Presently, an amount of publications in Machine Learning and Data Mining contexts are contributing to the improvement of algorithms and methods in their respective fields. However, with regard to publication and sharing of scientific experiment achievements, we still face problems on searching and ranking these methods. Scouring the Internet to search state-of-the-art information about specific contexts, such as Named Entity Recognition (NER), is often a time-consuming task. Besides, this process can lead to an incomplete investigation, either because search engines may return incomplete information or keywords may not be properly defined. To bridge this gap, we present WASOTA, a web portal specifically designed to share and readily present metadata about the state of the art on a specific domains, making the process of searching this information easier.
%0 Conference Paper
%1 wasota2016
%A Neto, Ciro Baron
%A Esteves, Diego
%A Soru, Tommaso
%A Moussallem, Diego
%A Valdestilhas, Andre
%A Marx, Edgard
%B 12th International Conference on Semantic Systems (SEMANTiCS 2016), 12-15 September 2016, Leipzig, Germany (Posters & Demos)
%D 2016
%K 2016 aksw baron ciro esteves group_aksw marx mex mole moussallem simba soru valdestilhas
%T WASOTA: What are the states of the art?
%U http://wasota.aksw.org/#/home
%X Presently, an amount of publications in Machine Learning and Data Mining contexts are contributing to the improvement of algorithms and methods in their respective fields. However, with regard to publication and sharing of scientific experiment achievements, we still face problems on searching and ranking these methods. Scouring the Internet to search state-of-the-art information about specific contexts, such as Named Entity Recognition (NER), is often a time-consuming task. Besides, this process can lead to an incomplete investigation, either because search engines may return incomplete information or keywords may not be properly defined. To bridge this gap, we present WASOTA, a web portal specifically designed to share and readily present metadata about the state of the art on a specific domains, making the process of searching this information easier.
@inproceedings{wasota2016,
abstract = {Presently, an amount of publications in Machine Learning and Data Mining contexts are contributing to the improvement of algorithms and methods in their respective fields. However, with regard to publication and sharing of scientific experiment achievements, we still face problems on searching and ranking these methods. Scouring the Internet to search state-of-the-art information about specific contexts, such as Named Entity Recognition (NER), is often a time-consuming task. Besides, this process can lead to an incomplete investigation, either because search engines may return incomplete information or keywords may not be properly defined. To bridge this gap, we present WASOTA, a web portal specifically designed to share and readily present metadata about the state of the art on a specific domains, making the process of searching this information easier.},
added-at = {2024-06-18T09:45:25.000+0200},
author = {Neto, Ciro Baron and Esteves, Diego and Soru, Tommaso and Moussallem, Diego and Valdestilhas, Andre and Marx, Edgard},
biburl = {https://www.bibsonomy.org/bibtex/26a88644dce8acba744c7b9c586b5e1d5/aksw},
booktitle = {12th International Conference on Semantic Systems (SEMANTiCS 2016), 12-15 September 2016, Leipzig, Germany (Posters \& Demos)},
interhash = {7873582c6f84f151436329b615860337},
intrahash = {6a88644dce8acba744c7b9c586b5e1d5},
keywords = {2016 aksw baron ciro esteves group_aksw marx mex mole moussallem simba soru valdestilhas},
timestamp = {2024-06-18T09:45:25.000+0200},
title = {WASOTA: What are the states of the art?},
url = {http://wasota.aksw.org/#/home},
year = 2016
}