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2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)最新文献

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Introducing Supplemental Context for Word Sense Disambiguation 介绍词义消歧的补充上下文
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0164
Alan Black, Rosina O. Weber
{"title":"Introducing Supplemental Context for Word Sense Disambiguation","authors":"Alan Black, Rosina O. Weber","doi":"10.1109/ICTAI.2016.0164","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0164","url":null,"abstract":"Microtext is sparse and informal content typical in social media that is being widely used to study various facets of today's society. This paper proposes the use of supplemental context to counteract the limitations imposed by the sparsity and the informality of microtext on the performance of word sense disambiguation (WSD). WSD relies on the senses of words around an ambiguous word to disambiguate it. Because microtext is sparse and informal, it lacks exploitable context. This creates a major challenge for using this kind of data and consequently to the analyses of studies that rely on microtext sources. This paper proposes, demonstrates, and describes some of the challenges in selecting and utilizing supplemental context. We present studies using twitter data. We validate our studies with around 10,000 tweets using a gold standard proxy we call the blue standard. The method relies on the notion of one sense per collocation, and we implement it by identifying collocated word sequences that are strongly indicative of the target word's sense.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124252592","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: 0
Classification of Apple Tree Disorders Using Convolutional Neural Networks 用卷积神经网络对苹果树病害进行分类
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0078
Lucas G. Nachtigall, R. M. Araújo, G. Nachtigall
{"title":"Classification of Apple Tree Disorders Using Convolutional Neural Networks","authors":"Lucas G. Nachtigall, R. M. Araújo, G. Nachtigall","doi":"10.1109/ICTAI.2016.0078","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0078","url":null,"abstract":"This paper studies the use of Convolutional Neural Networks to automatically detect and classify diseases, nutritional deficiencies and damage by herbicides on apple trees from images of their leaves. This task is fundamental to guarantee a high quality of the resulting yields and is currently largely performed by experts in the field, which can severely limit scale and add to costs. By using a novel data set containing labeled examples consisting of 2539 images from 6 known disorders, we show that trained Convolutional Neural Networks are able to match or outperform experts in this task, achieving a 97.3% accuracy on a hold-out set.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117296412","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: 93
A Genetic Algorithm Approach for Clustering Large Data Sets 大型数据集聚类的遗传算法
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0093
Diego Luchi, Alexandre Rodrigues Loureiros, F. M. Varejão, Willian Santos
{"title":"A Genetic Algorithm Approach for Clustering Large Data Sets","authors":"Diego Luchi, Alexandre Rodrigues Loureiros, F. M. Varejão, Willian Santos","doi":"10.1109/ICTAI.2016.0093","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0093","url":null,"abstract":"In this paper we present a sampling approach to run the k-means algorithm in large data sets. We propose a genetic algorithm to guide sampling based on evaluating the fitness of each individual of the population through the k-means clustering algorithm. Although we want a partition with the lowest SSE, our algorithm tries to find the sample with the highest SSE. After finding a good sample the remaining points of the entire data set are clustered using the nearest centroid and, after that, the SSE of the final solution is calculated. Our proposal is applied on a set of public domain data sets and the results are compared against two other methods: the k-means running in a uniform random sample of the data set, and the k-means in the complete data set. The results showed that our algorithm has a good trade off between quality and computational cost, especially for large data sets and higher number of clusters.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121968547","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
Applying Semantic Similarity to Phrase Pivot Translation 语义相似度在短语中心翻译中的应用
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0160
H. Trieu, Le-Minh Nguyen
{"title":"Applying Semantic Similarity to Phrase Pivot Translation","authors":"H. Trieu, Le-Minh Nguyen","doi":"10.1109/ICTAI.2016.0160","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0160","url":null,"abstract":"Pivot methods have shown to be an effective solution to overcome the problem of unavailable large bilingual corpora in statistical machine translation. The representative approach of pivot methods is the phrase pivot translation which is based on common pivot phrases to produce connections between source-pivot and pivot-target phrase tables. Nevertheless, this approach produces insufficient connections behind the phrase tables because pivot phrases still contain the same meaning even when they are not matched to each other. In this work, we propose applying semantic similarity between pivot phrases to phrase pivot translation. In order to extract similar pivot phrases, we used string similarity measures for phrase similarity, and WordNet and Word2Vec were used for word similarity. The experiments show that using semantic similarity is able to extract more informative phrases, which can support for phrase pivot translation.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117128744","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
Sets of Contrasting Rules: A Supervised Descriptive Rule Induction Pattern for Identification of Trigger Factors 对比规则集:一种用于识别触发因素的有监督描述性规则归纳模式
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0072
Marharyta Aleksandrova, A. Brun, O. Chertov, A. Boyer
{"title":"Sets of Contrasting Rules: A Supervised Descriptive Rule Induction Pattern for Identification of Trigger Factors","authors":"Marharyta Aleksandrova, A. Brun, O. Chertov, A. Boyer","doi":"10.1109/ICTAI.2016.0072","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0072","url":null,"abstract":"Data mining, through association rules mining, is one of the best known approaches for patterns identification. However, it results most of the time in a huge set of patterns (rules), so their exploitation is not easy and often requires expert analysis. In this paper we describe a new pattern \"set of contrasting rules\" which, contrary to most state-of-the-art patterns, has the characteristic of being made up of a set of rules. It has also the advantage of not only identifying a reduced set of rules, but also structuring it into sets. One main originality of this pattern is that it allows to automatically identify trigger factors: factors that can bring some event state changes. In this work we show that the proposed pattern methodologically belongs to the supervised descriptive rules induction paradigm. We also show through the experiments on a real dataset of census data that \"set of contrasting rules\" can be considered as a way to filter the huge amount of association rules and can be used to identify trigger factors.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128155503","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
Improving Exact Solution Counting for Decomposition Methods 改进分解方法的精确解计数
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0057
Philippe Jégou, H. Kanso, C. Terrioux
{"title":"Improving Exact Solution Counting for Decomposition Methods","authors":"Philippe Jégou, H. Kanso, C. Terrioux","doi":"10.1109/ICTAI.2016.0057","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0057","url":null,"abstract":"The problem of counting solutions in CSP, called #CSP, is an extremely difficult problem that has many applications in Artificial Intelligence. This problem can be addressed by exact methods, but more classically it is solved by approximate methods. Here, we focus primarily on the exact counting. We show how it is possible to improve the methods based on structural decomposition by offering to enhance the search for a new solution which is a critical step for counting, particularly for such methods. Moreover, if the resources in time or in space are insufficient, we show that our approach is still able to provide a lower bound of the result. Experiments on CSP benchmarks show the practical advantage of our approach w.r.t. the best methods of the literature.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127984210","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
An Evaluation of Different Evolutionary Approaches Applied in the Process of Automatic Transcription of Music Scores into Tablatures 不同演化方法在乐谱自动转写制表过程中的应用评价
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0106
Joao Victor Ramos, A. S. Ramos, C. Silla, D. Sanches
{"title":"An Evaluation of Different Evolutionary Approaches Applied in the Process of Automatic Transcription of Music Scores into Tablatures","authors":"Joao Victor Ramos, A. S. Ramos, C. Silla, D. Sanches","doi":"10.1109/ICTAI.2016.0106","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0106","url":null,"abstract":"The problem of converting a music in standard music notation (music sheet) to the alternative notation of guitar tablature is known as transcription. The process of transcription consists of indicating where each note from the original music sheet needs to be played in the guitar, i.e. which string and fret of the guitar that needs to be played to produce a particular note. However, considering that each note can be played in different positions of the guitar fretboard, this is not a straightforward process, and can be classified as a combinatorial optimization problem. For this reason, we have employed a comparative study of different algorithms: A-star, genetic algorithms (GA), genetic algorithms based on subpopulations (GA-SP), ant colony optimization (ACO) and differential evolution (DE). It was also included heuristics based on local search 2-opt and 3-opt in the approaches GA, GA-SP and DE. The experimental results with a dataset of 87 musics indicated that the approaches ACO, GA-SP with 2-opt and GA with 2-opt reached the best performance. Also, the results obtained with each approach were statistically compared using ANOVA test with post hoc Tukey.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123357898","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: 3
Visual Orientation Inhomogeneity Based Convolutional Neural Networks 基于卷积神经网络的视觉定向不均匀性
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0079
S. Zhong, Jiaxin Wu, Yingying Zhu, Peiqi Liu, Jianmin Jiang, Yan Liu
{"title":"Visual Orientation Inhomogeneity Based Convolutional Neural Networks","authors":"S. Zhong, Jiaxin Wu, Yingying Zhu, Peiqi Liu, Jianmin Jiang, Yan Liu","doi":"10.1109/ICTAI.2016.0079","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0079","url":null,"abstract":"The details of oriented visual stimuli are better resolved when they are horizontal or vertical rather than oblique. This \"oblique effect\" has been researched and confirmed in numerous research studies, including behavioral studies and neurophysiological and neuroimaging findings. Although the \"oblique effect\" has influence in many fields, little research integrated it into computational models. In this paper, we try to explore this inhomogeneity of visual orientation based on Convolutional neural networks (CNNs) in image recognition. We validate that visual orientation inhomogeneity CNNs can achieve comparable performance with higher computational efficiency on various datasets. We can also get the conclusion that, compared with the cardinal information, oblique information is indeed less useful in natural color image recognition. Through the exploration of the proposed model on image recognition, we gain more understanding of the inhomogeneity of visual orientation. It also illuminates a wide range of opportunities for integrating the inhomogeneity of visual orientation with other computational models.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126056158","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
Privacy-Driven Electricity Group Demand Response in Smart Cities Using Particle Swarm Optimization 基于粒子群优化的智慧城市隐私驱动的电力群需求响应
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0146
M. Alamaniotis, L. Tsoukalas, M. Buckner
{"title":"Privacy-Driven Electricity Group Demand Response in Smart Cities Using Particle Swarm Optimization","authors":"M. Alamaniotis, L. Tsoukalas, M. Buckner","doi":"10.1109/ICTAI.2016.0146","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0146","url":null,"abstract":"In the smart cities of the future, digital connectivity will become the cornerstone for implementing intelligent management of electric power from the side of demand. In particular, consumers will connect via communication networks and exchange data messages or share information. Utilization of information will allow consumers to manage their electricity consumption in a more efficient and economical way. However, connectivity and information exchange come at a cost of reduced privacy. In particular, third parties connected to the power grid are able to monitor the consumption signals and make inferences about the consumers' behavior. In this a paper, an intelligent methodology for enhancing privacy in smart power systems in smart cities is presented. The methodology fuses the demand patterns of several consumers, which are connected to the power grid, and provides a new consumption pattern. The new pattern, which hides individual consumer characteristics, is obtained as the solution to an optimization problem whose solution is computed by particle swarm optimization. Testing of the methodology is performed on a set of real consumption patterns, while benchmarked against genetic algorithm. Results exhibit the efficiency of the proposed intelligent methodology, and its superiority over the benchmarked algorithm.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121831520","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
A Reactive Agent-Based Decision-Making System for SBCE 基于反应型主体的SBCE决策系统
2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0117
Baudouin Dafflon, Mohammed Taha Elhariri Essamlali, A. Sekhari, Abdelaziz Bouras
{"title":"A Reactive Agent-Based Decision-Making System for SBCE","authors":"Baudouin Dafflon, Mohammed Taha Elhariri Essamlali, A. Sekhari, Abdelaziz Bouras","doi":"10.1109/ICTAI.2016.0117","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0117","url":null,"abstract":"Nowadays, manufactured products offer more and more personalization. This paradigm is in acceleration due to the emergence of mass customization proposed by industry 4.0. To cope with this demand, industry must design suitable products and adhere to a strict specification. Tools and process were proposed to manage product design, validation and manufacturing such as Set-Based Concurrent Engineering (SBCE). Project Manager in charge of this critical step is helped by metrics and indicators. However, visual aid, dynamic and adatative solution, capable to reply in real-time to a major project evolution does not exist. The aim of this paper is to present an approach for SBCE alternatives selection, based on the application of reactive multiagents systems. Multi-agents systems are an efficient approach for problem solving and decision making in dynamic context. The proposal is evaluated in simulation on drone design optimization.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123865460","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
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