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The purpose of this study is to propose a framework for extracting medical information from the Web using domain ontologies. Patient–Doctor conversations have become prevalent on the Web. For instance, solutions like HealthTap or AskTheDoctors allow patients to ask doctors health-related questions. However, most online health-care consumers still struggle to express their questions efficiently due mainly to the expert/layman language and knowledge discrepancy. Extracting information from these layman descriptions, which typically lack expert terminology, is challenging. This hinders the efficiency of the underlying applications such as information retrieval. Herein, an ontology-driven approach is proposed, which aims at extracting information from such sparse descriptions using a meta-model.

A meta-model is designed to bridge the gap between the vocabulary of the medical experts and the consumers of the health services. The meta-model is mapped with SNOMED-CT to access the comprehensive medical vocabulary, as well as with WordNet to improve the coverage of layman terms during information extraction. To assess the potential of the approach, an information extraction prototype based on syntactical patterns is implemented.

The evaluation of the approach on the gold standard corpus defined in Task1 of ShARe CLEF 2013 showed promising results, an F-score of 0.79 for recognizing medical concepts in real-life medical documents.

The originality of the proposed approach lies in the way information is extracted. The context defined through a meta-model proved to be efficient for the task of information extraction, especially from layman descriptions.

The requirements engineering (RE) process constitutes the earliest phase of the information system development life cycle. Requirements elicitation is considered as one of the most critical activities of this phase. Moreover, requirements elicitation is still a challenge, especially in the distributed environment of so‐called inter‐company cooperative information systems (ICISs). The purpose of this paper is to propose a methodology to elicit requirements for an ICIS.

An analytical research approach was conducted. The current RE approaches, which are based either on goal, scenario or viewpoint were evaluated. Then the role of the elicitation technique selection step within the requirements elicitation process was examined. Finally the factors that affect this step in a distributed environment were studied. An example from the textile industry is used to illustrate the applicability of the proposed methodology.

Though existing requirements elicitation approaches based either on goal, scenario or viewpoint are effective techniques, they do not fit exactly to a cooperative distributed environment: more issues are created by inadequate communication, time difference between sites, cultural, language and characteristics diversity of stakeholders which affect the elicitation technique selection step and thus the requirements elicitation process. In order to tackle these issues, this paper presents a methodology called MAMIE (from Macro‐ to Micro‐level requirements Elicitation) to elicit requirements for an ICIS. A prototype tool has been developed to support the operation of the methodology.

The major limitation of the paper is that has not yet been tested in an existing organization.

To provide the analyst with well‐defined steps in order to elicit requirements of an ICIS. To understand the role of the elicitation technique selection step within the requirements elicitation process and identifying the factors which have an impact on this step. To select an appropriate elicitation technique according to these factors.

MAMIE integrates the three notions of goal, scenario and viewpoint to elicit requirements for an ICIS. The paper argues that these concepts may be used simultaneously and in a complementary way to improve the requirements elicitation process. Moreover, in order to increase the quality of the elicited requirements and thus the quality of the system‐to‐be, selecting an elicitation technique in MAMIE is not based on personal preferences but on situation assessment.

Many problems in science and engineering fields involve decision making. Usually these decision‐making processes are based on several criteria that represent various experts' knowledge. Stakeholder prioritization is useful for assisting in decision‐making situations where various stakeholders have competing interests, resources are limited, and stakeholder requirements must be appropriately balanced. When these conflicts arise it is important to the success of the organization that it has prioritized each stakeholder according to the situation. To date, few researchers tried to resolve this question, mostly are based on intuitive and very simple reasoning methods which are error prone. The purpose of this paper is to propose a multi‐criteria decision analysis process to help decision makers when evaluating and prioritizing stakeholders.

In this process, Mitchell et al.'s model is used for identifying criteria on which stakeholders will be evaluated and the fuzzy Choquet integral as an aggregation operator. This research also tested and discussed the proposal using a case study from Toulouse city subway.

The results show the applicability of this process and the effectiveness of using the fuzzy Choquet integral than a traditional multi‐criteria evaluation method for human subjective evaluation, or when criteria are not mutually independent.

The highly subjective nature of criteria weights and rapid elicitation can lead to questions of validity. Also, results are not always widely accepted.

The paper is original in considering the stakeholder prioritization problem as a multi‐criteria decision analysis problem; using a simple and well‐known model to classify stakeholders, i.e Mitchell et al.'s model; and in using Choquet integral as an aggregation operator which allows considering interaction between criteria.