2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI)

20-22 Nov. 2015

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  • Author index

    Publication Year: 2015, Page(s):572 - 576
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  • Competitions

    Publication Year: 2015, Page(s): 570
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  • [Copyright notice]

    Publication Year: 2015, Page(s): 2
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  • [Front cover]

    Publication Year: 2015, Page(s): c1
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  • Flyer

    Publication Year: 2015, Page(s):577 - 580
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  • Keynote speech I production 4.0 from the perspective of intelligent computing

    Publication Year: 2015, Page(s): 25
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  • Keynote speech II evolutionary multi-objective optimization in engineering and prognostic applications

    Publication Year: 2015, Page(s): 26
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  • Keynote speech III controlled imprecision: Fuzzy technology for exploration processes

    Publication Year: 2015, Page(s): 27
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  • Keynote speech IV sentiment analysis, lifelong learning, and intelligent personal assistants

    Publication Year: 2015, Page(s): 28
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  • Keynote speech V deriving values from spatial trajectories

    Publication Year: 2015, Page(s): 29
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  • Keynote speech VI think fast ??? resource constrained reasoning and planning under uncertainty

    Publication Year: 2015, Page(s): 30
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  • Organization

    Publication Year: 2015, Page(s):15 - 18
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  • General chairs and program chairs message

    Publication Year: 2015, Page(s):13 - 14
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  • Toward social approach of classifying road lighting situation for community-centric system

    Publication Year: 2015, Page(s):53 - 57
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (2781 KB) | HTML iconHTML

    This paper proposes a method for classifying roads' lighting situation at night based on social approach. Information about roads' lighting situation is important in terms of safety and security of local communities, which is used for discussing anti-crime activities and route recommendation at night. However, it is difficult to know actual lighting situation on roads because of the lack of inform... View full abstract»

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  • Generate modern style Chinese poems based on common sense and evolutionary computation

    Publication Year: 2015, Page(s):315 - 322
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    Writing a poem is considered to be one of intelligent tasks that can be conducted by humans and that demand high competence on creativity, literary knowledge and common sense. This paper proposes an automated framework that can generate modern Chinese style poems under arbitrary topics. It is based on common sense knowledgebase ConceptNet and an evolutionary algorithm to search for a “best ... View full abstract»

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  • Fuzzy co-clustering considering site-wise confidence of vertically partitioned cooccurrence data

    Publication Year: 2015, Page(s):404 - 407
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (975 KB) | HTML iconHTML

    In many real world data analysis tasks, it is expected to get much more useful knowledge by utilizing multiple databases stored in different organizations, such as cooperation groups, state organs and allied countries. However, in many such organizations, they often hesitate to publish their databases because of privacy and security issues although they believe the advantages of collaborative anal... View full abstract»

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  • A study on fuzzy co-clustering with partial supervision and virtual samples

    Publication Year: 2015, Page(s):408 - 411
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (416 KB) | HTML iconHTML

    Semi-supervised clustering is a promising approach for improving partition quality of unsupervised clustering in large-scale data analysis while it is often difficult to utilize an enough amount of supervised objects. A virtual sample approach is a practical technique for improving classification quality in semi-supervised learning, in which additional virtual samples are generated by combining se... View full abstract»

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  • Constructing sentiment sensitive vectors for word polarity classification

    Publication Year: 2015, Page(s):252 - 259
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1833 KB) | HTML iconHTML

    Sentiment classification has been an essential part of opinion mining and sentiment analysis. This topic has been applied to real world scenarios such as mining customer reviews on merchandise sold online and film reviews of movies. Therefore, we aimed to gain insight into sentiment word classification, as it could serve as the foundation for larger scale sentiment analyses on corpuses and documen... View full abstract»

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  • Local Chan-Vese segmentation for non-ideal visible wavelength iris images

    Publication Year: 2015, Page(s):506 - 511
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (894 KB) | HTML iconHTML

    Iris segmentation becomes a challenging task for non-ideal iris shape captured under visible wavelength environment. In this paper, we proposed a localized active contour model for iris segmentation. A Local Chan-Vese (LCV) region-based active contour model is studied and applied to segment the non-ideal visible wavelength iris images. The proposed localized region-based formulation is more robust... View full abstract»

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  • Supporting consecutive data exploration by visualizing spatio-temporal trend information

    Publication Year: 2015, Page(s):227 - 231
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (799 KB) | HTML iconHTML

    This paper reports on a study in which a proposed interface that visualizes spatio-temporal trend information for exploratory data analysis was realized. The proposed system supports users' analysis of time-series data in an exploratory manner. Such exploratory analysis requires repeated access to various types of information related to the users' interests such as texts and numerical data. During... View full abstract»

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  • A new MCTS-based algorithm for multi-objective flexible job shop scheduling problem

    Publication Year: 2015, Page(s):136 - 141
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    Multi-objective flexible job-shop scheduling problem (MO-FJSP) is very important in both fields of production management and combinatorial optimization. Wu et al. proposed a Monte-Carlo Tree Search (MCTS) to solve MO-FJSP and successfully improved the performance of MCTS to find 17 Pareto solutions: 4 of Kacem 4×5, 3 of 10×7, 4 of 8×8, 4 of 10×10, and 2 of 15×10.... View full abstract»

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  • Remote sensing image registration with spatial restraint based on moment invariants and fast generalized fuzzy clustering

    Publication Year: 2015, Page(s):97 - 104
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1606 KB) | HTML iconHTML

    Image registration is a key component in remote sensing image processing. In this paper, we present a remote sensing image registration method by incorporating spatial restraint based on moment invariants and fast generalized fuzzy clustering. Seven moment invariants are extracted as features of objects obtained by the fast generalized fuzzy c-means (FGFCM) algorithm. The objects are matched throu... View full abstract»

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  • A practical divide-and-conquer approach for preference-based learning to rank

    Publication Year: 2015, Page(s):554 - 561
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (507 KB) | HTML iconHTML

    Preference-based learning to rank (LTR) is a model that learns the underlying pairwise preference with soft binary classification, and then ranks test instances based on pairwise preference predictions. The model can be viewed as an alternative to the popular score-based LTR model, which learns a scoring function and ranks test instances based on their scores directly. Many existing works on prefe... View full abstract»

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  • Applying hueristic algorithms to portfolio selection problem

    Publication Year: 2015, Page(s):323 - 329
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1276 KB) | HTML iconHTML

    In this paper, we solve the portfolio selection problem. In our approach, we first propose a modified immune algorithm (IA) to reuse the memory cells we got in earlier stages, so that more information can be utilized in the next stages. Our experimental results show that the modified IA can successfully obtain significantly higher return than genetic algorithm (GA) and particle swarm optimization ... View full abstract»

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  • Task selection for bandit-based task assignment in heterogeneous crowdsourcing

    Publication Year: 2015, Page(s):164 - 171
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1990 KB) | HTML iconHTML

    Task selection (picking an appropriate labeling task) and worker selection (assigning the labeling task to a suitable worker) are two major challenges in task assignment for crowdsourcing. Recently, worker selection has been successfully addressed by the bandit-based task assignment (BBTA) method, while task selection has not been thoroughly investigated yet. In this paper, we experimentally compa... View full abstract»

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