Pub Date : 2019-11-06DOI: 10.1142/S2196888819500222
Chia-Hao Tu, Chunshien Li
This paper proposes an asymmetric complex fuzzy inference system (ACFIS) that improves a conventional fuzzy inference system (FIS) in two ways. First, the proposed model uses the novel neural-net-like aim–object parts, making the model flexible, in terms of model size of parameters and terse asymmetric structure. Second, the enhanced complex fuzzy sets (ECFSs) are used to expand membership degree from a single real-valued state to complex-valued vector state. Hence, the ACFIS can have the ability to predict multiple targets simultaneously. In addition, a hybrid learning algorithm, combining the particle swarm optimization (PSO) and the recursive least-square estimator (RLSE), is utilized to optimize the proposed model. To test the proposed approach, we did experimentation on four-function approximation using one single model only with 10 repeated trails. Based on the experimental results, the ACFIS has shown excellent performance.
{"title":"Multiple Function Approximation - A New Approach Using Asymmetric Complex Fuzzy Inference System","authors":"Chia-Hao Tu, Chunshien Li","doi":"10.1142/S2196888819500222","DOIUrl":"https://doi.org/10.1142/S2196888819500222","url":null,"abstract":"This paper proposes an asymmetric complex fuzzy inference system (ACFIS) that improves a conventional fuzzy inference system (FIS) in two ways. First, the proposed model uses the novel neural-net-like aim–object parts, making the model flexible, in terms of model size of parameters and terse asymmetric structure. Second, the enhanced complex fuzzy sets (ECFSs) are used to expand membership degree from a single real-valued state to complex-valued vector state. Hence, the ACFIS can have the ability to predict multiple targets simultaneously. In addition, a hybrid learning algorithm, combining the particle swarm optimization (PSO) and the recursive least-square estimator (RLSE), is utilized to optimize the proposed model. To test the proposed approach, we did experimentation on four-function approximation using one single model only with 10 repeated trails. Based on the experimental results, the ACFIS has shown excellent performance.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134357854","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 : 2019-10-25DOI: 10.1142/s2196888820500013
Shakil Ahmed Sumon, Raihan Goni, Niyaz Bin Hashem, Md. Tanzil Shahria, R. Rahman
In this paper, we have explored different strategies to find out the saliency of the features from different pretrained models in detecting violence in videos. A dataset has been created which consists of violent and non-violent videos of different settings. Three ImageNet models; VGG16, VGG19, ResNet50 are being used to extract features from the frames of the videos. In one of the experiments, the extracted features have been feed into a fully connected network which detects violence in frame level. Moreover, in another experiment, we have fed the extracted features of 30 frames to a long short-term memory (LSTM) network at a time. Furthermore, we have applied attention to the features extracted from the frames through spatial transformer network which also enables transformations like rotation, translation and scale. Along with these models, we have designed a custom convolutional neural network (CNN) as a feature extractor and a pretrained model which is initially trained on a movie violence dataset. In the end, the features extracted from the ResNet50 pretrained model proved to be more salient towards detecting violence. These ResNet50 features, in combination with LSTM provide an accuracy of 97.06% which is better than the other models we have experimented with.
{"title":"Violence Detection by Pretrained Modules with Different Deep Learning Approaches","authors":"Shakil Ahmed Sumon, Raihan Goni, Niyaz Bin Hashem, Md. Tanzil Shahria, R. Rahman","doi":"10.1142/s2196888820500013","DOIUrl":"https://doi.org/10.1142/s2196888820500013","url":null,"abstract":"In this paper, we have explored different strategies to find out the saliency of the features from different pretrained models in detecting violence in videos. A dataset has been created which consists of violent and non-violent videos of different settings. Three ImageNet models; VGG16, VGG19, ResNet50 are being used to extract features from the frames of the videos. In one of the experiments, the extracted features have been feed into a fully connected network which detects violence in frame level. Moreover, in another experiment, we have fed the extracted features of 30 frames to a long short-term memory (LSTM) network at a time. Furthermore, we have applied attention to the features extracted from the frames through spatial transformer network which also enables transformations like rotation, translation and scale. Along with these models, we have designed a custom convolutional neural network (CNN) as a feature extractor and a pretrained model which is initially trained on a movie violence dataset. In the end, the features extracted from the ResNet50 pretrained model proved to be more salient towards detecting violence. These ResNet50 features, in combination with LSTM provide an accuracy of 97.06% which is better than the other models we have experimented with.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128637536","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 : 2019-08-14DOI: 10.1142/S2196888819500106
Kacper Petrynski, I. Pozniak-Koszalka, L. Koszalka, A. Kasprzak
This paper concentrates on the newly improved algorithm for solving the single-machine total weighted tardiness (SMTWT) problem, called Algorithm Inspired by Tree and Sorting (AIT-S). The algorithm is based on searching the solution space along with the tree and sorting rules. The properties of the algorithm are studied taking into account the results of experiments made using the designed and implemented experimentation system. This system allows in tuning the parameters of the algorithm as well as to compare the effects obtained by AIT-S algorithm with effects of AIT algorithm, and known meta-heuristic algorithms. The paper shows that the proposed algorithm still requires some improvements, however, it seems to be promising.
{"title":"AIT-S for Single-Machine Weighted Tardiness Problem","authors":"Kacper Petrynski, I. Pozniak-Koszalka, L. Koszalka, A. Kasprzak","doi":"10.1142/S2196888819500106","DOIUrl":"https://doi.org/10.1142/S2196888819500106","url":null,"abstract":"This paper concentrates on the newly improved algorithm for solving the single-machine total weighted tardiness (SMTWT) problem, called Algorithm Inspired by Tree and Sorting (AIT-S). The algorithm is based on searching the solution space along with the tree and sorting rules. The properties of the algorithm are studied taking into account the results of experiments made using the designed and implemented experimentation system. This system allows in tuning the parameters of the algorithm as well as to compare the effects obtained by AIT-S algorithm with effects of AIT algorithm, and known meta-heuristic algorithms. The paper shows that the proposed algorithm still requires some improvements, however, it seems to be promising.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"104 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124159621","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 : 2019-08-14DOI: 10.1142/S2196888819500155
Thi Kim Thoa Ho, Quang Vu Bui, M. Bui
In this research, we exploit a novel approach for propagation processes on a network related to textual information by using topic modeling and pretopology theory. We first introduce the textual agent’s network in which each agent represents a node which contains specific properties, particularly the agent’s interest. Agent’s interest is illustrated through the topic’s probability distribution which is estimated based on textual information using topic modeling. Based on textual agent’s network, we proposed two information diffusion models. The first model, namely Textual-Homo-IC, is an expanded model of independent cascade model in which the probability of infection is formed on homophily that is measured based on agent’s interest similarity. In addition to expressing the Textual-Homo-IC model on the static network, we also reveal it on dynamic agent’s network where there is transformation of not only the structure but also the node’s properties during the spreading process. We conducted experiments on two collected datasets from NIPS and a social network platform, Twitter, and have attained satisfactory results. On the other hand, we continue to exploit the dissemination process on a multi-relational agent’s network by integrating the pseudo-closure function from pretopology theory to the cascade model. By using pseudo-closure or stochastic pseudo-closure functions to define the set of neighbors, we can capture more complex kind of neighbors of a set. In this study, we propose the second model, namely Textual-Homo-PCM, an expanded model of pretopological cascade model, a general model for information diffusion process that can take place in more complex networks such as multi-relational networks or stochastic graphs. In Textual-Homo-PCM, pretopology theory will be applied to determine the neighborhood set on multi-relational agent’s network through pseudo-closure functions. Besides, threshold rule based on homophily will be used for activation. Experiments are implemented for simulating Textual-Homo-PCM and we obtained expected results. The work in this paper is an extended version of our paper [T. K. T. Ho, Q. V. Bui and M. Bui, Homophily independent cascade diffusion model based on textual information, in Computational Collective Intelligence, eds. N. T. Nguyen, E. Pimenidis, Z. Khan and B. Trawiski, Lecture Notes in Computer Science, Vol. 11055 (Springer International Publishing, 2018), pp. 134–145] presented in ICCCI 2018 conference.
在本研究中，我们利用主题建模和预拓扑理论开发了一种新的方法来处理与文本信息相关的网络传播过程。我们首先介绍文本代理网络，其中每个代理代表一个包含特定属性的节点，特别是代理的兴趣。通过主题的概率分布来说明Agent的兴趣，该概率分布是基于文本信息，使用主题建模来估计的。基于文本智能体网络，提出了两种信息扩散模型。第一个模型是text - homoo - ic，它是独立级联模型的扩展模型，在该模型中，基于agent的兴趣相似性度量的同质性形成感染的概率。除了在静态网络上表达text - homo - ic模型外，我们还在动态智能体网络上展示了该模型，其中在传播过程中不仅存在结构的变化，而且存在节点属性的变化。我们在NIPS和社交网络平台Twitter上收集了两个数据集，并进行了实验，得到了满意的结果。另一方面，我们通过将预拓扑理论的伪闭包函数与级联模型相结合，继续探索多关系智能体网络上的传播过程。通过使用伪闭包函数或随机伪闭包函数来定义邻域集，我们可以捕获集合中更复杂类型的邻域。在本研究中，我们提出了第二种模型，即text - homo - pcm，这是一种扩展的预拓扑级联模型，是一种可以在更复杂的网络(如多关系网络或随机图)中发生的信息扩散过程的一般模型。在text - homo - pcm中，预拓扑理论将通过伪闭包函数来确定多关系智能体网络上的邻域集。并采用基于同态性的阈值规则进行激活。进行了模拟文本-同源- pcm的实验，取得了预期的结果。本文的工作是我们的论文[T。何国栋，基于文本信息的同质无关级联扩散模型，计算集体智能，编。N. T. Nguyen, E. Pimenidis, Z. Khan和B. Trawiski，《计算机科学讲义》，Vol. 11055(施普林格International Publishing, 2018)， pp. 134-145]在ICCCI 2018年会议上发表。
{"title":"Information Diffusion on Complex Networks: A Novel Approach Based on Topic Modeling and Pretopology Theory","authors":"Thi Kim Thoa Ho, Quang Vu Bui, M. Bui","doi":"10.1142/S2196888819500155","DOIUrl":"https://doi.org/10.1142/S2196888819500155","url":null,"abstract":"In this research, we exploit a novel approach for propagation processes on a network related to textual information by using topic modeling and pretopology theory. We first introduce the textual agent’s network in which each agent represents a node which contains specific properties, particularly the agent’s interest. Agent’s interest is illustrated through the topic’s probability distribution which is estimated based on textual information using topic modeling. Based on textual agent’s network, we proposed two information diffusion models. The first model, namely Textual-Homo-IC, is an expanded model of independent cascade model in which the probability of infection is formed on homophily that is measured based on agent’s interest similarity. In addition to expressing the Textual-Homo-IC model on the static network, we also reveal it on dynamic agent’s network where there is transformation of not only the structure but also the node’s properties during the spreading process. We conducted experiments on two collected datasets from NIPS and a social network platform, Twitter, and have attained satisfactory results. On the other hand, we continue to exploit the dissemination process on a multi-relational agent’s network by integrating the pseudo-closure function from pretopology theory to the cascade model. By using pseudo-closure or stochastic pseudo-closure functions to define the set of neighbors, we can capture more complex kind of neighbors of a set. In this study, we propose the second model, namely Textual-Homo-PCM, an expanded model of pretopological cascade model, a general model for information diffusion process that can take place in more complex networks such as multi-relational networks or stochastic graphs. In Textual-Homo-PCM, pretopology theory will be applied to determine the neighborhood set on multi-relational agent’s network through pseudo-closure functions. Besides, threshold rule based on homophily will be used for activation. Experiments are implemented for simulating Textual-Homo-PCM and we obtained expected results. The work in this paper is an extended version of our paper [T. K. T. Ho, Q. V. Bui and M. Bui, Homophily independent cascade diffusion model based on textual information, in Computational Collective Intelligence, eds. N. T. Nguyen, E. Pimenidis, Z. Khan and B. Trawiski, Lecture Notes in Computer Science, Vol. 11055 (Springer International Publishing, 2018), pp. 134–145] presented in ICCCI 2018 conference.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133600998","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 : 2019-08-14DOI: 10.1142/S2196888819500167
N. R. Rahman, Md. Abdul Ahad Chowdhury, A. Firoze, R. Rahman
Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP), to rank some of the user preferred alternatives. The system considers the choice of the user and the quality of the alternatives to rank them. User preferences on the criteria are taken as inputs in the form of best–worst comparison vectors to measure the choice of the user. These values are applied to calculate the numeric weights of each of the criteria. These weights reflect the preference of the user. A dataset of secondary schools in Bangladesh has been compiled and used for automatic quantitative pairwise comparison on the alternatives to calculate the score of each alternative in every criterion, which reflects its quality in that criterion. These scores are calculated using AHP. The weights of the criteria as well as the scores of these alternatives in those criteria are then used to calculate the final score of the alternatives and to rank them accordingly. An extensive experimental analysis and comparative study is reported at the end of this paper.
{"title":"Fusion of BWM and AHP MCDM Methods to Choose the Most Suitable Secondary School for an Individual in the Context of Bangladesh","authors":"N. R. Rahman, Md. Abdul Ahad Chowdhury, A. Firoze, R. Rahman","doi":"10.1142/S2196888819500167","DOIUrl":"https://doi.org/10.1142/S2196888819500167","url":null,"abstract":"Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP), to rank some of the user preferred alternatives. The system considers the choice of the user and the quality of the alternatives to rank them. User preferences on the criteria are taken as inputs in the form of best–worst comparison vectors to measure the choice of the user. These values are applied to calculate the numeric weights of each of the criteria. These weights reflect the preference of the user. A dataset of secondary schools in Bangladesh has been compiled and used for automatic quantitative pairwise comparison on the alternatives to calculate the score of each alternative in every criterion, which reflects its quality in that criterion. These scores are calculated using AHP. The weights of the criteria as well as the scores of these alternatives in those criteria are then used to calculate the final score of the alternatives and to rank them accordingly. An extensive experimental analysis and comparative study is reported at the end of this paper.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126555609","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 : 2019-08-14DOI: 10.1142/S2196888819500179
X. Meza, T. Yamanaka
There are several issues compromising the educational role of social networks, particularly in the case of video-based online content. Among them, individual (cognitive and emotional), social (privacy and ethics) and structural (algorithmic bias) challenges can be found. To cope with such issues, we propose a recommendation system for online video content, applying the principles of sustainable design. Precision and recall in English were slightly lower for the system in comparison to YouTube, but the variety of recommended items increased; while in Spanish, precision and recall were higher. Expected results include fostering the adoption of complex thinking by taking on account a user’s objective and subjective contexts.
{"title":"A Video Recommendation System for Complex Topic Learning Based on a Sustainable Design Approach","authors":"X. Meza, T. Yamanaka","doi":"10.1142/S2196888819500179","DOIUrl":"https://doi.org/10.1142/S2196888819500179","url":null,"abstract":"There are several issues compromising the educational role of social networks, particularly in the case of video-based online content. Among them, individual (cognitive and emotional), social (privacy and ethics) and structural (algorithmic bias) challenges can be found. To cope with such issues, we propose a recommendation system for online video content, applying the principles of sustainable design. Precision and recall in English were slightly lower for the system in comparison to YouTube, but the variety of recommended items increased; while in Spanish, precision and recall were higher. Expected results include fostering the adoption of complex thinking by taking on account a user’s objective and subjective contexts.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115646481","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 : 2019-08-14DOI: 10.1142/S2196888819500180
Krzysztof Kania, Przemysław Juszczuk, J. Kozák
In this paper, we propose a novel approach for transforming financial time-series values into symbolic representation based on value changes. Such approach seems to have few advantages over the existing approaches; one of the most obvious is noise reduction in the data and another one is possibility to find patterns which are universal for investigating different currency pairs. To achieve the goal we introduce a preprocessing method that allows initial data transformation. We also define a text-based similarity measure which can be used as an alternative for methods allowing to find the exact patterns in the historical data. To effectively evaluate our method, we present a concept that allows to predict the potential price movement direction and compare it with the actual price direction observed in the historical data. Such a method gives an opportunity not only to indicate the different price patterns based on the symbolic representation but also at the same time evaluate the predictive power of such patterns. The proposed approach is experimentally verified on 10 different currency pairs, each covering approximately a period of 10 years.
{"title":"Enhanced Symbolic Description in Analyzing Patterns and Volatility on the Forex Market","authors":"Krzysztof Kania, Przemysław Juszczuk, J. Kozák","doi":"10.1142/S2196888819500180","DOIUrl":"https://doi.org/10.1142/S2196888819500180","url":null,"abstract":"In this paper, we propose a novel approach for transforming financial time-series values into symbolic representation based on value changes. Such approach seems to have few advantages over the existing approaches; one of the most obvious is noise reduction in the data and another one is possibility to find patterns which are universal for investigating different currency pairs. To achieve the goal we introduce a preprocessing method that allows initial data transformation. We also define a text-based similarity measure which can be used as an alternative for methods allowing to find the exact patterns in the historical data. To effectively evaluate our method, we present a concept that allows to predict the potential price movement direction and compare it with the actual price direction observed in the historical data. Such a method gives an opportunity not only to indicate the different price patterns based on the symbolic representation but also at the same time evaluate the predictive power of such patterns. The proposed approach is experimentally verified on 10 different currency pairs, each covering approximately a period of 10 years.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128631599","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 : 2019-08-01DOI: 10.1142/S2196888819500076
Marcin Hernes, N. Nguyen
Efficient operation of the integrated management information systems (IMISs), especially multi-agent systems, is related to their ability to automatically process collective knowledge. On the basis of this knowledge the decision-making process is realized in the business organizations. This paper presents issues related to framework for acquiring and acquisition subprocesses in a collective knowledge of business organization processing in IMIS. The main novelty of the developed framework is the coverage of all the areas of operation of an organization. Additionally, the inter-area knowledge for automatic strategic-level decision-making has been taken into consideration. The main improvements of this framework are that it allows for processing of the whole collective knowledge of business organization and it can be directly implemented in IMIS.
{"title":"Definition of a Framework for Acquiring and Acquisition Subprocesses in a Collective Knowledge Processing in the Integrated Management Information System","authors":"Marcin Hernes, N. Nguyen","doi":"10.1142/S2196888819500076","DOIUrl":"https://doi.org/10.1142/S2196888819500076","url":null,"abstract":"Efficient operation of the integrated management information systems (IMISs), especially multi-agent systems, is related to their ability to automatically process collective knowledge. On the basis of this knowledge the decision-making process is realized in the business organizations. This paper presents issues related to framework for acquiring and acquisition subprocesses in a collective knowledge of business organization processing in IMIS. The main novelty of the developed framework is the coverage of all the areas of operation of an organization. Additionally, the inter-area knowledge for automatic strategic-level decision-making has been taken into consideration. The main improvements of this framework are that it allows for processing of the whole collective knowledge of business organization and it can be directly implemented in IMIS.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115421832","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 : 2019-07-08DOI: 10.1142/S2196888819500192
Gharbi Alshammari, S. Kapetanakis, Abdullah Alshammari, Nikolaos Polatidis, M. Petridis
Recommender systems help users find relevant items efficiently based on their interests and historical interactions with other users. They are beneficial to businesses by promoting the sale of products and to user by reducing the search burden. Recommender systems can be developed by employing different approaches, including collaborative filtering (CF), demographic filtering (DF), content-based filtering (CBF) and knowledge-based filtering (KBF). However, large amounts of data can produce recommendations that are limited in accuracy because of diversity and sparsity issues. In this paper, we propose a novel hybrid method that combines user–user CF with the attributes of DF to indicate the nearest users, and compare four classifiers against each other. This method has been developed through an investigation of ways to reduce the errors in rating predictions based on users’ past interactions, which leads to improved prediction accuracy in all four classification algorithms. We applied a feature combination method that improves the prediction accuracy and to test our approach, we ran an offline evaluation using the 1M MovieLens dataset, well-known evaluation metrics and comparisons between methods with the results validating our proposed method.
{"title":"Improved Movie Recommendations Based on a Hybrid Feature Combination Method","authors":"Gharbi Alshammari, S. Kapetanakis, Abdullah Alshammari, Nikolaos Polatidis, M. Petridis","doi":"10.1142/S2196888819500192","DOIUrl":"https://doi.org/10.1142/S2196888819500192","url":null,"abstract":"Recommender systems help users find relevant items efficiently based on their interests and historical interactions with other users. They are beneficial to businesses by promoting the sale of products and to user by reducing the search burden. Recommender systems can be developed by employing different approaches, including collaborative filtering (CF), demographic filtering (DF), content-based filtering (CBF) and knowledge-based filtering (KBF). However, large amounts of data can produce recommendations that are limited in accuracy because of diversity and sparsity issues. In this paper, we propose a novel hybrid method that combines user–user CF with the attributes of DF to indicate the nearest users, and compare four classifiers against each other. This method has been developed through an investigation of ways to reduce the errors in rating predictions based on users’ past interactions, which leads to improved prediction accuracy in all four classification algorithms. We applied a feature combination method that improves the prediction accuracy and to test our approach, we ran an offline evaluation using the 1M MovieLens dataset, well-known evaluation metrics and comparisons between methods with the results validating our proposed method.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"22 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120813335","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 : 2019-05-22DOI: 10.1142/S219688881950009X
Tram Nguyen, T. Bui, Bay Vo
This paper proposes the use of multi-swarm method in particle swarm optimization (PSO) algorithm to generate multiple-choice tests based on assumed objective levels of difficulty. The method extracts an abundance of tests at the same time with the same levels of difficulty and approximates the difficulty-level requirement given by the users. The experimental results show that the proposed method can generate many tests from question banks satisfying predefined levels of difficulty. Additionally, the proposed method is also shown to be effective in terms of many criteria when compared with other methods such as manually extracted tests, random methods and PSO-based methods in terms of execution time, standard deviation, the number of particles per swarm and the number of swarms.
{"title":"Multi-Swarm Single-Objective Particle Swarm Optimization to Extract Multiple-Choice Tests","authors":"Tram Nguyen, T. Bui, Bay Vo","doi":"10.1142/S219688881950009X","DOIUrl":"https://doi.org/10.1142/S219688881950009X","url":null,"abstract":"This paper proposes the use of multi-swarm method in particle swarm optimization (PSO) algorithm to generate multiple-choice tests based on assumed objective levels of difficulty. The method extracts an abundance of tests at the same time with the same levels of difficulty and approximates the difficulty-level requirement given by the users. The experimental results show that the proposed method can generate many tests from question banks satisfying predefined levels of difficulty. Additionally, the proposed method is also shown to be effective in terms of many criteria when compared with other methods such as manually extracted tests, random methods and PSO-based methods in terms of execution time, standard deviation, the number of particles per swarm and the number of swarms.","PeriodicalId":256649,"journal":{"name":"Vietnam. J. Comput. Sci.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128975664","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：