17.6.11

Comment in New Scientist feature on Crowsourced SMS Spam filter

Jakob Aron from New Scientist interviewed me some time a go regarding the following paper:

Kuldeep Yadav, Ponnurangam Kumaraguru, Atul Goyal, Ashish Gupta, Vinayak Naik. SMSAssassin: Crowdsourcing Driven Mobile-based System for SMS Spam Filtering.
12th Workshop on Mobile Computing Systems and Applications (HotMobile 2011).

You can find my opinion at the feature: Crowdsourced software could stop SMS spam.

15.6.11

Buscando una herramienta para hacer mockups Web

Estoy buscando una herramienta para prototipar productos con GUI basada en Web. Estos son mis requisitos:

Necesario:

  • Standalone, no web-based
  • Version para Windows
  • Gratuito pero completamente funcional, no soporte a un solo proyecto
  • Desarrollo de mockups Web
  • Eventos activos (e.g. pulsar boton lleva a otra pantalla/pagina)

Deseable:

  • Generación de código (aunque sea vacio para el backend)
  • Visualización Web (se generan htmls que se pueden colgar)
  • Soporte para cambio de CSSs

Prescindible

  • Soporte para wireframes
  • Aplicaciones sobre Win/GTK/etc.
  • Soporte para desarrollo de graficos (que se puede cubrir con otras herramientas)

Algunas posibilidades que ya he revisado:

Me gustaría escuchar vuestra experiencia, sugerencias, etc. Por favor, comentad.

9.6.11

New dataset released: SMS Spam Collection v.1

New dataset released: SMS Spam Collection v.1

The SMS Spam Collection v.1 is a public set of SMS labeled messages that have been collected for mobile phone spam research. It has one dataset composed by 5,574 English, real and non-enconded messages, tagged according being legitimate (ham) or spam.

The collection is free for all purposes, and it is public available at: http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/

This corpus has been collected from free or free for research sources at the Internet including the Grumbletext Web site, the NUS SMS Corpus, Caroline Tag's PhD Thesis, and a smaller previous collection (SMS Spam Corpus v.0.1: http://www.esp.uem.es/jmgomez/smsspamcorpus/, available for historic comparison).

A comprehensive study of this corpus can be found in the following paper, which offers a number of statistics, studies and baseline results for several machine learning methods.

Almeida, T.A., Gómez Hidalgo, J.M., Yamakami, A. Contributions to the study of SMS Spam Filtering: New Collection and Results. Proceedings of the 2011 ACM Symposium on Document Engineering (ACM DOCENG'11), Mountain View, CA, USA, 2011. (Accepted)

2.6.11

Invitation to participate in a text visual analytics user study

Let me disseminate this user study participation request.

Daniela Oelke, David Spretke, Andreas Stoffel, and Daniel A. Keim need to evaluate their research in the domain of visual analytics for improving the readability of a text. They would like to invite you to participate in a small survey that can be found here:

http://www.surveymonkey.com/s/H6KCJ52

Your task will be to read twice through 5 sentences and rank them. Afterwards you are asked to state your reasons for ranking them the way you did. Completing the study should take no longer than 10-15 minutes. Your effort is really appreciated as it helps us to further improve their algorithms.

To know more about their algorithms, check e.g.: "Visual Analytics: Combining Automated Discovery with Interactive Visualizations".

Via the SIGIR list.