2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)最新文献

NP-SOM: Network Programmable Self-Organizing Maps NP-SOM:网络可编程自组织地图

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00141

Yann Bernard, Emeline Buoy, Adrien Fois, B. Girau

引用次数: 2

Contextual Anomaly Detection in Spatio-Temporal Data Using Locally Dense Regions 基于局部密集区域的时空数据上下文异常检测

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00149

G. Anand, R. Nayak

引用次数: 0

Vehicle Routing and Scheduling for Regular Mobile Healthcare Services 定期移动医疗保健服务的车辆路线和调度

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00080

Cosmin Pascaru, Paul Diac

{"title":"Vehicle Routing and Scheduling for Regular Mobile Healthcare Services","authors":"Cosmin Pascaru, Paul Diac","doi":"10.1109/ICTAI.2018.00080","DOIUrl":"https://doi.org/10.1109/ICTAI.2018.00080","url":null,"abstract":"We propose our solution to a particular practical problem in the domain of vehicle routing and scheduling. The generic task is finding the best allocation of minimum number of mobile resources that can provide periodical services in remote locations. These mobile resources are based at a single central location. Specifications have been defined initially for a real-life application that is the starting point of an ongoing project. Particularly, the goal is to mitigate health problems in rural areas around a city in Romania. Medically equipped vans are programmed to start daily routes from county capital, provide a given number of examinations in townships within the county and return to the capital city in the same day. From healthcare perspective, each van is equipped with an ultrasound scanner and they are scheduled to investigate pregnant woman each trimester aiming to diagnose potential problems. The project is motivated by reports currently ranking Romania as the country with the highest infant mortality rate in European Union. Our solution was developed in two phases: first modeling of the most relevant parameters and data available for our goal and second, design and implement an algorithm that provides an optimized solution. The most important metric of a scheduling is the number of vans that are necessary to provide a given amount of examination time per township, followed by total travel time or fuel consumption, number of different routes, etc. Our solution implements two probabilistic algorithms out of which the best was chosen.","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125542000","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

Long-Term Recurrent Merge Network Model for Image Captioning 图像标注的长期循环合并网络模型

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00047

Yang Fan, Jungang Xu, Yingfei Sun, Ben He

引用次数: 5

Random Forests with Stochastic Induction of Decision Trees 决策树随机归纳的随机森林

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00087

M. Tsipouras, Dimosthenis C. Tsouros, Panagiotis N. Smyrlis, N. Giannakeas, A. Tzallas

引用次数: 7

Smart Governance Through Opinion Mining of Public Reactions on Ordinances 透过公众对条例反应的意见挖掘，实现智慧管治

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00131

Manish Puri, A. Varde, Xu Du, Gerard de Melo

{"title":"Smart Governance Through Opinion Mining of Public Reactions on Ordinances","authors":"Manish Puri, A. Varde, Xu Du, Gerard de Melo","doi":"10.1109/ICTAI.2018.00131","DOIUrl":"https://doi.org/10.1109/ICTAI.2018.00131","url":null,"abstract":"This work focuses on the area of Smart Governance in Smart Cities, which entails transparency in government through public involvement. Specifically, it describes our research on mining urban ordinances or local laws and the public reactions to them expressed on the social media site Twitter. We mine ordinances and tweets related to each other through their mutual connection with Smart City Characteristics (SCCs) and conduct sentiment analysis of relevant tweets for analyzing opinions of the public on local laws in the given urban region. This helps assess how well that region heads towards a Smart City based on (1) how closely ordinances map to the respective SCCs and (2) the extent of public satisfaction on ordinances related to those SCCs. The mining process relies on Commonsense Knowledge (CSK), i.e., knowledge that is obvious to humans but needs to be explicitly fed into machines for automation. CSK is useful in filtering during tweet selection, conducting SCC-based ordinancetweet mapping and performing sentiment analysis of tweets. This paper presents our work in mapping ordinances to tweets through single or multiple SCCs and opinion mining of tweets along with an experimental evaluation and a discussion with useful recommendations.","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122170538","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: 23

Efficient Traffic Routing with Progress Guarantees 具有进度保证的高效流量路由

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00147

Stefan Blumer, M. Eichelberger, Roger Wattenhofer

引用次数: 3

Message from the ICTAI General Chairs ICTAI总主席的致辞

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ictai.2018.00005

引用次数: 0

Improved Affinity Propagation Clustering for Business Districts Mining 商圈挖掘的改进亲和性传播聚类

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00067

Jian Xu, Y. Wu, Ning Zheng, Liming Tu, Ming Luo

{"title":"Improved Affinity Propagation Clustering for Business Districts Mining","authors":"Jian Xu, Y. Wu, Ning Zheng, Liming Tu, Ming Luo","doi":"10.1109/ICTAI.2018.00067","DOIUrl":"https://doi.org/10.1109/ICTAI.2018.00067","url":null,"abstract":"Business districts serve as basic structures for understanding the organization of real-world economic network. Discovering these business districts in cities establish new types of valuable applications that can benefit end users: Business investors can better identify the proximity of existing business districts and hence, can contribute a better future planning for investing. In this paper, we propose improved affinity propagation clustering for business districts mining. Given check-in data, whose geography information represents business venues' location, we introduce a affinity propagation clustering algorithm(AP), a basic solution, to cluster venues. This strategy requires that real-valued messages are exchanged among business venues until a set of centers and corresponding business districts gradually emerges. However, the computational complexity of AP is affected by the scale of input. And it's not adaptive for random distribution of venues when mining business districts. To conduct business districts mining efficiently, we introduce a pruning method, termed as PAP. And then present merging based mine approach, termed as MAP. We conduct experiments from Yelp data, and experimental results show that our proposed method outperforms the basic solutions and resolves the problem well.","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127018572","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

Path Generation with LSTM Recurrent Neural Networks in the Context of the Multi-Agent Patrolling 基于LSTM递归神经网络的多智能体巡逻路径生成

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2018-11-01 DOI: 10.1109/ICTAI.2018.00073

Mehdi Othmani-Guibourg, A. E. Seghrouchni, J. Farges

{"title":"Path Generation with LSTM Recurrent Neural Networks in the Context of the Multi-Agent Patrolling","authors":"Mehdi Othmani-Guibourg, A. E. Seghrouchni, J. Farges","doi":"10.1109/ICTAI.2018.00073","DOIUrl":"https://doi.org/10.1109/ICTAI.2018.00073","url":null,"abstract":"We propose a conceptually simple new decentralised and non-communicating strategy for the multi-agent patrolling based on the LSTM architecture. The recurrent neural networks and more specifically the LSTM architecture, as machines to learn temporal series, are well adapted to the multi-agent patrol problem to the extent that they can be viewed as a decision problem over the time. For a given scenario, a LSTM neural network is first trained from data generated in simulation for that configuration, then embedded in agents that shall use it to navigate through the area to patrol choosing the next place to visit by feeding it with their current node. Finally, this new LSTM-based strategy is evaluated in simulation and compared with two representative strategies, a cognitive and centralised one, and a reactive and decentralised one. Preliminary results indicate that the proposed strategy is globally not better than the representative strategies for the aggregating criterion of average idleness, but better than the decentralised representative for the evaluation criteria of mean interval and quadratic mean interval.","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123629862","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