Web Intell. Agent Syst.最新文献

Multi-agent orienteering problem with time-dependent capacity constraints 具有时变容量约束的多智能体定向问题

Web Intell. Agent Syst. Pub Date : 2014-10-01 DOI: 10.3233/WIA-140304

Cen Chen, Shih-Fen Cheng, H. Lau

{"title":"Multi-agent orienteering problem with time-dependent capacity constraints","authors":"Cen Chen, Shih-Fen Cheng, H. Lau","doi":"10.3233/WIA-140304","DOIUrl":"https://doi.org/10.3233/WIA-140304","url":null,"abstract":"In this paper, we formulate and study the Multi-agent Orienteering Problem with Time-dependent Capacity Constraints (MOPTCC). MOPTCC is similar to the classical orienteering problem at the single-agent level: given a limited time budget, an agent travels around the network and collects rewards by visiting different nodes, with the objective of maximizing the sum of his collected rewards. The most important feature we introduce in MOPTCC is the inclusion of multiple competing and interacting agents. All agents in MOPTCC are assumed to be self-interested, and they interact with each other when arrive at the same nodes simultaneously. As all nodes are capacitated, if a particular node receives more agents than its capacity, all agents at that node will be made to wait and agents suffer collectively as a result (in terms of extra time needed for queueing). Due to the decentralized nature of the problem, MOPTCC cannot be solved in a centralized manner; instead, we need to seek out equilibrium solutions; and if this is not possible, at least approximated equilibrium solutions. The major contribution of this paper is the formulation of the problem, and our first attempt in identifying an efficient and effective equilibrium-seeking procedure for MOPTCC.","PeriodicalId":263450,"journal":{"name":"Web Intell. Agent Syst.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131242907","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}

引用次数: 14

Web usage mining based recommender systems using implicit heterogeneous data: - A Particle Swarm Optimization based clustering approach 使用隐式异构数据的基于Web使用挖掘的推荐系统:-基于粒子群优化的聚类方法

Web Intell. Agent Syst. Pub Date : 2014-10-01 DOI: 10.3233/WIA-140302

Shafiq Alam, G. Dobbie, Yun Sing Koh, Patricia J. Riddle

{"title":"Web usage mining based recommender systems using implicit heterogeneous data: - A Particle Swarm Optimization based clustering approach","authors":"Shafiq Alam, G. Dobbie, Yun Sing Koh, Patricia J. Riddle","doi":"10.3233/WIA-140302","DOIUrl":"https://doi.org/10.3233/WIA-140302","url":null,"abstract":"Recommender systems have become one of the necessary tools to help a web user find a potentially interesting resource based on their preferences. In implicit recommender systems, the recommendations are made based on the implicit information of the web users i.e. data collected from web logs or cookies without knowing users preferences. Developing such a recommender system is complex due to the huge amount of anonymous noisy data. In this paper we present a Particle Swarm Optimization (PSO) based clustering approach called Hierarchical Particle Swarm Optimization based clustering (HPSO-clustering) for building a recommender system based on implicit web usage data. The approach mimics multi-agent properties of the particles of a swarm and divide the problem space into smaller sub-spaces i.e. clusters. Each cluster represents a particular group of user with similar interests. Later, the K-nearest neighbours of the most relevant cluster are generated as recommendations for a web user and ranked based on their distance. We performed different experiments for preprocessing, to assess the quality of clusters, and for the accuracy of recommendations. An overall accuracy of 65% to 95% was achieved for different scenarios, while in some cases the accuracy touched 100 precent when the selection was made from the top-5 recommendations.","PeriodicalId":263450,"journal":{"name":"Web Intell. Agent Syst.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124557155","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}

引用次数: 4

Scalable approximating SVD algorithm for recommender systems 推荐系统的可扩展逼近SVD算法

Web Intell. Agent Syst. Pub Date : 2014-10-01 DOI: 10.3233/WIA-140303

Xun Zhou, Jing He, Guangyan Huang, Yanchun Zhang

{"title":"Scalable approximating SVD algorithm for recommender systems","authors":"Xun Zhou, Jing He, Guangyan Huang, Yanchun Zhang","doi":"10.3233/WIA-140303","DOIUrl":"https://doi.org/10.3233/WIA-140303","url":null,"abstract":"With the rapid development of Internet, the amount of information on the Web grows explosively, people often feel puzzled and helpless in finding and getting the information they really need. For overcoming this problem, recommender systems such as singular value decomposition (SVD) method help users finding relevant information, products or services by providing personalized recommendations based on their profiles. SVD is a powerful technique for dimensionality reduction. However, due to its expensive computational requirements and weak performance for large sparse matrices, it has been considered inappropriate for practical applications involving massive data.Thus, to extract information in which the user is interested from a massive amount of data, we propose a personalized recommendation algorithm which is called ApproSVD algorithm based on approximating SVD in this paper. The trick behind our algorithm is to sample some rows of a user-item matrix, rescale each row by an appropriate factor to form a relatively smaller matrix, and then reduce the dimensionality of the smaller matrix. Finally, we present an empirical study to compare the prediction accuracy of our proposed algorithm with that of Drineas's LINEARTIMESVD algorithm and the standard SVD algorithm on MovieLens dataset and Flixster dataset, and show that our method has the best prediction quality. Furthermore, in order to show the superiority of the ApproSVD algorithm, we also conduct an empirical study to compare the prediction accuracy and running time between ApproSVD algorithm and incremental SVD algorithm on MovieLens dataset and Flixster dataset, and demonstrate that our proposed method has better performance overall.","PeriodicalId":263450,"journal":{"name":"Web Intell. Agent Syst.","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116008105","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}

引用次数: 5

Detecting cyberbullying in social networks using multi-agent system 利用多智能体系统检测社交网络中的网络欺凌

Web Intell. Agent Syst. Pub Date : 2014-10-01 DOI: 10.3233/WIA-140301

V. Nahar, Xue Li, H. Zhang, C. Pang

{"title":"Detecting cyberbullying in social networks using multi-agent system","authors":"V. Nahar, Xue Li, H. Zhang, C. Pang","doi":"10.3233/WIA-140301","DOIUrl":"https://doi.org/10.3233/WIA-140301","url":null,"abstract":"State-of-the-art studies on cyberbullying detection, using text classification, predominantly take it for granted that streaming text can be completely labelled. However, the rapid growth of unlabelled data generated in real time from online content renders this virtually impossible. In this paper, we propose a session-based framework for automatic detection of cyberbullying within the large volume of unlabelled streaming text. Given that the streaming data from Social Networks arrives in large volume at the server system, we incorporate an ensemble of one-class classifiers in the session-based framework. System uses Multi-Agent distributed environment to process streaming data from multiple social network sources. The proposed strategy tackles real world situations, where only a few positive instances of cyberbullying are available for initial training. Our main contribution in this paper is to automatically detect cyberbullying in real world situations, where labelled data is not readily available. Initial results indicate the suggested approach is reasonably effective for detecting cyberbullying automatically on social networks. The experiments indicate that the ensemble learner outperforms the single window and fixed window approaches, while the learning process is based on positive and unlabelled data only, no negative data is available for training.","PeriodicalId":263450,"journal":{"name":"Web Intell. Agent Syst.","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115565531","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}

引用次数: 12

Agent-based problem solving methods in Big Data environment 大数据环境下基于agent的问题解决方法

Web Intell. Agent Syst. Pub Date : 2014-10-01 DOI: 10.3233/WIA-140300

H. Zhang, H. Lau

引用次数: 1

A syntactic possibilistic belief change operator: Theory and empirical study 一种句法可能性信念改变算子:理论与实证研究

Web Intell. Agent Syst. Pub Date : 2014-04-01 DOI: 10.3233/WIA-140290

C. Pereira, A. Tettamanzi

引用次数: 2

Dynamic multiagent load balancing using distributed constraint optimization techniques 使用分布式约束优化技术的动态多代理负载平衡

Web Intell. Agent Syst. Pub Date : 2014-04-01 DOI: 10.3233/WIA-140288

Shanjun Cheng, A. Raja, Jiang Xie

{"title":"Dynamic multiagent load balancing using distributed constraint optimization techniques","authors":"Shanjun Cheng, A. Raja, Jiang Xie","doi":"10.3233/WIA-140288","DOIUrl":"https://doi.org/10.3233/WIA-140288","url":null,"abstract":"Resource management is a key challenge in multiagent systems. It is especially important in dynamic environments where decisions need to be made quickly and when decisions can get obsolete quickly. In wireless local area networks WLANs, resource management includes dynamic channel assignment, dynamic transmit power control and load balancing of WLANs traffic. In this work, we present a novel decentralized framework and a distributed optimization algorithm DLB-SDPOP for load balancing in complex WLANs. Our self-stabilizing algorithm focuses on repairing the network structure instead of reconstructing it when network perturbations occur. It controls the complexity of problem solving by utilizing efficient search and leverages uncertainty to reduce the possibility of reaching myopic solutions. The size and number of inter-agent communication messages are significantly reduced using a communication filtering mechanism. We categorize different scenarios based on key characteristics i.e., load, dynamics and uncertainty in WLANs and compare our algorithm with other state of the art distributed constraint optimization algorithms in each scenario. Our empirical results show that our distributed approach improves WLANs load balancing performance significantly.","PeriodicalId":263450,"journal":{"name":"Web Intell. Agent Syst.","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117183633","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}

引用次数: 2

Building up a class hierarchy with properties by refining and integrating Japanese Wikipedia Ontology and Japanese WordNet 通过提炼和集成日文维基本体和日文WordNet，建立了一个带有属性的类层次结构

Web Intell. Agent Syst. Pub Date : 2014-04-01 DOI: 10.3233/WIA-140293

Takeshi Morita, Yuka Sekimoto, Susumu Tamagawa, Takahira Yamaguchi

引用次数: 3

Activity-based topic discovery 基于活动的主题发现

Web Intell. Agent Syst. Pub Date : 2014-04-01 DOI: 10.3233/WIA-140292

Dandan Zhu, Yusuke Fukazawa, Eleftherios Karapetsas, J. Ota

引用次数: 3

Towards adaptive normative systems for communities of agents 面向主体群体的适应性规范系统

Web Intell. Agent Syst. Pub Date : 2013-10-01 DOI: 10.3233/WIA-130279

I. A. Letia, O. Pop

引用次数: 0