Search results for "artificial intelligence"

Multidimensional Model Design using Data Mining: A Rapid Prototyping Methodology

2017

[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]MOTIVE; International audience; Designing and building a Data Warehouse (DW), and associated OLAP cubes, are long processes, during which decision-maker requirements play an important role. But decision-makers are not OLAP experts and can find it difficult to deal with the concepts behind DW and OLAP. To support DW design in this context, we propose: (i) a new rapid prototyping methodology, integrating two different DM algorithms, to define dimension hierarchies according to decision-maker knowledge; (ii) a complete UML Profile, to define a DW schema that integrates both the DM algorithms; (iii) a mapping process to transform multidimensional …

An approximate/exact objective based search technique for solving general scheduling problems

2018

Abstract In this paper, we analyze single machine scheduling problems under the following minimization objectives: the maximum completion time (makespan), the total completion time and the maximum lateness, including fundamental practical aspects, which often occur in industrial or manufacturing reality: release dates, due dates, setup times, precedence constraints, deterioration (aging) of machines, as well as maintenance activities. To solve the problems, we propose an efficient representation of a solution and a fast neighborhood search technique, which calculates an approximation of criterion values in a constant time per solution in a neighborhood. On this basis, a novel approximate/ex…

Bayesian Modelling of Confusability of Phoneme-Grapheme Connections

2007

Deficiencies in the ability to map letters to sounds are currently considered to be the most likely early signs of dyslexia. This has motivated the use of Literate, a computer game for training this skill, in several Finnish schools and households as a tool in the early prevention of reading disability. In this paper, we present a Bayesian model that uses a student's performance in a game like Literate to infer which phoneme-grapheme connections student currently confuses with each other. This information can be used to adapt the game to a particular student's skills as well as to provide information about the student's learning progress to their parents and teachers. We apply our model to …

A Dynamic Reasoning Architecture for Computer Network Management

2005

This paper focuses on improving network management and monitoring by the adoption of Artificial Intelli- gence techniques. In order to allow automated reasoning on networking concepts, we defined an accurate ontologi- cal model capable of describing as better as possible the networking domain. The thorough representation of the do- main knowledge is used by a Logical Reasoner, which is an expert system capable of performing high-level manage- ment tasks.

Layout attributes and recall

2003

The spatial arrangement of elements such as icons in a computer interface may influence learning the interface. However, the effects of layout organization on users' information processing is relatively little studied so far. The three experiments of this paper examined two attributes of layouts: spatial grouping by proximity and semantic coherence. Learning was assessed by tasks in which 30 participants recalled icon-like items' labels, locations, or both as a series of study-recall trials. The results show that layout organization interacts with task demands. Semantic organization improves recall of labels, and spatial grouping supports recall of locations. When both labels and locations …

Recall of common and uncommon words from pure and mixed lists

1980

Recall of high- and low-frequency words in the conventional free recall paradigm was compared with recall of the same words when subjects were required to count backward before and after the presentation of each word. The addition of this distractor task was associated with a reduction in the high-frequency advantage otherwise found with pure lists containing only high- or low-frequency words. This finding is attributed to the disruption of organizational processes. In contrast, the low-frequency advantage found with conventional presentation of mixed lists, containing high- and low-frequency words, was not reduced by distraction. These findings indicate that the frequency effects obtained …

The effects of tasks on integrating information from multiple documents.

2008

The authors examine 2 issues: (a) how students integrate information from multiple scientific documents to describe and explain a physical phenomenon that represents a subset of the information in the documents; and (b) the role of 2 sorts of tasks to achieve this type of integration, either writing an essay on a question requiring integration across texts or answering shorter intratext questions that require students to integrate information within a single text, while superficial and deep comprehension measurements are obtained. Undergraduate students answered 1 of the 2 types of questions, and their reading times were recorded. Half of the sample thought aloud. Results showed that the in…

Feature selection using ROC curves on classification problems

2010

Feature Selection (FS) is one of the key stages in classification problems. This paper proposes the use of the area under Receiver Operator Characteristic curves to measure the individual importance of every input as well as a method to discover the variables that yield a statistically significant improvement in the discrimination power of the classification model.

2021

ObjectivesTo assess the ability to predict individual unfavourable future status and development in the 20m shuttle run test (20MSRT) during adolescence with machine learning (random forest (RF) classifier).MethodsData from a 2-year observational study (2013‒2015, 12.4±1.3 years, n=633, 50% girls), with 48 baseline characteristics (questionnaires (demographics, physical, psychological, social and lifestyle factors), objective measurements (anthropometrics, fitness characteristics, physical activity, body composition and academic scores)) were used to predict: (Task 1) unfavourable future 20MSRT status (identification of individuals in the lowest 20MSRT tertile after 2 years), and (Task 2) u…

Convolutional Matrix Factorization for Recommendation Explanation

2018

In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.