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 domain, making the process of searching this information easier.

1. www.postersession.com
www.postersession.com
WASOTA
What are the states of the art?
C. Baron, D. Esteves, T. Soru, D. Moussallem, A. Valdestilhas and E. Marx
University of Leipzig - AKSW Research Group
Introduction
~2k%
Nr. publications /year
LNCS statistics - 1981-2005
http://www.springer.com/computer/lncs?SGWID=0-164-2-73659-0
Problem
Related Work #WASOTA
Advantages Features
http://wasota.aksw.org/http://mex.aksw.org/
How to find state of the art information about given domain?
1. Is there a recent survey paper published?
2. Check proceedings manually for recent papers…?
3. Google “(what are the) state(s) of the art for {d}”
Drawbacks
1. (sometimes) It’s (very) time consuming
2. It may leads to an incomplete investigation (search engines)
How much time (avg) do you need to (properly) answer the question:
“What are the states of the art for {d}?”
● RunMyCode
○ http://www.runmycode.org/
● CodaLab
○ http://codalab.org/
1. Missing straightforward way to answer the question
2. No vocabulary-based
3. More focused on keeping track of scientific workflows
● myExperiment
○ http://www.myexperiment.org
● OpenML
○ http://www.openml.org/
#interoperable #metadata #provenance
An online metadata repository
1. For readily ranking your outcomes
2. For easily sharing your best configurations
3. For readily comparing your experiment
4. For benchmark systems
5. For making your life easier...
537 experiments
25.550 executions
2.452.800
parameters/outcomes (values)
1 Master thesis
may generate...
1) Web Interface
a) Searching for (state of the art) experiments
b) Publishing new experiments
c) Consuming RDF metadata
● Public API
● SPARQL endpoint