A review on the application of evolutionary computation to information retrieval

In this contribution, different proposals found in the specialized literature for the application of evolutionary computation to the field of information retrieval will be reviewed. To do so, different kinds of IR problems that have been solved by evolutionary algorithms are analyzed. Some of the specific existing approaches will be specifically described for some of these problems and the obtained results will be critically evaluated in order to give a clear view of the topic to the reader.CICYT under project TIC2002-03276University of Granada under project ‘‘Mejora de Metaheur ısticas mediante Hibridaci on y sus Aplicaciones

An Automatic Group Formation Method to Foster Innovation in Collaborative Learning at Workplace

Despite group formation in learning environments is commonly and successfully approached, there is a gap in the research literature with respect to its application in corporative learning. Regarding that creativity is as an important factor to increase innovation in companies, in the present research, we propose a group formation method, considering preferred roles and functional diversity, aiming to improve creativity in collaborative learning at workplace. We employed Tabu Search algorithm to automatically form groups based on Nonaka\u27s knowledge creation theory and preferred roles from Belbin’s model. We performed a case study to compare the quality of socio-cognitive interactions duringcollaborative learning in groups formed by the proposed method and randomly formed groups. The results show that groups formed by preferred roles and functional diversity are more creative and present enhanced fluency and more elaborated products in comparison to randomly formed groups

SEARCH ENGINES USING EVOLUTIONARY ALGORITHMS

A subset of AI is, evolutionary algorithm (EA) which involves evolutionary computation, a generic populationbased meta heuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Working of a search engine deals with searching for the indexed pages and referring to the related pages within a very short span of. Search engines commonly work through indexing. The paper deals with how a search engine works and how evolutionary algorithms can be used to develop a search engine that feeds on previous user requests to retrieve alternative documents that may not be returned by more conventional search engines

Multimodal emotion evaluation: a physiological model for cost-effective emotion classification

Emotional responses are associated with distinct body alterations and are crucial to foster adaptive responses, well-being, and survival. Emotion identification may improve peoples' emotion regulation strategies and interaction with multiple life contexts. Several studies have investigated emotion classification systems, but most of them are based on the analysis of only one, a few, or isolated physiological signals. Understanding how informative the individual signals are and how their combination works would allow to develop more cost-effective, informative, and objective systems for emotion detection, processing, and interpretation. In the present work, electrocardiogram, electromyogram, and electrodermal activity were processed in order to find a physiological model of emotions. Both a unimodal and a multimodal approach were used to analyze what signal, or combination of signals, may better describe an emotional response, using a sample of 55 healthy subjects. The method was divided in: (1) signal preprocessing; (2) feature extraction; (3) classification using random forest and neural networks. Results suggest that the electrocardiogram (ECG) signal is the most effective for emotion classification. Yet, the combination of all signals provides the best emotion identification performance, with all signals providing crucial information for the system. This physiological model of emotions has important research and clinical implications, by providing valuable information about the value and weight of physiological signals for emotional classification, which can critically drive effective evaluation, monitoring and intervention, regarding emotional processing and regulation, considering multiple contexts.publishe

Butterflies, Busy Weekends, and Chicken Salad: Genetic Criticism and the Output of @Pentametron

Textual analysis places great emphasis on determining the development and direction of authorial intention to illuminate a text’s layers of meaning. How, though, is one to determine the development of authorial intention in a text that appears to remove the traditional human author? This paper explores issues of authorship presented to genetic criticism (critique génétique) by algorithmically-produced texts – that is, texts produced through programmed logic in a computer rather than through direct human agency – such as those of the Twitter bot Pentametron (twitter.com/pentametron). This paper considers the perceived importance of authorship and human agency in the creation of a text. Algorithmic texts challenge contemporary notions of textual creation and development, in turn posing challenges to genetic criticism that are similar to those posed by cut-up texts in other media. This paper argues that Pentametron’s rather nonsensical algorithmic output stresses the reader’s responsibility for meaning-making, and suggests that such algorithmic texts are not so much final texts to be subjected to genetic critique themselves, but are more aptly considered to be forms of avant-texte. These avant-textes serve as inspiration for human-computer symbioses, for re-creations wherein readers make sense out of the seemingly senseless

The role of data mining techniques and tools in big data management in healthcare field

Data mining is one of the most important modern techniques used to achieve high output standards at all levels. The twenty-first century saw the advent of a new trend to improve medical services in the healthcare sector. To bridge the gap between previous studies and the practical applications of data mining, this study aimed to review the theoretical literature and previous studies related to the demonstration of data mining techniques and tools and their role in big data management. To achieve the objectives of the study, the researchers used a descriptive, analytical, documentary method. The study concluded many results including that in the era of the knowledge and technology revolution, data mining is one of the important issues, that requires everyone to take into account its achievements in our current era, as well as the existence of a correlation between big data and the provision of a separate health service in the field of healthcare, and work to address epidemics and discover vaccines for them. In the healthcare industry, data mining plays a vital role, especially in predicting various types of diseases. In detecting diseases, diagnosis is the main tool. The study recommended the need to conduct more experimental and exploratory studies dealing with healthcare data mining techniques and tools and their effect on the management of big data volumes, especially in our Arab countries and the need for the development of models and action plans and the development of processes and methods from which data in the healthcare sector can be explored