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Article
Publication date: 25 July 2018

Ke Yi Zhou and Shaolin Hu

The similarity measurement of time series is an important research in time series detection, which is a basic work of time series clustering, anomaly discovery, prediction…

Abstract

Purpose

The similarity measurement of time series is an important research in time series detection, which is a basic work of time series clustering, anomaly discovery, prediction and many other data mining problems. The purpose of this paper is to design a new similarity measurement algorithm to improve the performance of the original similarity measurement algorithm. The subsequence morphological information is taken into account by the proposed algorithm, and time series is represented by a pattern, so the similarity measurement algorithm is more accurate.

Design/methodology/approach

Following some previous researches on similarity measurement, an improved method is presented. This new method combines morphological representation and dynamic time warping (DTW) technique to measure the similarities of time series. After the segmentation of time series data into segments, three parameter values of median, point number and slope are introduced into the improved distance measurement formula. The effectiveness of the morphological weighted DTW algorithm (MW-DTW) is demonstrated by the example of momentum wheel data of an aircraft attitude control system.

Findings

The improved method is insensitive to the distortion and expansion of time axis and can be used to detect the morphological changes of time series data. Simulation results confirm that this method proposed in this paper has a high accuracy of similarity measurement.

Practical implications

This improved method has been used to solve the problem of similarity measurement in time series, which is widely emerged in different fields of science and engineering, such as the field of control, measurement, monitoring, process signal processing and economic analysis.

Originality/value

In the similarity measurement of time series, the distance between sequences is often used as the only detection index. The results of similarity measurement should not be affected by the longitudinal or transverse stretching and translation changes of the sequence, so it is necessary to incorporate the morphological changes of the sequence into similarity measurement. The MW-DTW is more suitable for the actual situation. At the same time, the MW-DTW algorithm reduces the computational complexity by transforming the computational object to subsequences.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 11 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

Book part
Publication date: 19 September 2014

George Chondrakis and Tomas Farchi

This article explores the effect of technological similarity in acquisitions on invention quantity and quality. In doing so, we confirm previous findings in the literature…

Abstract

This article explores the effect of technological similarity in acquisitions on invention quantity and quality. In doing so, we confirm previous findings in the literature suggesting that technological similarity exhibits an inverted U-shaped relationship with innovative output and a negative relationship with average invention quality. However, we identify the nature of the technology as an important moderating factor for both relationships. We distinguish between two types of technologies, complex and discrete, and suggest that at high levels of technological similarity, invention quantity and average quality increase more in complex technology industries as compared to discrete technology industries. These effects are attributed to innovation cumulativeness and the interdependencies developed between patent rights in complex technology settings. A study of acquisition and patenting activity in two industries over a sixteen-year period provides empirical support to our claims.

Details

Advances in Mergers and Acquisitions
Type: Book
ISBN: 978-1-78350-970-6

Keywords

Book part
Publication date: 9 November 2020

Riikka Hofmann

There is an identified need in higher education research for methods which have the capacity to generate conceptual insights grounded in concrete local practice but with…

Abstract

There is an identified need in higher education research for methods which have the capacity to generate conceptual insights grounded in concrete local practice but with wider applicability in understanding and facilitating research-based change. This chapter outlines an intermediate approach to qualitative data analysis which can support theoretical knowledge advancement from practice-based research, which I call the difference-within-similarity approach. It involves a particular way of conducting dialogues with our data: of interanimating similarities and differences within our qualitative datasets. The approach outlined involves first identifying a similarity, then systematically examining differences within that similarity to generate theoretical explanations. Drawing on sociocultural theorising, particularly dialogic theory and cultural–historical activity theory, the approach is based on the idea that new meanings arise from a comparison of multiple perspectives on the ‘same’ phenomenon. The tensions between such perspectives are seen as a key driver for change in educational practice. Therefore, articulating and examining such tensions in our data gives an opportunity to simulate the possibility of change in our analysis and, hence, develop insights which can inform change beyond local settings. Important here is that the differences examined are bound together by an analytically productive similarity. Through multiple research examples, the chapter identifies and illustrates a range of ways of articulating productive analytical similarities for comparison in our data: through theory/literature, through forward and backwards processing of data itself and through a process termed ‘weaving’.

Open Access
Article
Publication date: 15 February 2022

Martin Nečaský, Petr Škoda, David Bernhauer, Jakub Klímek and Tomáš Skopal

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle…

Abstract

Purpose

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle, lacking the luxury of centralized database administration, database schemes, shared attributes, vocabulary, structure and semantics. The existing dataset catalogs provide basic search functionality relying on keyword search in brief, incomplete or misleading textual metadata attached to the datasets. The search results are thus often insufficient. However, there exist many ways of improving the dataset discovery by employing content-based retrieval, machine learning tools, third-party (external) knowledge bases, countless feature extraction methods and description models and so forth.

Design/methodology/approach

In this paper, the authors propose a modular framework for rapid experimentation with methods for similarity-based dataset discovery. The framework consists of an extensible catalog of components prepared to form custom pipelines for dataset representation and discovery.

Findings

The study proposes several proof-of-concept pipelines including experimental evaluation, which showcase the usage of the framework.

Originality/value

To the best of authors’ knowledge, there is no similar formal framework for experimentation with various similarity methods in the context of dataset discovery. The framework has the ambition to establish a platform for reproducible and comparable research in the area of dataset discovery. The prototype implementation of the framework is available on GitHub.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

Book part
Publication date: 19 July 2016

Cynthia L. Gramm and John F. Schnell

We investigate the effects of management-employee similarity on mistreated employees’ propensities to engage in legal and organizational claiming, to quit, and to not seek…

Abstract

Purpose

We investigate the effects of management-employee similarity on mistreated employees’ propensities to engage in legal and organizational claiming, to quit, and to not seek a remedy in ongoing employment relationships.

Methodology/approach

We test hypotheses generated by the similarity-attraction and similarity-betrayal paradigms using Tobit regression and data from vignette-based employee surveys.

Findings

Mistreated employees with same-sex supervisors are more likely to initiate legal claims and to quit than those with opposite-sex supervisors, but less likely to initiate legal claims and to quit when they have a same-race supervisor than when they have a different-race supervisor. The effects of management-employee similarity on mistreated employees’ remedy-seeking responses exhibit asymmetries by gender and by race. The presence of same-race supervisors or other managers appears to diminish the greater reluctance of nonwhite employees, compared to white employees, to use organizational claiming mechanisms.

Originality/value

We know of no prior published research that has investigated the determinants of employees’ propensities to engage in multiple forms of remedy seeking, as well as the propensity to not seek a remedy, in response to plausibly illegal mistreatment not involving dismissal.

Book part
Publication date: 3 October 2006

Javier Gimeno, Ming-Jer Chen and Jonghoon Bae

We investigate the dynamics of competitive repositioning of firms in the deregulated U.S. airline industry (1979–1995) in terms of a firm's target market, strategic…

Abstract

We investigate the dynamics of competitive repositioning of firms in the deregulated U.S. airline industry (1979–1995) in terms of a firm's target market, strategic posture, and resource endowment relative to other firms in the industry. We suggest that, despite strong inertia in competitive positions, the direction of repositioning responds to external and internal alignment considerations. For external alignment, we examined how firms changed their competitive positioning to mimic the positions of similar, successful firms, and to differentiate themselves when experiencing intense rivalry. For internal alignment, we examined how firms changed their position in each dimension to align with the other dimensions of positioning. This internal alignment led to convergent positioning moves for firms with similar resource endowments and strategic postures, and divergent moves for firms with similar target markets and strategic postures. The evidence suggests that repositioning moves in terms of target markets and resource endowments are more sensitive to external and internal alignment considerations, but that changes in strategic posture are subject to very high inertia and do not appear to respond well to alignment considerations.

Details

Ecology and Strategy
Type: Book
ISBN: 978-1-84950-435-5

Book part
Publication date: 12 September 2003

Joel A.C Baum and Theresa K Lant

Organizations create their environments by constructing interpretations and then acting on them as if they were true. This study examines the cognitive spatial boundaries…

Abstract

Organizations create their environments by constructing interpretations and then acting on them as if they were true. This study examines the cognitive spatial boundaries that managers of Manhattan hotels impose on their competitive environment. We derive and estimate a model that specifies how the attributes of managers’ own hotels and potential rival hotels influence their categorization of competing and non-competing hotels. We show that similarity in geographic location, price, and size are central to managers’ beliefs about the identity of their competitors, but that the weights they assign to these dimensions when categorizing competitors diverge from their influence on competitive outcomes, and indicate an overemphasis on geographic proximity. Although such categorization is commonly conceived as a rational process based on the assessment of similarities and differences, we suggest that significant distortions can occur in the categorization process and examine empirically how factors including managers’ attribution errors, cognitive limitations, and (in)experience lead them to make type I and type II competitor categorization errors and to frame competitive environments that are incomplete, erroneous, or even superstitious. Our findings suggest that understanding inter-firm competition may require greater attention being given to the cognitive foundations of competition.

Details

Geography and Strategy
Type: Book
ISBN: 978-0-76231-034-0

Book part
Publication date: 17 November 2010

Rolando Quintana and Mark T. Leung

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process…

Abstract

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Details

Advances in Business and Management Forecasting
Type: Book
ISBN: 978-0-85724-201-3

Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-7656-1305-9

Article
Publication date: 23 November 2021

Hanqing Gong, Lingling Shi, Xiang Zhai, Yimin Du and Zhijing Zhang

The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.

Abstract

Purpose

The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.

Design/methodology/approach

By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.

Findings

By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.

Originality/value

The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.

Details

Assembly Automation, vol. 42 no. 1
Type: Research Article
ISSN: 0144-5154

Keywords

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