Reputation Analysis towards Discovery

Raffaele Palmieri, Vincenzo Orabona, Nadia Cinque, Stefano Tangorra, Donato Cappetta

2017

Abstract

This work describes the development and the realization of an OSInt solution conducting a supplier risk assessment, focused on the evaluation of suppliers’ reputation starting from publicly available information. The main challenge is represented by the data processing phase that exploits NLP technologies to extract facts, events, and relations from unstructured sources, building the knowledge base for reputational analysis. Several measures have been adopted to provide a satisfactory user experience; however, further integrations are still needed to increase efficiency of the developed solution. Particularly, it is necessary to deepen and improve the analysis over the huge volume of data coming from open sources, enhancing the discovery of all possible relevant information influencing the reputation of the targeted entity.

Paper Citation

in Harvard Style

Palmieri R., Orabona V., Cinque N., Tangorra S. and Cappetta D. (2017). Reputation Analysis towards Discovery . In - KomIS, ISBN , pages 0-0. DOI: 10.5220/0006487303210330

in Bibtex Style

@conference{komis17,
author={Raffaele Palmieri and Vincenzo Orabona and Nadia Cinque and Stefano Tangorra and Donato Cappetta},
title={Reputation Analysis towards Discovery},
booktitle={ - KomIS,},
year={2017},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006487303210330},
isbn={},
}

in EndNote Style

TY - CONF
JO - - KomIS,
TI - Reputation Analysis towards Discovery
SN -
AU - Palmieri R.
AU - Orabona V.
AU - Cinque N.
AU - Tangorra S.
AU - Cappetta D.
PY - 2017
SP - 0
EP - 0
DO - 10.5220/0006487303210330