Search results for "association rule"
showing 8 items of 18 documents
A probabilistic condensed representation of data for stream mining
2014
Data mining and machine learning algorithms usually operate directly on the data. However, if the data is not available at once or consists of billions of instances, these algorithms easily become infeasible with respect to memory and run-time concerns. As a solution to this problem, we propose a framework, called MiDEO (Mining Density Estimates inferred Online), in which algorithms are designed to operate on a condensed representation of the data. In particular, we propose to use density estimates, which are able to represent billions of instances in a compact form and can be updated when new instances arrive. As an example for an algorithm that operates on density estimates, we consider t…
Processing of audiovisual associations in the human brain: dependency on expectations and rule complexity
2012
In order to respond to environmental changes appropriately, the human brain must not only be able to detect environmental changes but also to form expectations of forthcoming events. The events in the external environment often have a number of multisensory features such as pitch and form. For integrated percepts of objects and events, crossmodal processing, and crossmodally induced expectations of forthcoming events are needed. The aim of the present study was to determine whether the expectations created by visual stimuli can modulate the deviance detection in the auditory modality, as reflected by auditory event-related potentials (ERPs). Additionally, it was studied whether the complexi…
Using association rules to assess purchase probability in online stores
2016
The paper addresses the problem of e-customer behavior characterization based on Web server log data. We describe user sessions with the number of session features and aim to identify the features indicating a high probability of making a purchase for two customer groups: traditional customers and innovative customers. We discuss our approach aimed at assessing a purchase probability in a user session depending on categories of viewed products and session features. We apply association rule mining to real online bookstore data. The results show differences in factors indicating a high purchase probability in session for both customer types. The discovered association rules allow us to formu…
An Ontology-Based Monitoring System in Vineyards of the Burgundy Region
2019
Given the France's rich wine heritage as well as its pioneering position as the world's second wine producer, the production of high quality wines plays a role of primary importance. The recent development of IOT and efficient big data processing has been shown to provide purposeful issue to permanent monitoring during the entire wine making process. Standing within this trend, we introduce in this paper an intelligent system for vineyards monitoring in the Burgundy region. The main trust of the proposed system relies on the use of the Swrl rules in WineCloud ontology. The design of the ontology is mainly based on information gathered from interviews with wine growers. In addition, sensor d…
CLEARMiner: a new algorithm for mining association patterns on heterogeneous time series from climate data
2010
International audience; Recently, improvements in sensor technology contributed to increasing in spatial data acquisition. The use of remote sensing in many countries and states, where agricultural business is a large part of their gross income, can provide a valuable source to improve their economy. The combination of climate and remote sensing data can reveal useful information, which can help researchers to monitor and estimate the production of agricultural crops. Data mining techniques are the main tools to analyze and extract relationships and patterns. In this context, this paper presents a new algorithm for mining association patterns in Geo-referenced databases of climate and satel…
Adding Knowledge Extracted by Association Rules into Similarity Queries
2010
International audience; In this paper, we propose new techniques to improve the quality of similarity queries over image databases performing association rule mining over textual descriptions and automatically extracted features of the image content. Based on the knowledge mined, each query posed is rewritten in order to better meet the user expectations. We propose an extension of SQL aimed at exploring mining processes over complex data, generating association rules that extract semantic information from the textual description superimposed to the extracted features, thereafter using them to rewrite the queries. As a result, the system obtains results closer to the user expectation than i…
Facilitators of and Barriers to Sustainable Development in Small and Medium-Sized Enterprises: A Descriptive Exploratory Study in Romania
2021
In the context of growing concerns regarding the deterioration of the environment and the increase in social inequalities, the concept of sustainability emerged as a response of companies, in order to contribute to community goodwill. The drivers and obstacles for the businesses engaging in sustainable policies have been explored at large by scientific literature. However, research gaps were observed, namely regarding SMEs, that tend to have a less formal and more fragmented approach to sustainability. The goal of our study is to determine the main barriers and facilitators for sustainability that Romanian SMEs face, and the connections between them and with the firms’ characteristics. Our …
Discovering Gender-Specific Knowledge from Finnish Basic Education using PISA Scale Indices
2014
The Programme for International Student Assessment, PISA, is a worldwide study to assess knowledge and skills of 15- year-old students. Results of the latest PISA survey conducted in 2012 were published in December 2013. According to the results, Finland is one of the few countries where girls performed better in mathematics than boys. The purpose of this work is to refine the analysis of this observation by using education data mining techniques. More precisely, as part of standard PISA preprocessing phase certain scale indices are constructed based on information gathered from the background questionnaire of each participating student. The indices describe, e.g., students’ engagement, dri…