Approximate Web Database Search Based on Euclidean Distance Measurement
Sarawuth Sonnum, Sittichai Ano, Nittaya Kerdprasop · 2011
Abstract—Although most methods for data finding and object searching are effective, they have one major weak point. That is they tend to eliminate a large number of objects whose properties do not sufficiently match those identified by the methods. As a result, a large number of possible choices are unnecessary eliminated. To fill this gap, we develop a new method that can include as many possibly relevant objects as possible to facilitate approximate search through the Web database. This method, based on the Euclidean distance measurement, finds objects with similar or closely properties and then identifies objects that share closest properties. This paper demonstrates how the method works by programming with the Erlang language to implement a Web-based search on mobile-phone application using Euclidean distance computation. Index Terms—Similarity search, Euclidian distance measurement, Web database, Erlang programming