scholarly journals e-HUNSR: An Efficient Algorithm for Mining High Utility Negative Sequential Rules

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1211
Author(s):  
Mengjiao Zhang ◽  
Tiantian Xu ◽  
Zhao Li ◽  
Xiqing Han ◽  
Xiangjun Dong
Keyword(s):  
Decision Making ◽  
Real Life ◽  
The Other ◽  
Utility Value ◽  
Science Data ◽  
Related Information ◽  
Sequential Rule ◽  
Pruning Strategy ◽  
High Utility ◽  
Synthetic Datasets

As an important technology in computer science, data mining aims to mine hidden, previously unknown, and potentially valuable patterns from databases.High utility negative sequential rule (HUNSR) mining can provide more comprehensive decision-making information than high utility sequential rule (HUSR) mining by taking non-occurring events into account. HUNSR mining is much more difficult than HUSR mining because of two key intrinsic complexities. One is how to define the HUNSR mining problem and the other is how to calculate the antecedent’s local utility value in a HUNSR, a key issue in calculating the utility-confidence of the HUNSR. To address the intrinsic complexities, we propose a comprehensive algorithm called e-HUNSR and the contributions are as follows. (1) We formalize the problem of HUNSR mining by proposing a series of concepts. (2) We propose a novel data structure to store the related information of HUNSR candidate (HUNSRC) and a method to efficiently calculate the local utility value and utility of HUNSRC’s antecedent. (3) We propose an efficient method to generate HUNSRC based on high utility negative sequential pattern (HUNSP) and a pruning strategy to prune meaningless HUNSRC. To the best of our knowledge, e-HUNSR is the first algorithm to efficiently mine HUNSR. The experimental results on two real-life and 12 synthetic datasets show that e-HUNSR is very efficient.

scholarly journals On-Shelf Utility Mining of Sequence Data

2021 ◽  
Vol 16 (2) ◽  
pp. 1-31
Author(s):  
Chunkai Zhang ◽  
Zilin Du ◽  
Yuting Yang ◽  
Wensheng Gan ◽  
Philip S. Yu
Keyword(s):  
High Efficiency ◽  
Sequence Data ◽  
Real Life ◽  
Search Space ◽  
Upper Bounds ◽  
Utility Mining ◽  
Limited Memory ◽  
Time Periods ◽  
High Utility ◽  
Synthetic Datasets

Utility mining has emerged as an important and interesting topic owing to its wide application and considerable popularity. However, conventional utility mining methods have a bias toward items that have longer on-shelf time as they have a greater chance to generate a high utility. To eliminate the bias, the problem of on-shelf utility mining (OSUM) is introduced. In this article, we focus on the task of OSUM of sequence data, where the sequential database is divided into several partitions according to time periods and items are associated with utilities and several on-shelf time periods. To address the problem, we propose two methods, OSUM of sequence data (OSUMS) and OSUMS + , to extract on-shelf high-utility sequential patterns. For further efficiency, we also design several strategies to reduce the search space and avoid redundant calculation with two upper bounds time prefix extension utility ( TPEU ) and time reduced sequence utility ( TRSU ). In addition, two novel data structures are developed for facilitating the calculation of upper bounds and utilities. Substantial experimental results on certain real and synthetic datasets show that the two methods outperform the state-of-the-art algorithm. In conclusion, OSUMS may consume a large amount of memory and is unsuitable for cases with limited memory, while OSUMS + has wider real-life applications owing to its high efficiency.

Defining the Phenomenon of Mental Models for Critical Events

2013 ◽  
Author(s):  
Kanter van Deurzen ◽  
Imre Horváth ◽  
Regine Vroom
Keyword(s):  
Decision Making ◽  
Mental Models ◽  
Mental Model ◽  
Real Life ◽  
Critical Events ◽  
Cognitive Representations ◽  
Related Information ◽  
Strong Relation ◽  
Decision Making Processes ◽  
Definition Of

People use cognitive representations in order to characterize, understand, reason and predict the surrounding world. A class of these representations are called mental models. Designers of informing systems are interested in how mental models influence decision making, especially during critical events. With this knowledge they could optimize the content and amount of information that is needed for a dependable decision making process. New insights are needed about the operation of mental models in the course of critical events, as well as on how informing influences the real life operationalization of mental models. Most of the definitions available in the literature are overly general, and no definition was found that would support the design of informing systems for critical events. Therefore, the objective of our research was to derive a definition of mental models that play a role in critical events. Actually, we systematically constructed a definition from those attributes of mental model descriptions that were found to be relevant to critical events. First we decomposed 125 published descriptions to a set of attributes, and then assessed each attribute to see if they were associated with critical events, or not. In fact, this analysis involved not only the relevance of the attributes to critical events, but also the frequency of occurrence in the surveyed papers. This exploration provided a large number of attributes for a new mental model definition. Based on the top rated attributes, a definition was synthesized which, theoretically, has a strong relation to critical events. Though further validation will be needed, we argue that the derived mental model definition is strong because it establishes relationships with all generic features of critical events and makes the related information contents explicit. Hence the proposed definition can be considered a starting platform for investigations of the influence of informing on decision making processes in critical events.

Mining Dense Periodic Patterns in Time Series Databases

2008 ◽  
pp. 44-62
Author(s):  
Wynne Hsu ◽  
Mong Li Lee ◽  
Junmei Wang
Keyword(s):  
Time Series ◽  
Pattern Mining ◽  
Real Life ◽  
Search Space ◽  
Detection Algorithm ◽  
Limited Range ◽  
Periodic Pattern ◽  
Periodic Patterns ◽  
Pruning Strategy ◽  
Synthetic Datasets

In this chapter, we describe a new periodicity detection algorithm to efficiently discover short period patterns that may exist in only a limited range of the time series. We refer to these patterns as the dense periodic patterns, where the periodicity is focused on part of the time series. We present a dense periodic pattern mining algorithm called DPMiner to find dense periodic patterns, and design a pruning strategy to limit the search space to the feasible periods. Experimental results on both real-life and synthetic datasets indicate that DPMiner is both scalable and efficient.

Analysis of the Banks’ Initial Reactions with the 9/11 and 3/11

2015 ◽  
Vol 10 (1) ◽  
pp. 151-162
Author(s):  
Yasutake Sayanagi ◽  
◽  
Kenji Watanabe
Keyword(s):  
Decision Making ◽  
Banking Industry ◽  
Terrorist Attack ◽  
Great East Japan Earthquake ◽  
The Other ◽  
Location Strategy ◽  
Town Hall ◽  
Related Information ◽  
Crisis Leaders

The purpose of this paper is to analyze the initial reactions of banks with the disaster to improve the resiliency of banking industry and encourage banks to share more disaster related information in the industry to help each other. Two severe cases in the banking industry were picked up, one for the 3/11 Great East Japan Earthquake of 2011 (3/11 or 311) and the other for the 9/11 terrorist attack of 2001 (9/11 or 911). In addition, to support identifying the issues of the banks, this study refers to the case of Otsuchi Town Hall that had serious damages by the 3/11 Great East Japan Earthquake of 2011, as it is difficult making a direct comparison with some points between Iwate Banks and Fuji Bank. Those are analyzed in comparison with the other case of the Otsuchi Town Hall. Those cases are discussed from the various angles such as the immediate tasks they have to perform when disaster happens (the Day Zero Duty), the recovery location strategy, BCMPolicy and Crisis leaders. Potential conflicts were found between the BCM policy and the Day Zero Duty as well as the quick decision making and having too many recovery options etc.

scholarly journals Fuzzy Multicriteria Models for Decision Making in Gamification

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 682 ◽  
Author(s):  
María Carmen Carnero
Keyword(s):  
Decision Making ◽  
Operations Management ◽  
Fuzzy Ahp ◽  
Real Life ◽  
The Other ◽  
Analytic Hierarchy ◽  
Innovative Teaching ◽  
Teaching Technique ◽  
Hierarchy Process ◽  
Life Decision

Gamification is an innovative teaching technique that may prove hugely beneficial when properly used. For this reason, since 2002, the number of situations in which gamification is used has increased exponentially. This large number of options makes it difficult to choose the best application, especially in circumstances where there is the usual uncertainty that real-life decision making involves. To address this problem, this study creates two models, one using a fuzzy analytic hierarchy process (AHP), and the other, which combines fuzzy AHP with the measuring attractiveness by a categorical-based evaluation technique (MACBETH) approach, to choose the best gamification application for the ‘Operations Management’ course, within the Masters in Industrial Engineering. This is the first contribution in the literature combining fuzzy AHP and MACBETH. The decision centre used was the lecturer who teaches the course. There is no precedent in the literature using fuzzy logic to choose the best gamification application for a course. The results of the study show that Socrative is the best gamification application for this course within the Masters, and, as the models begin to be used in degree courses, the better choice would be Quizizz, the more clearly the earlier the course is taught within the degree programme.

Medical Diagnosis: A Real Life Application of Logic

1978 ◽  
Vol 71 (6) ◽  
pp. 499-504
Author(s):  
Kenneth P. Goldberg
Keyword(s):  
Decision Making ◽  
Mathematical Logic ◽  
Medical Diagnosis ◽  
Real Life ◽  
Junior College ◽  
The Other ◽  
College Level ◽  
Human Reason ◽  
The One ◽  
Rational Reasoning

Of all the mathematical topics taught at the high school and junior college level, logic must certainly be one of the most frustrating for both students and teachers. On the one hand, the student is told that logic is the necessary basis on which all rational reasoning and decision making rests. On the other hand, since few situations involving human reason are simple enough to permit the application of mathematical logic, it is extremely difficult to discuss and illustrate the use of logic in a believable and interesting manner.

A Bird in the Hand Isn’t Good for Long

2018 ◽  
Vol 65 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Stefan Scherbaum ◽  
Simon Frisch ◽  
Maja Dshemuchadse
Keyword(s):  
Decision Making ◽  
Cognitive Control ◽  
The Other ◽  
Decision Task ◽  
Short Term ◽  
Additional Time ◽  
Control Processes ◽  
Folk Wisdom ◽  
Study Participants ◽  
Insight Into

Abstract. Folk wisdom tells us that additional time to make a decision helps us to refrain from the first impulse to take the bird in the hand. However, the question why the time to decide plays an important role is still unanswered. Here we distinguish two explanations, one based on a bias in value accumulation that has to be overcome with time, the other based on cognitive control processes that need time to set in. In an intertemporal decision task, we use mouse tracking to study participants’ responses to options’ values and delays which were presented sequentially. We find that the information about options’ delays does indeed lead to an immediate bias that is controlled afterwards, matching the prediction of control processes needed to counter initial impulses. Hence, by using a dynamic measure, we provide insight into the processes underlying short-term oriented choices in intertemporal decision making.

Mental Contrasting of Future and Reality

2010 ◽  
Vol 9 (3) ◽  
pp. 138-144 ◽  
Author(s):  
Gabriele Oettingen ◽  
Doris Mayer ◽  
Babette Brinkmann
Keyword(s):  
Decision Making ◽  
Everyday Life ◽  
Brief Intervention ◽  
Middle Level ◽  
The Other ◽  
Metacognitive Strategy ◽  
Mental Contrasting ◽  
Low Expectations

Mental contrasting of a desired future with present reality leads to expectancy-dependent goal commitments, whereas focusing on the desired future only makes people commit to goals regardless of their high or low expectations for success. In the present brief intervention we randomly assigned middle-level managers (N = 52) to two conditions. Participants in one condition were taught to use mental contrasting regarding their everyday concerns, while participants in the other condition were taught to indulge. Two weeks later, participants in the mental-contrasting condition reported to have fared better in managing their time and decision making during everyday life than those in the indulging condition. By helping people to set expectancy-dependent goals, teaching the metacognitive strategy of mental contrasting can be a cost- and time-effective tool to help people manage the demands of their everyday life.

scholarly journals CAD integrated automatic recognition of weld paths

2021 ◽  
Author(s):  
Tuan Anh Tran ◽  
Andrei Lobov ◽  
Tord Hansen Kaasa ◽  
Morten Bjelland ◽  
Ole Terje Midling
Keyword(s):  
Life Cycle ◽  
Spatial Analysis ◽  
Product Life Cycle ◽  
Real Life ◽  
Automatic Recognition ◽  
Integrated Method ◽  
Weld Joints ◽  
Related Information ◽  
Almost All ◽  
Sequential Assembly

AbstractIn this paper, a CAD integrated method is proposed for automatic recognition of potential weld locations in large assembly structures predominantly comprised of weld joints. The intention is to reduce the total man-hours spent on manually locating, assigning, and maintaining weld-related information throughout the product life cycle. The method utilizes spatial analysis of extracted stereolithographic data in combination with available CAD functions to determine whether the accessibility surrounding a given intersection edge is sufficient for welding. To demonstrate the method, a system is developed in Siemens NX using their NXOpen Python API. The paper presents the application of the method to real-life use cases in varying complexity in cooperation with industrial partners. The system is able to correctly recognize almost all weld lines for the parts considered within a few minutes. Some exceptions are known for particular intersection lines located deep within notched joints and geometries weldable through sequential assembly, which are left as a subject to further works.

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