Abstract
In informal data sharing environments, misspellings
cause problems for data indexing and retrieval. This is even
more pronounced in mobile environments, in which devices
with limited input devices are used. In a mobile environment,
similarity search algorithms for finding misspelled data need to
account for limited CPU and bandwidth. This demo shows P2P
fast similarity search (P2PFastSS) running on mobile phones and
laptops that is tailored to uncertain data entry and uses available
resources efficiently. In this demo, users publish and search for
textual content containing misspellings without relying on query
logging, as done by Google, and with a minimum distributed
indexing infrastructure. Similarity search is supported by using
the concept of deletion neighborhood to evaluate the edit distance
metric of string similarity.
Bocek, T