Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Given a database with missing or uncertain content, our goal is to correct and fill the database by extracting specific information from a large corpus such as the Web, and to d...
We investigate indexing techniques for sequence data, crucial in a wide variety of applications, where efficient, scalable, and versatile search algorithms are required. Recent res...
Mihail Halachev, Nematollaah Shiri, Anand Thamildu...
We have developed a multiple genome alignment algorithm by using a sequence clustering algorithm to combine local pairwise genome sequence matches produced by pairwise genome align...
Artificial Neural Networks (ANNs) have proved both a popular and powerful technique for pattern recognition tasks in a number of problem domains. However, the adoption of ANNs in ...