support social choice theory with a formal syntax and semantics. Thus there are approches based on FOL, HOL and others trying to formalize the underlying concepts of this theory. I would like to highlight the “Doctrinal Paradox” that makes me feel uncomfortable with existing methods of judging being that using a “premise-based procedure” or a “conclusion-based procedure” to get a decision, the final result can change although both procedures are correct!
If you are interested in this kind of work or research, you can follow the Autumm Course about Computational Social Choice teached by Ulle Endriss as part of a Logics master.
Keep in touch!
In February I made an application to the HPC-Europa2 Transnational Access programme and I finally got a grant that enabled the opportunity of using the SARA infrastructure to test some algorithms. Thanks to the Professor Maarten de Rijke I could select the University of Amsterdam as host so…Now I am here for 6 weeks at the University of Amsterdam in the Institute for Informatics and more specifically in the Intelligent Systems Lab. I am very excited with this opportunity and I will do my best to get a good version of our reasoning prototype. Besides I would like to start a fruitful collaboration between people in this lab and our research group through publications, projects or whatever.
I would also like to thank all the administrative staff of UVA their time and consideration. When I arrived, last Thursday, in 15 minutes I had a visiting card, a desktop and WI-FI connection and a great sight…
I will keep you informed!
Finally, I finished the reviewed of this excellent book about mining massive datasets. The sheer mass of data on the web is continuosly growing, a lot of new methods, algorithms and tools are emerging in order to deal with this big amount of data but in some cases without providing a formal model to process the information. In this book, authors present a compilation of the most used algorithms (and its formal definition) to build recommendation systems based on data mining techniques.
I strongly recommend the reading of this book because it focuses on data mining of very large amounts of data that does not fit in main memory. Currently this situation can be applied to the management of digital libraries, analysis of social networks, bioinformatics, etc. in which the processing of large datasets is necessary. The main topics can be shown in the next figures but according to authors you will learn the next concepts:
- Distributed file systems and map/reduce approaches a a tool for creating parallel algorithms
- Methods to estimate and calculate similarity search
- Processing of data streams with specializaed algorithms
- Technology of existing search engines: page rank, link-spam detection, etc.
- Frequent-itemset mining
- Algorithms for clustering very large and high-dimensional datasets
- Two main applications of these techniques: advertising and recommendation systems
Nevertheless, I miss a section about real time processing of large amounts data instead of streaming techniques.