Pub Date : 2021-02-01DOI: 10.1142/s2196888821500020
Jan Treur
In this paper, the challenge for dynamic network modeling is addressed how emerging behavior of an adaptive network can be related to characteristics of the adaptive network’s structure. By applying network reification, the adaptation structure is modeled in a declarative manner as a subnetwork of a reified network extending the base network. This construction can be used to model and analyze any adaptive network in a neat and declarative manner, where the adaptation principles are described by declarative mathematical relations and functions in reified temporal-causal network format. In different examples, it is shown how certain adaptation principles known from the literature can be formulated easily in such a declarative reified temporal-causal network format. The main focus of this paper on how emerging adaptive network behavior relates to network structure is addressed, among others, by means of a number of theorems of the format “properties of reified network structure characteristics imply emerging adaptive behavior properties”. In such theorems, classes of networks are considered that satisfy certain network structure properties concerning connectivity and aggregation characteristics. Results include, for example, that under some conditions on the network structure characteristics, all states eventually get the same value. Similar analysis methods are applied to reification states, in particular for adaptation principles for Hebbian learning and for bonding by homophily, respectively. Here results include how certain properties of the aggregation characteristics of the network structure of the reified network for Hebbian learning entail behavioral properties relating to the maximal final values of the adaptive connection weights. Similarly, results are discussed on how properties of the aggregation characteristics of the reified network structure for bonding by homophily entail behavioral properties relating to clustering and community formation in a social network.
{"title":"Relating Emerging Adaptive Network Behavior to Network Structure: A Declarative Network Analysis Perspective","authors":"Jan Treur","doi":"10.1142/s2196888821500020","DOIUrl":"https://doi.org/10.1142/s2196888821500020","url":null,"abstract":"In this paper, the challenge for dynamic network modeling is addressed how emerging behavior of an adaptive network can be related to characteristics of the adaptive network’s structure. By applying network reification, the adaptation structure is modeled in a declarative manner as a subnetwork of a reified network extending the base network. This construction can be used to model and analyze any adaptive network in a neat and declarative manner, where the adaptation principles are described by declarative mathematical relations and functions in reified temporal-causal network format. In different examples, it is shown how certain adaptation principles known from the literature can be formulated easily in such a declarative reified temporal-causal network format. The main focus of this paper on how emerging adaptive network behavior relates to network structure is addressed, among others, by means of a number of theorems of the format “properties of reified network structure characteristics imply emerging adaptive behavior properties”. In such theorems, classes of networks are considered that satisfy certain network structure properties concerning connectivity and aggregation characteristics. Results include, for example, that under some conditions on the network structure characteristics, all states eventually get the same value. Similar analysis methods are applied to reification states, in particular for adaptation principles for Hebbian learning and for bonding by homophily, respectively. Here results include how certain properties of the aggregation characteristics of the network structure of the reified network for Hebbian learning entail behavioral properties relating to the maximal final values of the adaptive connection weights. Similarly, results are discussed on how properties of the aggregation characteristics of the reified network structure for bonding by homophily entail behavioral properties relating to clustering and community formation in a social network.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124539696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.1142/s2196888821300015
P. Jain, A. Vaidya
With the ever-growing number of online social media platforms, the world has shrunk even further with regards to communication and knowledge-sharing perspective. However, communication, at times, c...
随着网络社交媒体平台的不断增加，世界在交流和知识共享方面进一步缩小。然而，沟通，有时，c…
{"title":"Analysis of Social Media Based on Terrorism - A Review","authors":"P. Jain, A. Vaidya","doi":"10.1142/s2196888821300015","DOIUrl":"https://doi.org/10.1142/s2196888821300015","url":null,"abstract":"With the ever-growing number of online social media platforms, the world has shrunk even further with regards to communication and knowledge-sharing perspective. However, communication, at times, c...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122372689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.1142/s2196888821500056
Munqath Alattar, A. Sali
In general, there are two main approaches to handle the missing data values problem in SQL tables. One is to ignore or remove any record with some missing data values. The other approach is to fill or impute the missing data with new values [A. Farhangfar, L. A. Kurgan and W. Pedrycz, A novel framework for imputation of missing values in databases, IEEE Trans. Syst. Man Cybern. A, Syst. Hum. 37(5) (2007) 692–709]. In this paper, the second method is considered. Possible worlds, possible and certain keys, and weak and strong functional dependencies were introduced in Refs. 4 and 2 [H. Köhler, U. Leck, S. Link and X. Zhou, Possible and certain keys for SQL, VLDB J. 25(4) (2016) 571–596; M. Levene and G. Loizou, Axiomatisation of functional dependencies in incomplete relations, Theor. Comput. Sci. 206(1) (1998) 283–300]. We introduced the intermediate concept of strongly possible worlds in a preceding paper, which are obtained by filling missing data values with values already existing in the table. Using strongly possible worlds, strongly possible keys and strongly possible functional dependencies (spFDs) were introduced in Refs. 5 and 1 [M. Alattar and A. Sali, Keys in relational databases with nulls and bounded domains, in ADBIS 2019: Advances in Databases and Information Systems, Lecture Notes in Computer Science, Vol. 11695 (Springer, Cham, 2019), pp. 33–50; Functional dependencies in incomplete databases with limited domains, in FoiKS 2020: Foundations of Information and Knowledge Systems, Lecture Notes in Computer Science, Vol. 12012 (Springer, Cham, 2020), pp. 1–21]. In this paper, some axioms and rules for strongly possible functional dependencies are provided, These axioms and rules form the basis for a possible axiomatization of spFDs. For that, we analyze which weak/strong functional dependency and certain functional dependency axioms remain sound for strongly possible functional dependencies, and for the axioms that are not sound, we give appropriate modifications for soundness.
{"title":"Toward an Axiomatization of Strongly Possible Functional Dependencies","authors":"Munqath Alattar, A. Sali","doi":"10.1142/s2196888821500056","DOIUrl":"https://doi.org/10.1142/s2196888821500056","url":null,"abstract":"In general, there are two main approaches to handle the missing data values problem in SQL tables. One is to ignore or remove any record with some missing data values. The other approach is to fill or impute the missing data with new values [A. Farhangfar, L. A. Kurgan and W. Pedrycz, A novel framework for imputation of missing values in databases, IEEE Trans. Syst. Man Cybern. A, Syst. Hum. 37(5) (2007) 692–709]. In this paper, the second method is considered. Possible worlds, possible and certain keys, and weak and strong functional dependencies were introduced in Refs. 4 and 2 [H. Köhler, U. Leck, S. Link and X. Zhou, Possible and certain keys for SQL, VLDB J. 25(4) (2016) 571–596; M. Levene and G. Loizou, Axiomatisation of functional dependencies in incomplete relations, Theor. Comput. Sci. 206(1) (1998) 283–300]. We introduced the intermediate concept of strongly possible worlds in a preceding paper, which are obtained by filling missing data values with values already existing in the table. Using strongly possible worlds, strongly possible keys and strongly possible functional dependencies (spFDs) were introduced in Refs. 5 and 1 [M. Alattar and A. Sali, Keys in relational databases with nulls and bounded domains, in ADBIS 2019: Advances in Databases and Information Systems, Lecture Notes in Computer Science, Vol. 11695 (Springer, Cham, 2019), pp. 33–50; Functional dependencies in incomplete databases with limited domains, in FoiKS 2020: Foundations of Information and Knowledge Systems, Lecture Notes in Computer Science, Vol. 12012 (Springer, Cham, 2020), pp. 1–21]. In this paper, some axioms and rules for strongly possible functional dependencies are provided, These axioms and rules form the basis for a possible axiomatization of spFDs. For that, we analyze which weak/strong functional dependency and certain functional dependency axioms remain sound for strongly possible functional dependencies, and for the axioms that are not sound, we give appropriate modifications for soundness.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126082954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.1142/S2196888821500068
S. Mandal, Pritam Ghosh, N. Shit, D. Hajra, S. Banik
Various training algorithms are used in artificial neural networks for updating the weights during training the network. But, the selection of the appropriate training algorithm is dependent on the...
人工神经网络在训练过程中使用各种训练算法来更新权值。但是，选择合适的训练算法取决于…
{"title":"A Framework for Selection of Training Algorithm of Neuro-Statistic Model for Prediction of Pig Breeds in India","authors":"S. Mandal, Pritam Ghosh, N. Shit, D. Hajra, S. Banik","doi":"10.1142/S2196888821500068","DOIUrl":"https://doi.org/10.1142/S2196888821500068","url":null,"abstract":"Various training algorithms are used in artificial neural networks for updating the weights during training the network. But, the selection of the appropriate training algorithm is dependent on the...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128107305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.1142/s2196888821500032
Péter Marjai, A. Kiss
For decades, centrality has been one of the most studied concepts in the case of complex networks. It addresses the problem of identification of the most influential nodes in the network. Despite the large number of the proposed methods for measuring centrality, each method takes different characteristics of the networks into account while identifying the “vital” nodes, and for the same reason, each has its advantages and drawbacks. To resolve this problem, the TOPSIS method combined with relative entropy can be used. Several of the already existing centrality measures have been developed to be effective in the case of static networks, however, there is an ever-increasing interest to determine crucial nodes in dynamic networks. In this paper, we are investigating the performance of a new method that identifies influential nodes based on relative entropy, in the case of dynamic networks. To classify the effectiveness, the Suspected-Infected model is used as an information diffusion process. We are investigating the average infection capacity of ranked nodes, the Time-Constrained Coverage as well as the Cover Time.
{"title":"Influential Performance of Nodes Identified by Relative Entropy in Dynamic Networks","authors":"Péter Marjai, A. Kiss","doi":"10.1142/s2196888821500032","DOIUrl":"https://doi.org/10.1142/s2196888821500032","url":null,"abstract":"For decades, centrality has been one of the most studied concepts in the case of complex networks. It addresses the problem of identification of the most influential nodes in the network. Despite the large number of the proposed methods for measuring centrality, each method takes different characteristics of the networks into account while identifying the “vital” nodes, and for the same reason, each has its advantages and drawbacks. To resolve this problem, the TOPSIS method combined with relative entropy can be used. Several of the already existing centrality measures have been developed to be effective in the case of static networks, however, there is an ever-increasing interest to determine crucial nodes in dynamic networks. In this paper, we are investigating the performance of a new method that identifies influential nodes based on relative entropy, in the case of dynamic networks. To classify the effectiveness, the Suspected-Infected model is used as an information diffusion process. We are investigating the average infection capacity of ranked nodes, the Time-Constrained Coverage as well as the Cover Time.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130608889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.1142/s2196888821500044
Ridouane Tachicart, Karim Bouzoubaa
With the increase of Web use in Morocco today, Internet has become an important source of information. Specifically, across social media, the Moroccan people use several languages in their communication leaving behind unstructured user-generated text (UGT) that presents several opportunities for Natural Language Processing. Among the languages found in this data, Moroccan Arabic (MA) stands with an important content and several features. In this paper, we investigate online written text generated by Moroccan users in social media with an emphasis on Moroccan Arabic. For this purpose, we follow several steps, using some tools such as a language identification system, in order to conduct a deep study of this data. The most interesting findings that have emerged are the use of code-switching, multi-script and low amount of words in the Moroccan UGT. Moreover, we used the investigated data in order to build a new Moroccan language resource. The latter consists in building a Moroccan words orthographic variants lexicon following an unsupervised approach and using character neural embedding. This lexicon can be useful for several NLP tasks such as spelling normalization.
{"title":"Moroccan Data-Driven Spelling Normalization Using Character Neural Embedding","authors":"Ridouane Tachicart, Karim Bouzoubaa","doi":"10.1142/s2196888821500044","DOIUrl":"https://doi.org/10.1142/s2196888821500044","url":null,"abstract":"With the increase of Web use in Morocco today, Internet has become an important source of information. Specifically, across social media, the Moroccan people use several languages in their communication leaving behind unstructured user-generated text (UGT) that presents several opportunities for Natural Language Processing. Among the languages found in this data, Moroccan Arabic (MA) stands with an important content and several features. In this paper, we investigate online written text generated by Moroccan users in social media with an emphasis on Moroccan Arabic. For this purpose, we follow several steps, using some tools such as a language identification system, in order to conduct a deep study of this data. The most interesting findings that have emerged are the use of code-switching, multi-script and low amount of words in the Moroccan UGT. Moreover, we used the investigated data in order to build a new Moroccan language resource. The latter consists in building a Moroccan words orthographic variants lexicon following an unsupervised approach and using character neural embedding. This lexicon can be useful for several NLP tasks such as spelling normalization.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133881712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1142/S2196888821500184
Christine Dewi, Rung-Ching Chen, Hsiu-Te Hung
Restricted Boltzmann machine (RBM) plays an important role in current deep learning techniques, as most of the existing deep networks are based on or related to generative models and image classifi...
{"title":"Experiment Improvement of Restricted Boltzmann Machine Methods for Image Classification","authors":"Christine Dewi, Rung-Ching Chen, Hsiu-Te Hung","doi":"10.1142/S2196888821500184","DOIUrl":"https://doi.org/10.1142/S2196888821500184","url":null,"abstract":"Restricted Boltzmann machine (RBM) plays an important role in current deep learning techniques, as most of the existing deep networks are based on or related to generative models and image classifi...","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114892374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-21DOI: 10.1142/s219688882150024x
Chuangtao Ma, B. Molnár
Along with the rapidly growing scale of relational database (RDB), how to construct domain-related ontologies from various databases effectively and efficiently has been a bottleneck of the ontology-based integration. The traditional methods for constructing ontology from RDB are mainly based on the manual mapping and transformation, which not only requires a lot of human experience but also easily leads to the semantic loss during the transformation. Ontology learning from RDB is a new paradigm to (semi-)automatically construct ontologies from RDB by borrowing the techniques of machine learning, it provides potential opportunities for integrating heterogeneous data from various data sources efficiently. This paper surveys the recent methods and tools of the ontology learning from RDB, and highlights the potential opportunities and challenges of using ontology learning in semantic information integration. Initially, the previous surveys on the topic of the ontology-based integration and ontology learning were summarized, and then the limitations of previous surveys were identified and analyzed. Furthermore, the methods and techniques of ontology learning from RDB were investigated by classifying into three categories: reverse engineering, mapping, and machine learning. Accordingly, the opportunities and possibility of using ontology learning from RDB in semantic information integration were discussed based on the mapping results between the bottlenecks of ontology-based integration and the features of ontology learning. a
{"title":"Ontology Learning from Relational Database: Opportunities for Semantic Information Integration","authors":"Chuangtao Ma, B. Molnár","doi":"10.1142/s219688882150024x","DOIUrl":"https://doi.org/10.1142/s219688882150024x","url":null,"abstract":"Along with the rapidly growing scale of relational database (RDB), how to construct domain-related ontologies from various databases effectively and efficiently has been a bottleneck of the ontology-based integration. The traditional methods for constructing ontology from RDB are mainly based on the manual mapping and transformation, which not only requires a lot of human experience but also easily leads to the semantic loss during the transformation. Ontology learning from RDB is a new paradigm to (semi-)automatically construct ontologies from RDB by borrowing the techniques of machine learning, it provides potential opportunities for integrating heterogeneous data from various data sources efficiently. This paper surveys the recent methods and tools of the ontology learning from RDB, and highlights the potential opportunities and challenges of using ontology learning in semantic information integration. Initially, the previous surveys on the topic of the ontology-based integration and ontology learning were summarized, and then the limitations of previous surveys were identified and analyzed. Furthermore, the methods and techniques of ontology learning from RDB were investigated by classifying into three categories: reverse engineering, mapping, and machine learning. Accordingly, the opportunities and possibility of using ontology learning from RDB in semantic information integration were discussed based on the mapping results between the bottlenecks of ontology-based integration and the features of ontology learning. a","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128958756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-11DOI: 10.1142/s2196888821500251
P. Stefaniak, S. Anufriiev, Artur Skoczlas, Bartosz Jachnik, P. Śliwiński
For many years now, the mining industry has seen a boost in exploring and developing the systems for monitoring operational parameters of mining machines, in particular load-haul-dump machines. Therefore, further researches on algorithmics have also advanced dynamically regarding effective performance management as well as predictive maintenance. Nonetheless, the issue of road conditions is still being neglected. That issue has a substantial impact on both the overall operator’s convenience, their performance, and machinery reliability, especially its construction node and tire damages. Moreover, such negligence pertains also to the maintenance of mine infrastructure, including the network of passages. The paper explains the use of the portable inertial measurement unit (IMU) in evaluating road conditions in the deep underground mine. The detailed descriptions of the road quality classification procedure and bump detection have been included. The paper outlines the basic method of tracking the motion trajectory of vehicles and suggests the method of visualization of the results of the road conditions evaluation. This paper covers the sample results collected by the measurements unit in the deep underground mine during six experiments. This paper is an extended version of a paper presented at the ACIIDs 2020 conference [P. Stefaniak, D. Gawelski, S. Anufriiev and P. Śliwiński, Road-quality classification and motion tracking with inertial sensors in the deep underground mine, Asian Conference on Intelligent Information and Database Systems, March 2020, Springer, Singapore, pp. 168–178].
{"title":"Method to Haulage Path Estimation and Road-Quality Assessment Using Inertial Sensors on LHD Machines","authors":"P. Stefaniak, S. Anufriiev, Artur Skoczlas, Bartosz Jachnik, P. Śliwiński","doi":"10.1142/s2196888821500251","DOIUrl":"https://doi.org/10.1142/s2196888821500251","url":null,"abstract":"For many years now, the mining industry has seen a boost in exploring and developing the systems for monitoring operational parameters of mining machines, in particular load-haul-dump machines. Therefore, further researches on algorithmics have also advanced dynamically regarding effective performance management as well as predictive maintenance. Nonetheless, the issue of road conditions is still being neglected. That issue has a substantial impact on both the overall operator’s convenience, their performance, and machinery reliability, especially its construction node and tire damages. Moreover, such negligence pertains also to the maintenance of mine infrastructure, including the network of passages. The paper explains the use of the portable inertial measurement unit (IMU) in evaluating road conditions in the deep underground mine. The detailed descriptions of the road quality classification procedure and bump detection have been included. The paper outlines the basic method of tracking the motion trajectory of vehicles and suggests the method of visualization of the results of the road conditions evaluation. This paper covers the sample results collected by the measurements unit in the deep underground mine during six experiments. This paper is an extended version of a paper presented at the ACIIDs 2020 conference [P. Stefaniak, D. Gawelski, S. Anufriiev and P. Śliwiński, Road-quality classification and motion tracking with inertial sensors in the deep underground mine, Asian Conference on Intelligent Information and Database Systems, March 2020, Springer, Singapore, pp. 168–178].","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116888458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-04DOI: 10.1142/s2196888821500160
B. Molnár, András Béleczki, Bence Sarkadi-Nagy
Data structures and especially the relationship among the data entities have changed in the last couple of years. The network-like graph representations of data-model are becoming more and more common nowadays, since they are more suitable to depict these, than the well-established relational data-model. The graphs can describe large and complex networks — like social networks — but also capable of storing rich information about complex data. This was mostly of relational data-model trait before. This also can be achieved with the use of the knowledge representation tool called “hypergraphs”. To utilize the possibilities of this model, we need a practical way to store and process hypergraphs. In this paper, we propose a way by which we can store hypergraphs model in the SAP HANA in-memory database system which has a “Graph Core” engine besides the relational data model. Graph Core has many graph algorithms by default however it is not capable to store or to work with hypergraphs neither are any of these algorithms specifically tailored for hypergraphs either. Hence in this paper, besides the case study of the two information systems, we also propose pseudo-code level algorithms to accommodate hypergraph semantics to process our IS model.
{"title":"Storing Hypergraph-Based Data Models in Non-Hypergraph Data Storage and Applications for Information Systems","authors":"B. Molnár, András Béleczki, Bence Sarkadi-Nagy","doi":"10.1142/s2196888821500160","DOIUrl":"https://doi.org/10.1142/s2196888821500160","url":null,"abstract":"Data structures and especially the relationship among the data entities have changed in the last couple of years. The network-like graph representations of data-model are becoming more and more common nowadays, since they are more suitable to depict these, than the well-established relational data-model. The graphs can describe large and complex networks — like social networks — but also capable of storing rich information about complex data. This was mostly of relational data-model trait before. This also can be achieved with the use of the knowledge representation tool called “hypergraphs”. To utilize the possibilities of this model, we need a practical way to store and process hypergraphs. In this paper, we propose a way by which we can store hypergraphs model in the SAP HANA in-memory database system which has a “Graph Core” engine besides the relational data model. Graph Core has many graph algorithms by default however it is not capable to store or to work with hypergraphs neither are any of these algorithms specifically tailored for hypergraphs either. Hence in this paper, besides the case study of the two information systems, we also propose pseudo-code level algorithms to accommodate hypergraph semantics to process our IS model.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116682560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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