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Abstract-Some professional e-mails contain knowledge about how actor face problem in order to realize projects. This type of knowledge is produced in cooperative activity. Representing project knowledge leads to structure link between coordination, cooperative decision-making and communication. The main objective of our work is to extract knowledge from daily work. So the main questions of our research are:• Can we extract knowledge from professional e-mails? • If so, which type of knowledge can be represented? • How to link this knowledge to project memory? We present in this paper our first work in this aim. Our hypothesis is tested on a software development application.

Part 1: Tools and Methods for Knowledge AcquisitionInternational audienceSome professional e-mails contain knowledge about how actor face problem in order to realize projects. This type of knowledge is produced in cooperative activity. Representing project knowledge leads to structure link between coordination, cooperative decision-making and communication. The main objective of our work is to extract knowledge from daily work. So the main questions of our research are:

Even if immaterial capital represents an increasingly important part of the value of our enterprises, it's not always possible to store, trace or capture knowledge and expertise, for instance in middle sized projects. Email it still widely used in professional projects especially among geographically distributed teams. In this paper we present a novel approach to detect zones inside business emails where elements of knowledge are likely to be found. We define an enhanced context taking into account not only the email content and metadata but also the competencies of the users and their roles. Also linguistic pragmatic analysis is added to usual NLP technics. After describing our model and method, we apply it to a real life corpus and evaluate the results based on machine learning experiments and filtering algorithm

From the beginning, knowledge is a preoccupation of human preoccupation. A lot of questions are still discussed: what is knowledge? How knowledge is built? How is it represented in mind? How can it be kept? How can it be learned? Our challenge is to capture design project knowledge related to work episodes, to extract and to represent the deep knowledge which belongs to the type of projects and design activities. In this paper, we present an approach that helps to capture knowledge from daily design project environment and to aggregate this knowledge as classifications.