Search results for "Data Science"

On Big Data: How should we make sense of them?

2020

The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven method. In this piece, I critically scrutinize two key claims that are usually associated with this approach, namely, the fact that data speak for themselves, deflating the role of theories and models, and the primacy of correlation over causation. In so doing, I will also refer to a recent case history of data mining projects in the field of biomedicine, i.e. EXPOsOMICS. My intention is both to acknow…

Mining customer requirements from online reviews: A product improvement perspective

2016

We propose a filtering model to predict helpfulness of reviews for product design.We provide a way to use the KANO model based on online reviews.We explore how to obtain insights from Big Data through knowledge-based view. Big data commerce has become an e-commerce trend. Learning how to extract valuable and real time insights from big data to drive smarter and more profitable business decisions is a main task of big data commerce. Using online reviews as an example, manufacturers have come to value how to select helpful online reviews and what can be learned from online reviews for new product development. In this research, we first proposed an automatic filtering model to predict the help…

Development of Applications for Interactive and Reproducible Research: a Case Study

2016

For a proper understanding of the organization and regulation of gene expression, the computational analysis is an essential component of the scientific workflow, and this is particularly true in the fields of biostatistics and bioinformatics. Interactivity and reproducibility are two highly relevant features to consider when adopting or designing a tool, and often they can not be provided simultaneously.In this work, we address the issue of developing a framework that can provide interactive analysis, in order to allow experimentalists to fully exploit advanced software tools, as well as reproducibility as an internal validation of the analysis steps, by providing the underlying code and d…

Gaming Bot Detection: A Systematic Literature Review

2018

In online games, some players employ programs (bots) that allow them to bypass game routines and effortlessly gain virtual resources. This practice leads to negative effects, such as reduced revenue for the game development companies and unfair treatment for ordinary players. Bot detection methods act as a counter measure for such players. This paper presents a systematic literature review of bot detection in online games. We mainly focus on games that allow resource accumulation for players between game sessions. For this, we summarize the existing literature, list categories of games ignored by the scientific community, review publicly available datasets, present the taxonomy of detection…

A Biologically Inspired Representation of the Intelligence of a University Campus

2016

Abstract Intelligence or smartness in an urban environment implies several factors directed to improve quality of life and efficiency. It is important to note that in this context the inclusion of citizens and their devices is a key factor for reaching smartness. Data from mobile devices are increasingly used in everyday activities and have to be considered a useful means for handling and analyzing knowledge and communications. This paper shows how to represent important data when dealing with smartness by creating an analogy between the representation of human brain areas, activated when specific tasks are performed, and groups of students when behaviors or needs arise. The brain traffic c…

Investigating Centrality Measures in Social Networks with Community Structure

2021

Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majority of classical centrality measures are agnostic of the community structure characterizing many social networks. Recent works have developed community-aware centrality measures that exploit features of the community structure information encountered in most real-world complex networks. In this paper, we investigate the interactions between 5 popular classical centrality measures and 5 community-aware centrality measures using 8 real-world online networks. Correlation as well as similarity measures between both t…

Managing Multi-center Flow Cytometry Data for Immune Monitoring.

2014

With the recent results of promising cancer vaccines and immunotherapy 1 – 5 , immune monitoring has become increasingly relevant for measuring treatment-induced effects on T cells, and an essential tool for shedding light on the mechanisms responsible for a successful treatment. Flow cytometry is the canonical multi-parameter assay for the fine characterization of single cells in solution, and is ubiquitously used in pre-clinical tumor immunology and in cancer immunotherapy trials. Current state-of-the-art polychromatic flow cytometry involves multi-step, multi-reagent assays followed by sample acquisition on sophisticated instruments capable of capturing up to 20 parameters per cell at a…

Patient prioritisation in HCC treatment: All (good) things come in threes.

2017

Analysis of health communication texts: UK press coverage of debates about assisted dying

2015

Conventionally, social researchers analyse media messages by reading text and coding it. This is time consuming and restricts many studies to small samples. Nowadays very large amounts of text are available in electronic form, offering potential insights into the health messages they contain, but which appear daunting to the analyst with limited resources using conventional methods. I explain and illustrate methods for the computer-assisted analysis of media texts, using specialised software (Wordsmith Tools and Wordstat). These allow the analyst to provide a statistical overview of the key features of texts, to compare them (looking at change over time, for example) and to select illustrat…

Crowd Models for Emergency Evacuation: A Review Targeting Human-Centered Sensing

2013

Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from various fields. Better understanding of this class of crowd behavior opens up for improving evacuation policies and smarter design of buildings, increasing safety. Recently, a new class of disruptive technology has appeared: Human-centered sensing which allows crowd behavior to be monitored in real-time, and provides the basis for real-time crowd control. The question then becomes: to what degree can previous crowd models incorporate this development, and what areas need further research? In this paper, we provide a survey that describes some widely used crowd models and discuss their advantages a…