Business Opportunity Detection in the Big Data

Lyes Limam, Jean Lecouffe, Stéphane Chau

Abstract

Modern enterprise information systems are characterized by large amounts of data issued from various internal and external business applications, often stored and archived in different supports (databases, documents, etc. The nature of this data (voluminous, unstructured, heterogeneous, inconsistent, etc.) makes them difficult to use for analysis. In fact, it is typically an issue of big data analytics. The main objective of our research project is to design a solution to detect opportunities (projects, new markets, skills, tenders, etc.) in the continually growing data, while adapting to its constraints. The extracted information should help users to take proactive actions to improve their business (e.g., identify a consultant skill that can be aligned with a given tender). In this project we are interested in text data. There are two main reasons. The first reason is that text data is the most difficult to analyse by humans, especially when it is voluminous. The second reason is that we are convinced that valuable information is usually textual. Therefore, we define six research axes: • Intelligent Information Sensing • Text Mining • Knowledge Representation (semantics) • Querying the knowledge • Results Interpretation • Self-learning.

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Paper Citation


in Harvard Style

Limam L., Lecouffe J. and Chau S. (2016). Business Opportunity Detection in the Big Data . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-187-8, pages 250-254. DOI: 10.5220/0005917402500254


in Bibtex Style

@conference{iceis16,
author={Lyes Limam and Jean Lecouffe and Stéphane Chau},
title={Business Opportunity Detection in the Big Data},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2016},
pages={250-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005917402500254},
isbn={978-989-758-187-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Business Opportunity Detection in the Big Data
SN - 978-989-758-187-8
AU - Limam L.
AU - Lecouffe J.
AU - Chau S.
PY - 2016
SP - 250
EP - 254
DO - 10.5220/0005917402500254