Proceedings of the Symposium on Applied Computing最新文献_第5页

Text-based question routing for question answering communities via deep learning 通过深度学习为问答社区提供基于文本的问题路由

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019762

Amr Azzam, N. Tazi, A. Hossny

引用次数: 10

Usability evaluation and development of heuristics for second-screen applications 第二屏幕应用程序的可用性评估和启发式开发

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019883

E. Mosqueira-Rey, David Alonso-Ríos, Diego Prado-Gesto, V. Moret-Bonillo

引用次数: 6

Driving time-dependent paths in clinical BPMN processes 驱动临床BPMN过程中的时间依赖路径

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019620

Combi Carlo, P. Sala, Francesca Zerbato

引用次数: 3

On-the-fly transformation synthesis for information sharing in heterogeneous multi-agent systems 异构多智能体系统信息共享的动态变换综合

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019879

S. Niemczyk, Nugroho Fredivianus, K. Geihs

引用次数: 1

Genetic algorithm based patching scheme for worm containment on social network 基于遗传算法的社交网络蠕虫围堵修补方案

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019912

Donghwa Kang, Seoyeon Kim, Jinmang Jung, Bongjae Kim, Hong Min, Junyoung Heo

引用次数: 1

Doctrine based multi-resolution HLA distributed simulation 基于原理的HLA多分辨率分布式仿真

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019727

R. L. Paul, Raul Ceretta Nunes, Vanderlan D. Oliveira, Diogo Kunde

{"title":"Doctrine based multi-resolution HLA distributed simulation","authors":"R. L. Paul, Raul Ceretta Nunes, Vanderlan D. Oliveira, Diogo Kunde","doi":"10.1145/3019612.3019727","DOIUrl":"https://doi.org/10.1145/3019612.3019727","url":null,"abstract":"In distributed simulation, the purpose of multi-resolution methods is to allow simulation integration getting consistent views of different resolutions. In these methods, challenges in the treatment of aggregation and disaggregation can be found, such as synchronization of events and objects, and data reliability when occurs a change of resolution. Doctrines are the basis for operations involving different resources (human and material) with different roles to succeed in operation, and multi-resolution in distributed simulation can take advantage of this factor to ensure the reliability of aggregation and disaggregation processes. The aim of this paper is to propose a new strategy for treatment of multi-resolution, which builds converting rules from doctrine dynamic rules. The multi-resolution converter uses dynamic rules to describe aspects of the doctrine in the aggregation and disaggregation processes, increasing the reliability of multi-resolution distributed simulations. This strategy was implemented on a High Level Architecture (HLA) federation with virtual and constructive Commercial Off- The-Shelf (COTS) simulators. The experiments showed the flexibility of this strategy on managing different doctrines.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78953565","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: 1

An asynchronous distributed constraint optimization approach to multi-robot path planning with complex constraints 复杂约束下多机器人路径规划的异步分布式约束优化方法

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019708

Alberto Viseras Ruiz, Valentina Karolj, L. Merino

{"title":"An asynchronous distributed constraint optimization approach to multi-robot path planning with complex constraints","authors":"Alberto Viseras Ruiz, Valentina Karolj, L. Merino","doi":"10.1145/3019612.3019708","DOIUrl":"https://doi.org/10.1145/3019612.3019708","url":null,"abstract":"Multi-robot teams can play a crucial role in many applications such as exploration, or search and rescue operations. One of the most important problems within the multi-robot context is path planning. This has been shown to be particularly challenging, as the team of robots must deal with additional constraints, e.g. inter-robot collision avoidance, while searching in a much larger action space. Previous works have proposed solutions to this problem, but they present two major drawbacks: (i) algorithms suffer from a high computational complexity, or (ii) algorithms require a communication link between any two robots within the system. This paper presents a method to solve this problem, which is both computationally efficient and only requires local communication between neighboring agents. We formulate the multirobot path planning as a distributed constraint optimization problem. Specifically, in our approach the asynchronous distributed constraint optimization algorithm (Adopt) [15] is combined with sampling-based planners to obtain collision free paths, which allows us to take into account both kinematic and kinodynamic constraints of the individual robots. The paper analyzes the performance and scalability of the approach using simulations, and presents real experiments employing a team of several robots.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77449481","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: 6

Schema-summarization in linked-data-based feature selection for recommender systems 基于链接数据的推荐系统特征选择中的模式总结

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019837

A. Ragone, Paolo Tomeo, Corrado Magarelli, T. D. Noia, M. Palmonari, A. Maurino, E. Sciascio

{"title":"Schema-summarization in linked-data-based feature selection for recommender systems","authors":"A. Ragone, Paolo Tomeo, Corrado Magarelli, T. D. Noia, M. Palmonari, A. Maurino, E. Sciascio","doi":"10.1145/3019612.3019837","DOIUrl":"https://doi.org/10.1145/3019612.3019837","url":null,"abstract":"Recommender systems are emerging as an interesting application scenario for Linked Data (LD). In fact, by exploiting the knowledge encoded in LD datasets, a new generation of semantics-aware recommendation engines have been developed in the last years. As Linked Data is often very rich and contains many information that may result irrelevant and noisy for a recommendation task, an initial step of feature selection is always required in order to select the most meaningful portion of the original dataset. Many approaches have been proposed in the literature for feature selection that exploit different statistical dimensions of the original data. In this paper we investigate the role of the semantics encoded in an ontological hierarchy when exploited to select the most relevant properties for a recommendation task. In particular, we compare an approach based on schema summarization with a \"classical\" one, i.e., Information Gain. We evaluated the performance of the two methods in terms of accuracy and aggregate diversity by setting up an experimental testbed relying on the Movielens dataset.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76452862","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: 24

Exploiting implicit and explicit signed trust relationships for effective recommendations 利用隐式和显式签名信任关系进行有效推荐

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019666

Irfan Ali, Jiwon Hong, Sang-Wook Kim

{"title":"Exploiting implicit and explicit signed trust relationships for effective recommendations","authors":"Irfan Ali, Jiwon Hong, Sang-Wook Kim","doi":"10.1145/3019612.3019666","DOIUrl":"https://doi.org/10.1145/3019612.3019666","url":null,"abstract":"Trust networks have been widely used to mitigate the data sparsity and cold-start problems of collaborative filtering. Recently, some approaches have been proposed which exploit explicit signed trust relationships, i.e., trust and distrust relationships. These approaches ignore the fact that users despite trusting/distrusting each other in a trust network may have different preferences in real-life. Most of these approaches also handle the notion of the transitivity of distrust as well as trust. However, other existing work observed that trust is transitive while distrust is intransitive. Moreover, explicit signed trust relationships are fairly sparse and may not contribute to infer true preferences of users. In this paper, we propose to create implicit signed trust relationships and exploit them along with explicit signed trust relationship to solve sparsity problem of trust relationships. We also confirm the similarity (resp. dissimilarity) of implicit and explicit trust (resp. distrust) relationships by using the similarity score between users so that users' true preferences can be inferred. In addition to these strategies, we also propose a matrix factorization model that simultaneously exploits implicit and explicit signed trust relationships along with rating information and also handles transitivity of trust and intransitivity of distrust. Extensive experiments on Epinions dataset show that the proposed approach outperforms existing approaches in terms of accuracy.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83903528","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: 6

SBMI-LTD: stationary background model initialization based on low-rank tensor decomposition 基于低秩张量分解的平稳背景模型初始化

Proceedings of the Symposium on Applied Computing Pub Date : 2017-04-03 DOI: 10.1145/3019612.3019687

S. Javed, T. Bouwmans, Soon Ki Jung

{"title":"SBMI-LTD: stationary background model initialization based on low-rank tensor decomposition","authors":"S. Javed, T. Bouwmans, Soon Ki Jung","doi":"10.1145/3019612.3019687","DOIUrl":"https://doi.org/10.1145/3019612.3019687","url":null,"abstract":"Initialization of background model also known as foreground-free image against outliers or noise is a very important task for various computer vision applications. Tensor deomposition using Higher Order Robust Principal Component Analysis has been shown to be a very efficient framework for exact recovery of low-rank (corresponds to the background model) component. Recent study shows that tensor decomposition based on online optimization into low- rank and sparse component addressed the limitations of memory and computational issues as compared to the earlier approaches. However, it is based on the iterative optimization of nuclear norm which is not always robust when the large entries of an input observation tensor are corrupted against outliers. Therefore, the task of background modeling shows a weak performance in the presence of an increasing number of outliers. To address this issue, this paper presents an extension of an online tensor decomposition into low-rank and sparse components using a maximum norm constraint. Since, maximum norm regularizer is more robust than nuclear norm against large number of outliers, therefore the proposed extended tensor based decomposition framework with maximum norm provides an accurate estimation of background scene. Experimental evaluations on synthetic data as well as real dataset such as Scene Background Modeling Initialization (SBMI) show encouraging performance for the task of background modeling as compared to the state of the art approaches.","PeriodicalId":20728,"journal":{"name":"Proceedings of the Symposium on Applied Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79925224","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: 13