2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)

25-27 Nov. 2016

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  • [Front cover]

    Publication Year: 2016, Page(s): c1
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  • [Copyright notice]

    Publication Year: 2016, Page(s): 2
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  • Table of contents

    Publication Year: 2016, Page(s):3 - 7
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  • General chairs and program chairs message

    Publication Year: 2016, Page(s):8 - 9
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  • Committees

    Publication Year: 2016, Page(s): 10
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  • Program committee

    Publication Year: 2016, Page(s):11 - 12
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  • Panel: AI now!

    Publication Year: 2016, Page(s): 17
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  • Panel: AI now in companies

    Publication Year: 2016, Page(s): 18
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  • Keynote speech: Keynote 1: It's all about AI

    Publication Year: 2016, Page(s):19 - 20
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    Summary form only given. In this talk, I will cover two topics which are closely related to AI. The first one is spatiotemporal learning of basketball offensive strategies” and the second one is learning to classify shot types.”Video-based group behavior analysis is drawing attention to its rich application in sports, military, surveillance and biological observations. Focusing speci... View full abstract»

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  • Keynote2: Intercultural collaboration as a multi-agent system

    Publication Year: 2016, Page(s): 21
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  • Keynote3: Contention and disruption

    Publication Year: 2016, Page(s):22 - 23
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  • Author index

    Publication Year: 2016, Page(s):278 - 280
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  • [Sponsors]

    Publication Year: 2016, Page(s): 1
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  • User behavior analysis and commodity recommendation for point-earning apps

    Publication Year: 2016, Page(s):170 - 177
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (1043 KB)

    In recent years, due to the rapid development of e-commerce, personalized recommendation systems have prevailed in product marketing. However, recommendation systems rely heavily on big data, creating a difficult situation for businesses at initial stages of development. We design several methods - including a traditional classifier, heuristic scoring, and machine learning - to build a recommendat... View full abstract»

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  • Topic suggestion by Bayesian network enhanced tag inference in community question answering

    Publication Year: 2016, Page(s):178 - 185
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (6963 KB) | HTML iconHTML

    Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work ai... View full abstract»

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  • The development of a simulated car racing controller based on Monte-Carlo tree search

    Publication Year: 2016, Page(s):104 - 109
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (272 KB)

    Ever since its introduction, Monte Carlo Tree Search (MCTS) has shown very good performances on a number of games, most of which are turn-based zero-sum games. More recently, researchers have also started to expand the application of MCTS to other types of games. This paper proposes a new framework of applying MCTS to the game of simulated car racing. We choose to build the search tree in a discre... View full abstract»

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  • Fast-searching algorithm for vector quantization using modified multiple triangular inequality

    Publication Year: 2016, Page(s):52 - 57
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (437 KB)

    This paper proposes a Modified Multiple Triangular Inequality Elimination (MMTIE) to further reduce the search number of candidate codevectors. The MMTIE adopts the same original search space as the MTIE scheme with the initial best-matched codevector selected by the Initial Index Code Assignment (IICA), and integrates the intersection rule of the Candidate Codevectors Group (CCG) scheme to furthe... View full abstract»

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  • Aspect-category-based sentiment classification with aspect-opinion relation

    Publication Year: 2016, Page(s):162 - 169
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (268 KB) | HTML iconHTML

    In recent years, researches of aspect-category-based sentiment analysis have been approached in terms of predefined categories. In this paper, we target two sub-tasks of SemEval-2014 Task 4 dedicated to aspect-based sentiment analysis: detecting aspect category and aspect category polarity. Also, a pre-identified set of aspect categories {food, price, service, ambience, miscellaneous} defined by S... View full abstract»

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  • Systematic selection of N-tuple networks with consideration of interinfluence for game 2048

    Publication Year: 2016, Page(s):186 - 193
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (206 KB) | HTML iconHTML

    The puzzle game 2048, a single-player stochastic game played on a 4 × 4 grid, is the most popular among similar slide-and-merge games. One of the strongest computer players for 2048 uses temporal difference learning (TD learning) on so called N-tuple networks, where the shapes of the N-tuples are given by human based on characteristics of the game. In our previous work (Oka and Matsuzaki, 2... View full abstract»

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  • Speed control in AOI system by using neural networks algorithm

    Publication Year: 2016, Page(s):66 - 72
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (418 KB) | HTML iconHTML

    This paper presents a two layer recurrent neural network employed in glass speed control transmitted by linear servo motor in Automated Optical Inspection (AOI) system platform. The recurrent neural network consists of an identifier and a controller, the identifier is used to catch a feedback signal from the position sensor and the controller is processed in microprocessor in order to supply an ad... View full abstract»

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  • Linking, integrating, and translating entities via iterative graph matching

    Publication Year: 2016, Page(s):248 - 255
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    Entity tasks, such as linking, integration, and translation, are crucial for many search and NLP applications. For this purposed entity graphs have been manually built or automatically harvested. In this paper, we survey existing approaches abstracting these problems into a graph-based iterative matching on a pair of entity graphs. View full abstract»

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  • Prediction of accrual expenses in balance sheet using decision trees and linear regression

    Publication Year: 2016, Page(s):73 - 77
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (202 KB)

    In response to globalization, International Financial Reporting Standards (IFRS) has become the norm of the global capital markets. Companies preparing financial statements using IFRS may make the financial situation fully disclosed. Nevertheless, an overestimated accrual expense of a balance sheet may not only underestimate the earnings data, but also increase the cash outflows of the statement o... View full abstract»

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  • A game informatical analysis of RoShamBo

    Publication Year: 2016, Page(s):116 - 123
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (589 KB) | HTML iconHTML

    This paper introduces a family of RoShamBo games, denoted by RSB(n,b,s,r) which means that n players simultaneously show a move among b possible moves with possible s winning regulations, at each round out of r round matches in total. The player who wins more after r rounds wins. A game informatical analysis of RSB(n,b,s,r) using game refinement measure is carried out, while experiments have been ... View full abstract»

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  • Transfer learning for sequential recommendation model

    Publication Year: 2016, Page(s):154 - 161
    Request permission for commercial reuse | Click to expandAbstract |PDF file iconPDF (289 KB)

    In this work, we address the problem of transfer learning for sequential recommendation model. Most of the state-of-the-art recommendation systems consider user preference and give customized results to different users. However, for those users without enough data, personalized recommendation systems cannot infer their preferences well or rank items precisely. Recently, transfer learning technique... View full abstract»

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  • Exploring multi-view learning for activity inferences on smartphones

    Publication Year: 2016, Page(s):212 - 219
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    Inferring activities on smartphones is a challenging task. Prior works have elaborated on using sensory data from built-in hardware sensors in smartphones or taking advantage of location information to understand human activities. In this paper, we explore two types of data on smartphones to conduct activity inference: 1) Spatial-Temporal: reflecting daily routines from the combination of spatial ... View full abstract»

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