@conference {ElAkrouchi2021,
	title = {Review on adopting concept extraction in weak signals detection in competitive intelligence},
	booktitle = {ACM International Conference Proceeding Series},
	year = {2021},
	note = {cited By 0},
	abstract = {The dynamic nature of competition in the business environment makes a company{\textquoteright}s ability to secure future change more critical to its survival. Consequently, efficient exploitation of valuable intel is globally acknowledged as an essential foundation of competitive advantage, leading to Competitive Intelligence. Besides, one of the crucial keys to successful competitive information securing is studying the future. Thus, predicting what may happen in the uncertain future is a leading-edge technology leading to an extensive need for foresight analysis. Foresight study uses various methods to recognize future developments and make plans that anticipate possible future changes. One of the leading techniques used in foresight is detecting and understanding Weak Signals. But knowing the nature of these signals, automatically scanning them is still considered a difficult task. For this, we examine the Concept Extraction technique as a main step to detect weak signals from documents automatically. In this paper, we will explain the concept extraction methods used so far, and we present in detail all the main methods and approaches and their application in detecting weak signals. {\textcopyright} 2021 Association for Computing Machinery.},
	keywords = {Business environments, Competition, Competitive advantage, Competitive intelligence, Concept extraction, Data mining, Dynamic nature, Extraction, Leading edge technology, Possible futures, Signal detection, Topic Modeling, Weak signal detection, Weak signals},
	doi = {10.1145/3485557.3485560},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121505750\&doi=10.1145\%2f3485557.3485560\&partnerID=40\&md5=01161f382ecb38a8faf2883a2bc37003},
	author = {El Akrouchi, M. and Benbrahim, H. and Kassou, I.}
}
