A Deep Dive into Deep Cluster

DextMP: deep dive into text for predicting moonlighting proteins

Motivation Moonlighting proteins (MPs) are an important class of proteins that perform more than one independent cellular function. MPs are gaining more attention in recent years as they are found to play important roles in various systems including disease developments. MPs also have a significant impact in computational function prediction and annotation in databases. Currently MPs are not la...

Dive deeper: Deep Semantics for Sentiment Analysis

This paper illustrates the use of deep semantic processing for sentiment analysis. Existing methods for sentiment analysis use supervised approaches which take into account all the subjective words and or phrases. Due to this, the fact that not all of these words and phrases actually contribute to the overall sentiment of the text is ignored. We propose an unsupervised rule-based approach using...

A Deep Dive into the LISP Cache and What ISPs Should Know about It

Due to scalability issues that the current Internet is facing, the research community has re-discovered the Locator/ID Split paradigm. As the name suggests, this paradigm is based on the idea of separating the identity from the location of end-systems, in order to increase the scalability of the Internet architecture. One of the most successful proposals, currently under discussion at the IETF,...

A deep dive into EC.02.03.05: maintaining fire equipment and building features.

A deep dive into location-based communities in social discovery networks

Location-based social discovery networks (LBSD) is an emerging category of location-based social networks (LBSN) that are specifically designed to enable users to discover and communicate with nearby people. In this paper, we present the first measurement study of the characteristics and evolution of location-based communities which are based on a social discovery network and geographic proximi...