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Article
Publication date: 1 February 1982

M. CAYROL, H. FARRENY and H. PRADE

Pattern‐directed inference systems (P.D.I.S.) are among the most largely used tools in A.I. to‐day in order to represent and exploit knowledge. Generally, P.D.I.S.'s use…

Abstract

Pattern‐directed inference systems (P.D.I.S.) are among the most largely used tools in A.I. to‐day in order to represent and exploit knowledge. Generally, P.D.I.S.'s use production rules triggered by matching between rule patterns and elements of the data base. However, the lack of flexibility in the matching remains a drawback in this kind of system. In the framework of the communication in natural language with robots, approximate descriptions of real world situations and approximately specified rules are needed; furthermore, similarity in the matching process does not always need to be perfect. Thus, the pervading fuzziness of natural language can be taken into account. The following levels, belonging to the real interval [0,1], are evaluated: The possibility of similarity between referents designated in the data and in the pattern respectively; the necessity that a referent designated in the data is similar to a referent designated in the pattern. Designations are fuzzy when the pattern or the data are fuzzy, which is usual with words of a natural language.

Details

Kybernetes, vol. 11 no. 2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 2 March 2012

Helmut Nechansky

The purpose of this paper is to analyze how sequence learning can build on pattern‐recognition systems and how it can contribute to the behavioral options of goal‐oriented systems.

Abstract

Purpose

The purpose of this paper is to analyze how sequence learning can build on pattern‐recognition systems and how it can contribute to the behavioral options of goal‐oriented systems.

Design/methodology/approach

A functional approach is used to develop the necessary cybernetic structures of a subsystem for sequence learning, that can recognize patterns, register patterns occurring repeatedly and connect these to sequences. Based on that it is analyzed how goal‐oriented systems can use information about reoccurring sequences.

Findings

A subsystem for sequence learning basically requires pattern recognition and it needs a structure for the directed connection of single standards for pattern matching to standards for sequences, given that it can learn both new patterns and new sequences. Such a subsystem for sequence learning may recognize a certain pattern and with that the end of a certain sequence. So it may deliver more than one output signal at a point in time, and therefore needs additionally a subsystem for directing attention.

Practical implications

The paper analyses the principles of an “associative” way of connecting standards for pattern matching to standards for sequences. Also it shows the cybernetic necessity of an attention directing system that has to decide how to deal with the multiple outputs of a subsystem for sequence learning, i.e. to decide to act either towards a pattern or a whole sequence.

Originality/value

The paper investigates basic mechanisms of sequence learning and its contribution to goal‐oriented behavior. Also, it lays the base for an analysis of attention directing systems and anticipatory systems.

Details

Kybernetes, vol. 41 no. 1/2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 30 January 2015

Philipp Bergener, Patrick Delfmann, Burkhard Weiss and Axel Winkelmann

Automating the task of identifying process weaknesses using process models is promising, as many organizations have to manage a large amount of process models. The purpose…

Abstract

Purpose

Automating the task of identifying process weaknesses using process models is promising, as many organizations have to manage a large amount of process models. The purpose of this paper is to introduce a pattern-based approach for automatically detecting potential process weaknesses in semantic process models, thus supporting the task of business process improvement.

Design/methodology/approach

Based on design research, combined with a case study, the authors explore the design, application and evaluation of a pattern-based process weakness detection approach within the setting of a real-life case study in a German bank.

Findings

Business process weakness detection can be automated to a remarkable extent using pattern matching and a semantic business process modeling language. A case study provided evidence that such an approach highly supports business process analysts.

Research limitations/implications

The presented approach is limited by the fact that not every potential process weakness detected by pattern matching is really a weakness but just gives the impression to be one. Hence, after detecting a weakness, analysts still have to decide on its authenticity.

Practical implications

Applying weakness patterns to semantic process models via pattern matching allows organizations to automatically and efficiently identify process improvement potentials. Hence, this research helps to avoid time- and resource-consuming manual analysis of process model landscapes.

Originality/value

The approach is not restricted to a single modeling language. Furthermore, by applying the pattern matching approach to a semantic modeling language, the authors avoid ambiguous search results. A case study proves the usefulness of the approach.

Details

Business Process Management Journal, vol. 21 no. 1
Type: Research Article
ISSN: 1463-7154

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Article
Publication date: 27 April 2012

Helmut Nechansky

The purpose of this paper is to analyze how pattern recognition can contribute to the behavioral options of a goal‐oriented system.

Abstract

Purpose

The purpose of this paper is to analyze how pattern recognition can contribute to the behavioral options of a goal‐oriented system.

Design/methodology/approach

A functional approach is used to develop the necessary cybernetic structures of a pattern recognition unit that can store observations as new standards for pattern matching by itself and can later apply them to recognize patterns in incoming sensor data.

Findings

Combining such a structure for pattern recognition with a feedback system shows that the resulting system can only deal with known patterns. To deal with novel patterns this structure has to be added to an adaptive system that can develop system‐specific behavior. Such a system has to able to initiate a trial and error process to test new behavior towards new patterns and to evaluate its effect on the highest, existential goal‐values of the system.

Practical implications

A system with a pattern recognition unit that can set new standards for pattern matching by itself is identified as the point of departure where not‐programmable and unpredictable individual behavior starts. Dealing with newly‐recognized pattern requires individual behavioral solutions and a system‐specific evaluation of the achieved results in relation to the highest goal‐values of the system. Here internal “emotional” criteria to select behavior emerge as a cybernetic necessity.

Originality/value

The paper is the third in a series of three on a cybernetic theory distinguishing system capable of pre‐programmed adaptation, system‐specific adaptation and learning. It determines the cybernetic starting point of individual psychology.

Details

Kybernetes, vol. 41 no. 3/4
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 20 February 2009

Chern‐Sheng Lin, Kuo‐Chun Wu, Yun‐Long Lay, Chi‐Chin Lin and Jim‐Min Lin

The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and…

Abstract

Purpose

The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the existing control system, the double aligner mark searching time is decreased to reduce the working time of the integrated system.

Design/methodology/approach

The improved pattern matching method of genetic algorithm was adopted, including setting for template image selecting, encoding, calculating fitness function, pattern matching, template generating and genetic algorithm steps. The predetermined pixels were selected from the target template based on the minimum difference to the block image to be tested by utilizing the genetic algorithm, and the other pixels which have not been selected were neglected.

Findings

The selected pixels were encoded for recording by sequence mode, and then the target template and the image to be tested were compared based on the calculated fitness function. This method has the advantages of using the fitness function to reduce the searching time, with the help of genetic algorithm to find the optimal target template, and saving memory space by recording target template based on the sequence mode.

Research limitations/implications

The genetic algorithm used in this study is a kind of optimal tool free from gradient data. As long as the fitness function and after continuous iteration are determined, the optimal solution can be found out, and then the optimal target template can be generated.

Practical implications

This system uses fitness function to reduce the pattern matching time. Plural pixels are preset inside the target template, and its fitness function value is calculated. When the target template is compared with the image to be tested, only the fitness function value (also the difference of the plural pixels) is calculated and compared.

Originality/value

The remaining pixels are neglected, so that the searching time can be reduced greatly. The sequence mode is used to save the required memory space for recording target template. Since sequence mode is adopted to record the information of selected pixels, lots of required memory space for recording target template information will be saved.

Details

Assembly Automation, vol. 29 no. 1
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 28 August 2009

Zhewei Jiang, Cheng Luo, Wen‐Chi Hou, Dunren Che and Qiang Zhu

The purpose of this paper is to provide an efficient algorithm for Extensible Markup Language (XML) twig query evaluation.

Abstract

Purpose

The purpose of this paper is to provide an efficient algorithm for Extensible Markup Language (XML) twig query evaluation.

Design/methodology/approach

A single‐phase holistic twig pattern matching method based on the TwigStack algorithm is proposed. The method applies a novel stack structure to preserve the holisticity of the twig matches. Twig matches rooted at elements that are currently in the root stack are output directly.

Findings

Without generating individual path matches as intermediate results, the method is able to avoid the storage and output/input of the individual path matches, and totally eliminate the potentially time‐consuming merging operation. Experimental results demonstrate the applicability and advantages of our approach.

Originality/value

The paper proposes an efficient XML twig query evaluation algorithm, which by both theoretical analyses and empirical studies demonstrates its advantages over the current state‐of‐the‐art algorithm TwigStack.

Details

International Journal of Web Information Systems, vol. 5 no. 3
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 27 March 2009

Hadi Grailu, Mojtaba Lotfizad and Hadi Sadoghi‐Yazdi

The purpose of this paper is to propose a lossy/lossless binary textual image compression method based on an improved pattern matching (PM) technique.

Abstract

Purpose

The purpose of this paper is to propose a lossy/lossless binary textual image compression method based on an improved pattern matching (PM) technique.

Design/methodology/approach

In the Farsi/Arabic script, contrary to the printed Latin script, letters usually attach together and produce various patterns. Hence, some patterns are fully or partially subsets of some others. Two new ideas are proposed here. First, the number of library prototypes is reduced by detecting and then removing the fully or partially similar prototypes. Second, a new effective pattern encoding scheme is proposed for all types of patterns including text and graphics. The new encoding scheme has two operation modes of chain coding and soft PM, depending on the ratio of the pattern area to its chain code effective length. In order to encode the number sequences, the authors have modified the multi‐symbol QM‐coder. The proposed method has three levels for the lossy compression. Each level, in its turn, further increases the compression ratio. The first level includes applying some processing in the chain code domain such as omission of small patterns and holes, omission of inner holes of characters, and smoothing the boundaries of the patterns. The second level includes the selective pixel reversal technique, and the third level includes using the proposed method of prioritizing the residual patterns for encoding, with respect to their degree of compactness.

Findings

Experimental results show that the compression performance of the proposed method is considerably better than that of the best existing binary textual image compression methods as high as 1.6‐3 times in the lossy case and 1.3‐2.4 times in the lossless case at 300 dpi. The maximum compression ratios are achieved for Farsi and Arabic textual images.

Research limitations/implications

Only the binary printed typeset textual images are considered.

Practical implications

The proposed method has a high‐compression ratio for archiving and storage applications.

Originality/value

To the authors' best knowledge, the existing textual image compression methods or standards have not so far exploited the property of full or partial similarity of prototypes for increasing the compression ratio for any scripts. Also, the idea of combining the boundary description methods with the run‐length and arithmetic coding techniques has not so far been used.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 2 no. 1
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 1 February 2013

Helmut Nechansky

The purpose of this paper is to analyze how elementary anticipation, understood as anticipation of the repetition of one known pattern, can emerge out of sequence learning…

Abstract

Purpose

The purpose of this paper is to analyze how elementary anticipation, understood as anticipation of the repetition of one known pattern, can emerge out of sequence learning and how it can contribute to the behavioral options of goal‐oriented systems.

Design/methodology/approach

A functional approach is used to develop the necessary cybernetic structures of a subsystem for sequence learning that can additionally provide standards of anticipated patterns for future pattern matching. Based on that it is analyzed, how a goal‐oriented system can use the information about the actual occurrence of an anticipated pattern.

Findings

A subsystem for elementary anticipation of single patterns builds on sequence learning and requires additionally a structure: first, to unequivocally identify the beginning of known sequences just from their first patterns; and second, to decide to use a latter pattern of such a sequence as standard for an anticipated pattern. Deciding to actually use such a pattern for anticipation requires an additional subsystem to switch between the feedback pattern recognition mode and feedforward. Then the occurrence of such an anticipated pattern allows immediate recognition and action.

Practical implications

The paper shows a necessary evolution of cybernetic structures from pattern recognition via sequence learning to anticipation; and it shows, too, a necessary evolution in the cognitive development of individual systems. In the simple anticipatory structures analyzed here, only known patterns, that are part of a known sequence, can become anticipated patterns.

Originality/value

The paper places elementary anticipation of single patterns in an evolutionary development based on pattern recognition and sequence learning. It provides the base to analyze more complex forms of anticipation.

Details

Kybernetes, vol. 42 no. 2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 March 1988

D.J. Evans and S. Ghanemi

The string searching problem is central to many information retrieval and text editing applications. The Brute Force algorithm is inefficient in some cases and in this…

Abstract

The string searching problem is central to many information retrieval and text editing applications. The Brute Force algorithm is inefficient in some cases and in this article four other algorithms are discussed, of which the Boyer‐Moore and the Improved Boyer‐Moore are found to be the fastest. A parallel implementation using the divide and conquer method is examined. Comparisons using the MIMD‐type parallel computer systems are presented.

Details

Kybernetes, vol. 17 no. 3
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 5 November 2018

Sisay Adugna Chala, Fazel Ansari, Madjid Fathi and Kea Tijdens

The purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker…

Abstract

Purpose

The purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker qualifications and skills, against the vacancy provided by employers or job-agents.

Design/methodology/approach

The paper presents a framework of bidirectional jobseeker-to-vacancy matching system. Using occupational data from various sources such as the WageIndicator web survey, International Standard Classification of Occupations, European Skills, Competences, Qualifications, and Occupations as well as vacancy data from various open access internet sources and job seekers information from social networking sites, the authors apply machine learning techniques for bidirectional matching of job vacancies and occupational standards to enhance the contents of job vacancies and job seekers profiles. The authors also apply bidirectional matching of job seeker profiles and vacancies, i.e., semantic matching vacancies to job seekers and vice versa in the individual level. Moreover, data from occupational standards and social networks were utilized to enhance the relevance (i.e. degree of similarity) of job vacancies and job seekers, respectively.

Findings

The paper provides empirical insights of increase in job vacancy advertisements on the selected jobs – Internet of Things – with respect to other job vacancies, and identifies the evolution of job profiles and its effect on job vacancies announcements in the era of Industry 4.0. In addition, the paper shows the gap between job seeker interests and available jobs in the selected job area.

Research limitations/implications

Due to limited data about jobseekers, the research results may not guarantee high quality of recommendation and maturity of matching results. Therefore, further research is required to test if the proposed system works for other domains as well as more diverse data sets.

Originality/value

The paper demonstrates how online jobseeker-to-vacancy matching can be improved by use of semantic technology and the integration of occupational standards, web survey data, and social networking data into user profile collection and matching.

Details

International Journal of Manpower, vol. 39 no. 8
Type: Research Article
ISSN: 0143-7720

Keywords

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