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2012 IEEE 24th International Conference on Tools with Artificial Intelligence最新文献

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Sentix: An Aspect and Domain Sensitive Sentiment Lexicon Sentix:面向和领域敏感的情感词汇
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.43
H. Lek, D. Poo
{"title":"Sentix: An Aspect and Domain Sensitive Sentiment Lexicon","authors":"H. Lek, D. Poo","doi":"10.1109/ICTAI.2012.43","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.43","url":null,"abstract":"Sentiment lexicons have often been used to aid sentiment analysis. Most of these sentiment lexicons are general-purpose lexicons which assign a fixed polarity to every word. However, it has been noted that the polarity of words depends on both the aspect and domain, thus a general-purpose sentiment lexicon would not be able to accurately classify the sentiment of words. This paper proposes a method to automatically construct an aspect and domain sensitive sentiment lexicon which assigns polarity to a word depending on its aspect and domain, and make available Sentix which is an aspect and domain sensitive sentiment lexicon spanning over 200 product domains. Experimental results have shown that our lexicon produces significantly better results compared to other commonly used lexicons. We also observe the long tail distribution behavior of product aspects, and propose the possibility of aspect ranking by comparing the number of domains and number of sentiment words present for an aspect.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128146164","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 Exploratory Analysis Tool for a Long-Term Video from a Stationary Camera 一种用于固定摄像机长期视频的探索性分析工具
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.185
Ryoji Nogami, B. Shizuki, H. Hosobe, J. Tanaka
{"title":"An Exploratory Analysis Tool for a Long-Term Video from a Stationary Camera","authors":"Ryoji Nogami, B. Shizuki, H. Hosobe, J. Tanaka","doi":"10.1109/ICTAI.2012.185","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.185","url":null,"abstract":"We present an interactive tool for the exploratory analysis of a long-term video from a stationary camera. The tool consists of three key methods: spatial change visualization, temporal change visualization, and similarity-based video retrieval. The first two methods provide the summarization of the long-term video that lets the user know where and when changes frequently occurred during a certain period, enabling the user to find an event of interest from the long-term video. In addition, with the third method, the user can search the video for a similar event, enabling the user to count events of interest and to observe distributions of such events. These methods are uniformly implemented using frame differences in 1-bit depth, making the implementation of these methods simple but efficient.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128336116","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
Class-Dependent Locality Preserving Projections for Multimodal Scenarios 多模态情景的类相关局部保持投影
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.139
Elias R. Silva, George D. C. Cavalcanti, Ing Ren Tsang
{"title":"Class-Dependent Locality Preserving Projections for Multimodal Scenarios","authors":"Elias R. Silva, George D. C. Cavalcanti, Ing Ren Tsang","doi":"10.1109/ICTAI.2012.139","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.139","url":null,"abstract":"This paper proposes a method for linear feature extraction called Class-dependent Locality Preserving Projections. It is a supervised extension of the Locality Preserving Projection algorithm and it aims to work in scenarios with within-class multimodality, which are those scenarios where the scattering of the patterns follows more than one modal distribution. Differently from the classical feature extraction techniques that build their solutions based on the whole dataset, the Class-dependent Locality Preserving Projections looks at each class separately, building a specific projection for each class. The proposed technique analyses a query pattern based on the output of each class and chooses the class that better fit the pattern. The experimental study shows that the Class-dependent Locality Preserving Projections is a feature extraction technique for general purposes, however, it is particularly well succeed when applied to within-class multimodal scenarios.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131842794","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
Document Classification by Computing an Echo in a Very Simple Neural Network 在一个非常简单的神经网络中计算回声的文档分类
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.104
Christophe Brouard
{"title":"Document Classification by Computing an Echo in a Very Simple Neural Network","authors":"Christophe Brouard","doi":"10.1109/ICTAI.2012.104","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.104","url":null,"abstract":"In this paper we present a new classification system called ECHO. This system is based on a principle of echo and applied to document classification. It computes the score of a document for a class by combining a bottom-up and a top-down propagation of activation in a very simple neural network. This system bridges a gap between Machine Learning methods and Information Retrieval since the bottom-up and the top-down propagations can be seen as the measures of the specificity and exhaustivity which underlie the models of relevance used in Information Retrieval. The system has been tested on the Reuters 21578 collection and in the context of an international challenge on large scale hierarchical text classification with corpus extracted from Dmoz and Wikipedia. Its comparison with other classification systems has shown its efficiency.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127992402","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
Modularizing OWL Ontologies Using $E^{DDL} _{HQ^+}$ $mathcal{SHIQ}$ 基于$E^{DDL} _{HQ^+}$ $mathcal{SHIQ}$的OWL本体模块化
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.63
Georgios M. Santipantakis, G. Vouros
{"title":"Modularizing OWL Ontologies Using $E^{DDL} _{HQ^+}$ $mathcal{SHIQ}$","authors":"Georgios M. Santipantakis, G. Vouros","doi":"10.1109/ICTAI.2012.63","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.63","url":null,"abstract":"Ontology modularization concerns about extracting ontology units from ontologies and partitioning large ontologies to possibly interdependent ontology units. Each unit specifies a specific context for performing ontology maintenance, evolution and reasoning tasks, which nevertheless has to be combined with chunks of tasks performed in other units. The modularization task is affected by assumptions concerning the mutual relations between the domains covered by distinct units, as well as by the expressiveness of the language used for specifying knowledge in units and for connecting distinct units. This paper presents a tool for partitioning SHIQ ontologies into units. These units can be combined using subjective class-to-class correspondences, as well as by inter-unit link properties that can be subjected to cardinality restrictions, existential and universal quantifiers, be hierarchically related and be transitive. While the modularization algorithm incorporated in this tool implements a specific partitioning method, the underlying representation framework provides a range of modularization possibilities, from units connected via class correspondences, to highly intertwined units, combined with class correspondences and inter-unit properties associated with restrictions.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131583855","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
Probabilistic Extension of Allen's Relations Using the Hourglass Model 用沙漏模型对Allen关系的概率推广
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.157
Sergios Petridis, Alexandros Psomas
{"title":"Probabilistic Extension of Allen's Relations Using the Hourglass Model","authors":"Sergios Petridis, Alexandros Psomas","doi":"10.1109/ICTAI.2012.157","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.157","url":null,"abstract":"This paper presents a probabilistic extension of Allen's relations that enables reasoning with intervals whose boundaries are uncertain. Building on an earlier work on an hourglass model that depicts the geometry of interval relations, we first provide further evidence that support its qualitative properties. We then specify two orthogonal axes, which quantitatively describe respectively the relative position and relative size of intervals. The quantitative hourglass model is then used to define a consistent probabilistic set of all thirteen Allen's relations. Probabilistic relations between intervals and points are also accounted for in the developed framework.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"465 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132985663","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
Texture and Shadow Insensitive Metric for Image-Based Reconstruction 基于图像重建的纹理和阴影不敏感度量
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.140
Rui Wu, Xu Zhao, Zhong Zhou, Wei Wu
{"title":"Texture and Shadow Insensitive Metric for Image-Based Reconstruction","authors":"Rui Wu, Xu Zhao, Zhong Zhou, Wei Wu","doi":"10.1109/ICTAI.2012.140","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.140","url":null,"abstract":"This paper proposes an accurate metric for image based 3d reconstruction without ground truth. Specially, our metric is insensitive to texture changing and shadows, which are commonly occurred in real world scenes. Based on the interreflected rendering model, we improve the accuracy of previous irradiance based metric. Additionally, we estimate the reflectance of each vertex on the surface to support the case with varying reflectance. We also consider the difference between estimated and observed irradiance in our metric to further eliminate the boundary effect of texture changing or self-shadow. Experiments on both indoor and outdoor datasets illustrate the effectiveness of our metric. Our evaluation results are not only more accurate than the results of previous metrics, but also insensitive to the texture and shadow.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131606595","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
Object-Oriented Representation and Hierarchical Reinforcement Learning in Infinite Mario 《无限马里奥》中的面向对象表示和层次强化学习
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.152
Mandar Joshi, R. Khobragade, Saurabh Sarda, U. Deshpande, Shiwali Mohan
{"title":"Object-Oriented Representation and Hierarchical Reinforcement Learning in Infinite Mario","authors":"Mandar Joshi, R. Khobragade, Saurabh Sarda, U. Deshpande, Shiwali Mohan","doi":"10.1109/ICTAI.2012.152","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.152","url":null,"abstract":"In this work, we analyze and improve upon reinforcement learning techniques used to build agents that can learn to play Infinite Mario, an action game. We extend the object-oriented representation by introducing the concept of object classes which can be effectively used to constrain state spaces. We then use this representation combined with the hierarchical reinforcement learning model as a learning framework. We also extend the idea of hierarchical RL by designing a hierarchy in action selection using domain specific knowledge. With the help of experimental results, we show that this approach facilitates faster and efficient learning for this domain.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115656402","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: 10
Combining Color and Topology for Partial Matching 结合颜色和拓扑进行部分匹配
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.109
D. Santos, I. Silva, D. Guliato, Manuel J. Fonseca
{"title":"Combining Color and Topology for Partial Matching","authors":"D. Santos, I. Silva, D. Guliato, Manuel J. Fonseca","doi":"10.1109/ICTAI.2012.109","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.109","url":null,"abstract":"Although, color is one of the most visually distinguishable visual properties, color alone is not enough to describe the content of images. The spatial organization of the different color regions also play an important role. In this paper, we propose and evaluate a new descriptor that combines information about color and about its spatial arrangement in an image. Moreover, the mechanism used to compute the descriptor provides support for partial matching of images and for the development of efficient retrieval systems. We first describe the spatial arrangement of the color regions using a topological graph, where vertices represent the color regions and edges represent connections between regions and also the color differences between them. To compute the descriptor from this graph representation we use the spectral graph theory, avoiding the need for direct graph comparison. We performed various experimental evaluations to compare the accuracy of our new descriptor with descriptors based only on color, based only on topological information and a combination of both.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115945926","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
Compiling Domain Consequences 编译域结果
2012 IEEE 24th International Conference on Tools with Artificial Intelligence Pub Date : 2012-11-07 DOI: 10.1109/ICTAI.2012.89
Alexandre Papadopoulos, B. O’Sullivan
{"title":"Compiling Domain Consequences","authors":"Alexandre Papadopoulos, B. O’Sullivan","doi":"10.1109/ICTAI.2012.89","DOIUrl":"https://doi.org/10.1109/ICTAI.2012.89","url":null,"abstract":"This paper presents a method for computing all the domain consequences of a constraint satisfaction problem. Domain consequences are a generalisation of prime implicates to multi-valued constraint problems. We define ordered automata to encode a large, potentially exponential, number of domain consequences. We design a range of algorithms that directly operate on this compact representation, with a complexity that depends on its size and not the size of the encoded set. This allows us to generate the domain consequences of a problem even for problems that have an exponential number of domain consequences. Furthermore, a simple empirical study illustrates the effectiveness of the method in compiling a large number of domain consequences, and the compactness of this representation.","PeriodicalId":155588,"journal":{"name":"2012 IEEE 24th International Conference on Tools with Artificial Intelligence","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116428645","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
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