Learning Business Rules with Association Rule Classifiers

Kliegr, Tomáš; Kuchař, Jaroslav; Sottara, Davide; Vojíř, Stanislav

doi:10.1007/978-3-319-09870-8_18

Cited by 14 publications

(9 citation statements)

References 7 publications

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“…Based on the concepts defined above, the construction of the CAR-Classifier is elaborated as follows. Concretely, building a CAR-Classifier mainly consists of two stages [34,39,49], i.e., the rule generation stage (RG-Stage) and the classifier build stage (CB-Stage). The former aims to mine all CARs, i.e., CCARs that satisfy specific minSup and minConf requirements, while the latter is to build the CAR-Classifier based on the extracted CARs.…”

Section: Methodsmentioning

confidence: 99%

Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining

Liu

Zhou

Wang

et al. 2019

Sensors

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Hypertension is one of the most common cardiovascular diseases, which will cause severe complications if not treated in a timely way. Early and accurate identification of hypertension is essential to prevent the condition from deteriorating further. As a kind of complex physiological state, hypertension is hard to characterize accurately. However, most existing hypertension identification methods usually extract features only from limited aspects such as the time-frequency domain or non-linear domain. It is difficult for them to characterize hypertension patterns comprehensively, which results in limited identification performance. Furthermore, existing methods can only determine whether the subjects suffer from hypertension, but they cannot give additional useful information about the patients’ condition. For example, their classification results cannot explain why the subjects are hypertensive, which is not conducive to further analyzing the patient’s condition. To this end, this paper proposes a novel hypertension identification method by integrating classification and association rule mining. Its core idea is to exploit the association relationship among multi-dimension features to distinguish hypertensive patients from normotensive subjects. In particular, the proposed method can not only identify hypertension accurately, but also generate a set of class association rules (CARs). The CARs are proved to be able to reflect the subject’s physiological status. Experimental results based on a real dataset indicate that the proposed method outperforms two state-of-the-art methods and three common classifiers, and achieves 84.4%, 82.5% and 85.3% in terms of accuracy, precision and recall, respectively.

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Section: Methodsmentioning

confidence: 99%

Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining

Liu

Zhou

Wang

et al. 2019

Sensors

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“…decision trees). A disadvantage of a model based on association rules is the large number of rules (Kliegr et al, 2014). It is suitable to insert these rules in a business rule system into a conditioned rule subsetin order to maintain the transparency a manageability of the whole business rule base.…”

Section: Discussion Advantages and Limitations Of The Proposed Methodsmentioning

confidence: 99%

Business Rules Mining Using GUHA Method for the Personalization of Commercial Offers

Vojíř¹,

Smutný²

2017

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A shift from mass to personalized marketing, and thus also to personalized offers, brings firms an advantage for building customer relationships. The article introduces an artefact in the form of a method for creating personalized offers, focused on companies engaged in e-commerce. This method is based on mining association rules using the GUHA method. The association rules are converted into business rules and then combined with other manually defined business rules. The application of the method in practice is illustrated on customers' data from the e-shop of a company doing business in navigation systems, for the purpose of selecting personalized offers for an e-mailing campaign. The practical illustration uses a combination of the data mining system LISp-Miner and the business rule system JBoss Drools, which are freely available tools. The advantages and limitations of the proposed method, in connection with creating personalized marketing strategies in e-commerce, are discussed. The purpose of this practically oriented article is to address marketing and account managers and the issues connected with the personalization of marketing activities.

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“…A previous article about the H2020 Smart-Akis project presented knowledge about the contributions of European Farming Technologies and commercial technologies [ 25 ]. Additionally, reference [ 26 ] demonstrated that the use of Association Rule Classification algorithms, such as Classification Based on Associations algorithm (CBA) [ 27 ], solves the excessive number of rules contained within even small datasets, and allows contradicting rules to be generated without adversely impacting the quality of the classifier. A similar tool focused on agriculture was presented in [ 28 ] where the author proposed a cloud-based autonomic information system for delivering Agriculture-as-a-Service (AaaS) through the use of cloud and big data technology.…”

Section: Related Workmentioning

confidence: 99%

Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming

Cambra

Sendra

Lloret

et al. 2018

Sensors

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Improving the sustainability in agriculture is nowadays an important challenge. The automation of irrigation processes via low-cost sensors can to spread technological advances in a sector very influenced by economical costs. This article presents an auto-calibrated pH sensor able to detect and adjust the imbalances in the pH levels of the nutrient solution used in hydroponic agriculture. The sensor is composed by a pH probe and a set of micropumps that sequentially pour the different liquid solutions to maintain the sensor calibration and the water samples from the channels that contain the nutrient solution. To implement our architecture, we use an auto-calibrated pH sensor connected to a wireless node. Several nodes compose our wireless sensor networks (WSN) to control our greenhouse. The sensors periodically measure the pH level of each hydroponic support and send the information to a data base (DB) which stores and analyzes the data to warn farmers about the measures. The data can then be accessed through a user-friendly, web-based interface that can be accessed through the Internet by using desktop or mobile devices. This paper also shows the design and test bench for both the auto-calibrated pH sensor and the wireless network to check their correct operation.

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Learning Business Rules with Association Rule Classifiers

Cited by 14 publications

References 7 publications

Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining

Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining

Business Rules Mining Using GUHA Method for the Personalization of Commercial Offers

Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming

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