An analog implementation of a deep machine-learning system for efficient feature extraction
is presented in this work. It features online unsupervised trainability and non-volatile floating …

Study of this paper describes the incremental behaviours of partitioning based K-means
clustering. This incremental clustering is designed using the cluster's metadata captured …

Abstract Recently, advances in Information Technologies (social networks, mobile
applications, Internet of Things, etc.) generate a deluge of digital data; but to convert these …

Current obstacles in the study of social media marketing include dealing with massive data
and real-time updates have motivated to contribute solutions that can be adopted for viral …

US PATENT DOCUMENTS 5,179,643 A 1/1993 Homma et al. 5,388,259 A 2f1995
Fleischman et al. 5,832,182 A 11/1998 Zhang et al. 6,026,398 A 2/2000 Brown et al …

In dynamic information environments such as the web, the amount of information is rapidly
increasing. Thus, the need to organize such information in an efficient manner is more …

RSNRAE Freauency counts matches associated with Strings occurring in records. The
method includes processing records to determine a set of string representations that …

The adoption of Service Oriented Architecture (SOA) and semantic Web technologies in the
Internet of Things (IoT) enables to enhance the interoperability of devices by abstracting …

In this paper, we present a novel strategy for evolving prototype based clusters that uses a
weighting scheme to “progressively forget” old samples. The rate of forgetfulness can be …

Inspired by the clustering mechanism of human cognitive development, this paper proposes
a density-based evolutionary clustering algorithm based on incremental data (DBEC). The …