2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)最新文献_第2页

Clustering-Based Query Routing in Cooperative Semi-Structured Peer to Peer Networks 协同半结构化对等网络中基于聚类的查询路由

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0064

Rami Suleiman Alkhawaldeh, J. Jose, P Deepak

引用次数: 1

A Novel Density-Based Approach for Instance Selection 一种新的基于密度的实例选择方法

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0090

J. Carbonera, Mara Abel

{"title":"A Novel Density-Based Approach for Instance Selection","authors":"J. Carbonera, Mara Abel","doi":"10.1109/ICTAI.2016.0090","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0090","url":null,"abstract":"Due to the increasing of the size of the datasets, techniques for instance selection have been applied for reducing the data to a manageable volume, leading to a reduction of the computational resources that are necessary for performing the learning process. Besides that, algorithms of instance selection can also be applied for removing useless, erroneous or noisy instances, before applying learning algorithms. In the last years, several approaches for instance selection have been proposed. However, most of them have high time complexity and, due to this, they cannot be used for dealing with large datasets. In this paper, we present an algorithm called CDIS that can be viewed as an improvement of a recently proposed density-based approach for instance selection. The main contribution of this paper is a formal characterization of a novel density function that is adopted by the CDIS algorithm. The CDIS algorithm evaluates the instances of each class separately and keeps only the densest instances in a given (arbitrary) neighborhood. This ensures a reasonably low time complexity. Our approach was evaluated on 20 well-known data sets and its performance was compared with the performance of 6 state-of-the-art algorithms, considering three measures: accuracy, reduction and effectiveness. For evaluating the accuracy achieved using the datasets produced by the algorithms, we applied the KNN algorithm. The results show that our approach achieves a performance (in terms of balance of accuracy and reduction) that is better or comparable to the performances of the other algorithms considered in the evaluation.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"170 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":"122412794","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: 17

Multiple-Origin-Multiple-Destination Path Finding with Minimal Arc Usage: Complexity and Models 使用最小弧线的多起点多目的地寻径:复杂性和模型

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0024

R. Barták, A. Dovier, Neng-Fa Zhou

引用次数: 3

Time Evolution of Writing Styles in Romanian Language 罗马尼亚语写作风格的时间演变

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0161

Daniela Gîfu, M. Dascalu, Stefan Trausan-Matu, L. Allen

{"title":"Time Evolution of Writing Styles in Romanian Language","authors":"Daniela Gîfu, M. Dascalu, Stefan Trausan-Matu, L. Allen","doi":"10.1109/ICTAI.2016.0161","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0161","url":null,"abstract":"This paper presents a diachronic analysis centered on the exploration of differences between the writing styles of journalistic texts in Romanian language. This analysis is focused on the time evolution of this language across two adjacent regions, Bessarabia and Romania in two major periods that were marked by important historical differences. Our aim is to examine these language differences based on corpora of historical and contemporary texts. To this end, we employ the ReaderBench framework to calculate a number of textual complexity indices that can be reliably used to characterize writing style. These analyses are conducted on two independent corpora for each of the two language styles, covering the following time periods: 1941-1991, when Bessarabia was separated from Romania and became a state in the Soviet Union (and there were few connections and language influences with Romania), and after July 1991, when Bessarabia became an independent state, Republic of Moldavia (and many language interactions with Romania occurred). The results of our analyses highlight the lexical and cohesive textual complexity indices that best reflect the differences in writing style, ranging from sentence and paragraph structure to word entropy and cohesion, measured in terms of Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA).","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"105 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":"130412900","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

Learning Nobetter Clauses in Max-SAT Branch and Bound Solvers Max-SAT分支定界解的Nobetter子句学习

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0075

André Abramé, Djamal Habet

引用次数: 4

Comparing Two Representations for Evolving Micro in 3D RTS Games 三维即时战略游戏中微进化的两种表现形式的比较

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0114

Siming Liu, S. Louis

{"title":"Comparing Two Representations for Evolving Micro in 3D RTS Games","authors":"Siming Liu, S. Louis","doi":"10.1109/ICTAI.2016.0114","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0114","url":null,"abstract":"We are interested in using genetic algorithms to generate winning maneuvering behaviors (or micro) in skirmish scenarios for three dimensional Real-Time Strategy games. In prior work, we encoded parameterized 3D micro behaviors like target selection and kiting into an algorithm for controlling friendly units in battle. Genetic algorithms then tuned these parameters to guide unit maneuvering in order to win skirmishes. In this study, we investigate a new representation for micro behaviors that uses only an influence map and a combination of thirteen potential fields. Genetic algorithms then tune influence map and potential field parameters to evolve winning micro behaviors. We compare the performance of both representations on identical scenarios against identical opponents in a full 3D RTS game environment called FastEcslent. The results show that the genetic algorithm using our new representation using less domain knowledge, reliably evolved high quality 3D micro behaviors that slightly, but significantly, outperformed behaviors from our prior work. Our work thus provides evidence for the viability of using potential fields for generating high quality, complex, micro for three dimensional RTS games.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"13 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":"124241535","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

Improving NetFeatureMap-Based Representation through Frequent Pattern Mining in a Specialized Database 利用频繁模式挖掘改进基于netfeaturemap的表示

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0147

V. Duarte, Rita Maria Silva Julia

{"title":"Improving NetFeatureMap-Based Representation through Frequent Pattern Mining in a Specialized Database","authors":"V. Duarte, Rita Maria Silva Julia","doi":"10.1109/ICTAI.2016.0147","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0147","url":null,"abstract":"The adequate representation of states in the construction of intelligent agents is fundamental for allowing them to achieve a satisfactory performance, principally for those that actuate in a competitive environment that possesses a high state space. One particular type of representation that is very appropriate for these situations is the NetFeatureMap, which describes by means of features the relevant aspects that are inherent to the environment where the agent actuates. In renowned intelligent agents, such features are manually selected, which certainly leads to inadequate choices. Thus, investigating adequate approaches that perform automatic selection of these features becomes a crucial task. In this way, the main contribution of this paper is to propose a new approach that automatically selects appropriate features based on the frequency at which they occur in the states explored by the agent in the course of its acting over the environment. Such an approach is based on Frequent Pattern Mining. It is interesting to point out that there also exist Genetic Algorithms-based approaches that successfully cope with the same task. Unlike Genetic Algorithms that use heuristic functions to select the features, the present proposal uses real data contained in a specialized database for performing this task. Under the intent of investigating the efficacy of such a proposal, the authors utilize the domain of Checkers player agents as their case study, since they operate in a competitive environment with a very wide state space. This investigation is performed by means of tournaments in which agents whose features are selected by the approach proposed herein face others whose features are selected either manually or by Genetic Algorithms. The superior performance of the Frequent-Pattern-based agents in the tournaments proves the efficacy of the present proposal.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"236 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":"116205550","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

Expanding Science and Technology Thesauri from Bibliographic Datasets Using Word Embedding 利用词嵌入从书目数据集扩展科技词典

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0133

Takahiro Kawamura, Kouji Kozaki, Tatsuya Kushida, Katsutaro Watanabe, Katsuji Matsumura

{"title":"Expanding Science and Technology Thesauri from Bibliographic Datasets Using Word Embedding","authors":"Takahiro Kawamura, Kouji Kozaki, Tatsuya Kushida, Katsutaro Watanabe, Katsuji Matsumura","doi":"10.1109/ICTAI.2016.0133","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0133","url":null,"abstract":"The use of thesauri and taxonomies for science and technology information in scientometrics has been attracting attention. However, manual construction and maintenance of thesauri is expensive and requires significant time, thus, methods for semi-automatic construction and maintenance are being actively studied. We propose a method to expand an existing thesaurus using the abstracts of articles from state-of-the-art technological domains with limited structured information. Specifically, we consider a method for properly allocating new terms to the hierarchical structures of an existing thesaurus using rapidly evolving word embedding. In an experiment, word vectors of 500 degrees are constructed from 567,000 biomedical articles and are clustered after dimension reduction using principal component analysis. Then, semantic relations are estimated based on the spatial relations between the new term and any of the terms in the thesaurus. We then conducted a comparison of the results obtained from three experts. In future, we will develop a recommendation system for new terms related to the existing terms to support semi-automatic thesaurus maintenance.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"37 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":"125791093","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: 7

Combining Statistics-Based and CNN-Based Information for Sentence Classification 基于统计和基于cnn信息的句子分类

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0156

Lang Zhining, Gu Xiaozhuo, Zhou Quan, Xu Taizhong

{"title":"Combining Statistics-Based and CNN-Based Information for Sentence Classification","authors":"Lang Zhining, Gu Xiaozhuo, Zhou Quan, Xu Taizhong","doi":"10.1109/ICTAI.2016.0156","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0156","url":null,"abstract":"Sentence classification, serving as the foundation of the subsequent text-based processing, continues attracting researchers attentions. Recently, with the great success of deep learning, convolutional neural network (CNN), a kind of common architecture of deep learning, has been widely used to this filed and achieved excellent performance. However, most CNN-based studies focus on using complex architectures to extract more effective category information, requiring more time in training models. With the aim to get better performance with less time cost on classification, this paper proposes two simple and effective methods by fully combining information both extracted from statistics and CNN. The first method is S-SFCNN, which combines statistical features and CNN-based probabilistic features of classification to build feature vectors, and then the vectors are used to train the logistic regression classifiers. And the second method is C-SFCNN, which combines CNN-based features and statistics-based probabilistic features of classification to build feature vectors. In the two methods, the Naive Bayes log-count ratios are selected as the text statistical features and the single-layer and single channel CNN is used as our CNN architecture. The testing results executed on 7 tasks show that our methods can achieve better performance than many other complex CNN models with less time cost. In addition, we summarized the main factors influencing the performance of our methods though experiment.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"50 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":"129398055","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: 7

Effects of Emotional Visual Scenes on the Ability to Decode Emotional Melodies 情绪性视觉场景对情绪旋律解码能力的影响

2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) Pub Date : 2016-11-01 DOI: 10.1109/ICTAI.2016.0124

A. Esposito, A. Esposito, M. Esposito, M. Riviello, A. Vinciarelli, N. Bourbakis

{"title":"Effects of Emotional Visual Scenes on the Ability to Decode Emotional Melodies","authors":"A. Esposito, A. Esposito, M. Esposito, M. Riviello, A. Vinciarelli, N. Bourbakis","doi":"10.1109/ICTAI.2016.0124","DOIUrl":"https://doi.org/10.1109/ICTAI.2016.0124","url":null,"abstract":"An effective change in Human Computer Interaction requires to account of how communication practices are transformed in different contexts, how users sense the interaction with a machine, and an efficient machine sensitivity in interpreting users' communicative signals, and activities. To this aims, the present paper investigates on whether and how positive and negative visual scenes may alter listeners' ability to decode emotional melodies. Emotional tunes were played alone and with, either positive, or negative, or neutral emotional scenes. Afterword, subjects (8 groups, each of 38 subjects, equally balanced by gender) were asked to decode the emotional feeling aroused by melodies ascribing them either emotional valences (positive, negative, I don't know) or emotional labels (happy, sad, fear, anger, another emotion, I don't know). It was found that dimensional emotional features rather than emotional labels strongly affect cognitive judgements of emotional melodies. Musical emotional information is most effectively retained when the task is to assign labels rather than valence values to melodies. In addition, significant misperception effects are observed when happy or positively judged melodies are concurrently played with negative scenes.","PeriodicalId":245697,"journal":{"name":"2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"120 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":"132567751","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