USI: a fast and accurate approach for conceptual document annotation

Background: Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document. Results: In this paper we present USI (User-oriented Semantic Indexer), a fast and intuitive method for indexing tasks. We introduce a solution to suggest a conceptual annotation for new entities based on related already indexed documents. Our results, compared to those obtained by previous authors using the MeSH thesaurus and a dataset of biomedical papers, show that the method surpasses text-specific methods in terms of both quality and speed. Evaluations are done via usual metrics and semantic similarity. Conclusions: By only relying on neighbor documents, the User-oriented Semantic Indexer does not need a representative learning set. Yet, it provides better results than the other approaches by giving a consistent annotation scored with a global criterion-instead of one score per concept

Optimising industrial performance improvement within a quantitative multi-criteria aggregation framework

The major industrial control purpose is the reaching of the expected performances. In this sense, improvement processes are continuously carried out in order to define the right actions with regard to the objectives achievement. Thus, in order to better monitor the performance continuous improvement process, we consider a quantitative model for performance assessment. The industrial performance being multi-criteria, the proposed model is thus based on the one hand, on the MACBETH method to express quantitatively elementary performances from qualitative expert pair-wise comparisons and, on the other hand, on the Choquet integral to express the overall performance according to subordination and transverse interactions between the elementary performances. Then, the main focus concerns the decision-maker's requirements for optimising the improvement of the overall performance versus the allocated resources. In this view, we propose useful pieces of information first for diagnosis, then for overall performance improvement optimisation versus the costs of elementary performance improvements. Finally, the proposed approach is applied to an industrial case looking for optimising the improvement of the lean objective satisfaction related to the throughput time of hydraulic component manufacturing.industrial performance; performance indicators; Choquet integral; performance improvement; multi-criteria aggregation; decision support systems; DSS; MACBETH methodology; multi-criteria optimisation; industrial case study; mathematical programming; data analysis; throughput time; hydraulic components; component manufacturing.

Monitoring the improvement of an overall industrial performance based on a Choquet integral aggregation

The design and use of performance measurement systems (PMSs) have received considerable attention in recent years. Indeed, industrial performances are now defined in terms of numerous criteria to be synthesized for overall improvement purposes. The analysis of the literature leads to the conclusion that most of the proposed approaches deal with a qualitative approach of this multi-criteria issue. But only a few quantitative models for PMSs have been proposed in order to better monitor the continuous improvement cycle. Among them, the one proposed by the authors, based on a Choquet integral aggregation operator, allows to express an overall performance according to subordination and transverse interactions between the criteria involved. But, as this model is nonlinear, it is useful to define pieces of information aimed at aiding the manager to improve the performance situation. Thus, this article is a contribution to the managers' requirements for optimizing the improvement of the overall performance versus the allocated resources. In this view, indexes of efficiency and predictive improvement are proposed. The approach is applied to a case study submitted by a company manufacturing kitchen and bathroom furniture which wants to upgrade the monitoring of its "environment and quality improvement plan".Performance measurement systems Choquet integral aggregation Continuous performance improvement Resource optimization

Artificial Intelligence for industrial process supervision

This paper presents some difficulties of complex industrial process supervision and explains why artificial intelligence may help to solve some problems. Qualitative or semi-qualitative trend extraction is mentioned first. Then fault detection and fault supervision are evoked. The necessity for intelligent interfaces is explained next and distributed supervision is finally mentioned

On line qualitative interpretation of a dynamic simulation for diagnosis

SIGLEAvailable at INIST (FR), Document Supply Service, under shelf-number : RM 1234 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc