2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)最新文献

Development of a Cebuano Parse Tree for a Grammar Correction Tool Using Deep Parsing 基于深度解析的语法校正工具的语法树的开发

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00042

Jan Mikhail Gaid, Robert Michael Lim, C. Maderazo

{"title":"Development of a Cebuano Parse Tree for a Grammar Correction Tool Using Deep Parsing","authors":"Jan Mikhail Gaid, Robert Michael Lim, C. Maderazo","doi":"10.1109/TAAI.2018.00042","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00042","url":null,"abstract":"Many technologies had surfaced to help people understand and learn a language. Learning major languages like English, Spanish, etc., was easier because a lot of people were speaking it and actually knew the structural integrity of its grammar, but what about the minor ones? How would you learn a language easily if you did not know its grammatical structure, especially if the language was not that known? The researchers would present a grammatical tool using deep parsing for Cebuano, a language that was mainly spoken in Central Visayas in the Philippines and was considered as one of the main languages in the whole Visayan region. This grammar tool would be useful mainly to people who wanted to learn the language; students, teachers, people from other regions of the country, and even foreigners. In this study, the researchers would relay the grammar through deep parsing, a method used to give a complete syntactic structure for a group of words. It also showed that the tool, with reliability marks higher than the expected 55%, would actually help the ones who needed it the most, and look forward for them into using it more.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116689204","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

Study on Green Logistics Initiatives through Text Mining 基于文本挖掘的绿色物流倡议研究

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00033

Fuyume Sai

引用次数: 0

TAAI 2018 Reviewers

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/taai.2018.00009

引用次数: 0

Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding 基于特征感知成本敏感标签嵌入的多标签分类

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00018

Hsien-Chun Chiu, Hsuan-Tien Lin

{"title":"Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding","authors":"Hsien-Chun Chiu, Hsuan-Tien Lin","doi":"10.1109/TAAI.2018.00018","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00018","url":null,"abstract":"Multi-label classification (MLC) is an important learning problem where each instance is annotated with multiple labels. Label embedding (LE) is an important family of methods for MLC that extracts and utilizes the latent structure of labels towards better performance. Within the family, feature-aware LE methods, which jointly consider the feature and label information during extraction, have been shown to reach better performance than feature-unaware ones. Nevertheless, current feature-aware LE methods are not designed to flexibly adapt to different evaluation criteria. In this work, we propose a novel feature-aware LE method that takes the desired evaluation criterion (cost) into account during training. The method, named Feature-aware Cost-sensitive Label Embedding (FaCLE), encodes the criterion into the distance between embedded vectors with a deep Siamese network. The feature-aware characteristic of FaCLE is achieved with a loss function that jointly considers the embedding error and the feature-to-embedding error. Moreover, FaCLE is coupled with an additional-bit trick to deal with the possibly asymmetric criteria. Experiment results across different data sets and evaluation criteria demonstrate that FaCLE is superior to other state-of-the-art feature-aware LE methods and competitive to cost-sensitive LE methods.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128667060","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

Personalized Content-Based Music Retrieval by User-Filtering and Query-Refinement 基于用户过滤和查询细化的个性化内容音乐检索

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00047

Ja-Hwung Su, T. Hong, Jyun-Yu Li, Jung-Jui Su

引用次数: 3

TAAI 2018 Program Committee TAAI 2018项目委员会

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/taai.2018.00008

A. Bakhtizin, Ayush Singhal

{"title":"TAAI 2018 Program Committee","authors":"A. Bakhtizin, Ayush Singhal","doi":"10.1109/taai.2018.00008","DOIUrl":"https://doi.org/10.1109/taai.2018.00008","url":null,"abstract":"Albert Bakhtizin, CEMI of RAS Aldy Gunawan, SMU Andrea Salfinger, JKU Ayush Singhal, UMN Bi-Ru Dai, NTUST Bor-Shen Lin, NTUST Cameron Browne, QUT Chang-Shing Lee, NI Cheng-Hsuan Li, NTCU Cheng-Zen Yang, YZU Chenn-Jung Huang, NDHU Chien-Feng Huang, NUK Chih-Chin Lai, NUK Chih-Hua Tai, NTPU Chih-Ya Shen, NTHU Chun-Hao Chen, TKU Chun-Wei Lin (Jerry Lin), HITSZ Chung-Kuang Chou, NTU Chung-Ming Ou, Kainan Univ. Churn-Jung Liau, Academia Sinica David L. Sallach, UChicago De-Nian Yang, Academia Sinica Fu-Shiung Hsieh, CYUT Gene P.K. Wu, PolyU Grace Lin, Asia Univ. GuanLing Lee, NDHU HaoChuan Wang, NTHU Hiroshi Kawakami, Kyoto Univ. Hong-Han Shuai, NCTU Hsiao-Ping Tsai, NCHU Hsin-Hung Chou, CJCU Hsiu-Min Chuang, NCU Hsu-Yung Cheng, NCU Hsuan-Tien Lin, NTU Hsun-Ping Hsieh, NCKU Hui-Ju Hung, PSU Hung-Yu Kao, NCKU I-Shyan Hwang, YZU Jen-Tzung Chien, NCTU Jen-Wei Huang, NCKU Jenn-Long Liu, ISU Jenq-Haur Wang, NTUT Jialin Liu, LBNL Jiann-Shu Lee, NUTN Jiun-Long Huang, NCTU Jung-Kuei Yang, NDHU Kazunori Mizuno, Takushoku Univ. Keng-Pei Lin, NSYSU Klaus Brinker, HSHL Koong Lin, NUTN Leilei Shi, BOC Intl. Ling-Jyh Chen, Academia Sinica Lung-Pin Chen, THU Marie-Liesse Cauwet, Paris-Sud Univ. Mark H.M. Winands, UM Masakazu Muramatsu, UEC Mi-Yen Yeh, Academia Sinica Min-Chun Hu, NCKU Ming-Feng Tsai, NCCU Mitsunori Matsushita, Kansai Univ. Mong-Fong Horng, KUAS Po-Ruey Lei, ROC Naval Academy Po-Yuan Chen, JUST Rung-Ching Chen, CYUT Sai-Keung Wong, NCTU Shie-Jue Lee, NSYSU Shih-Cheng Horng, CYUT Shih-Hung Wu, CYUT Shing-Tai Pan, NUK Shirley Ho, NCCU","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116756579","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

Successive Human Tracking and Posture Estimation with Multiple Omnidirectional Cameras 基于多全向摄像机的连续人体跟踪与姿态估计

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00019

Shunsuke Akama, Akihiro Matsufuji, E. Sato-Shimokawara, Shoji Yamamoto, Toru Yamaguchi

引用次数: 1

A Research on Document Summarization and Presentation System Based on Feature Word Extraction from Stored Informations 基于存储信息特征词提取的文档摘要与表示系统研究

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00022

Kei Matsubayashi, Akihiro Yamashita, H. Nonaka, Yohko Konno

引用次数: 2

A Method of Action Recognition in Ego-Centric Videos by Using Object-Hand Relations 基于物手关系的自我中心视频动作识别方法

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00021

Akihiro Matsufuji, Wei-Fen Hsieh, Hao-Ming Hung, Eri Shimokawara, Toru Yamaguchi, Lieu-Hen Chen

{"title":"A Method of Action Recognition in Ego-Centric Videos by Using Object-Hand Relations","authors":"Akihiro Matsufuji, Wei-Fen Hsieh, Hao-Ming Hung, Eri Shimokawara, Toru Yamaguchi, Lieu-Hen Chen","doi":"10.1109/TAAI.2018.00021","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00021","url":null,"abstract":"We present a system for integrating the neural networks' inference by using context and relation for complicated action recognition. In recent years, first person point of view which called as ego-centric video analysis draw a high attention to better understanding human activity and for being used to law enforcement, life logging and home automation. However, action recognition of ego-centric video is fundamental problem, and it is based on some complicating feature inference. In order to overcome these problems, we propose the context based inference for complicated action recognition. In realistic scene, people manipulate objects as a natural part of performing an activity, and these object manipulations are important part of the visual evidence that should be considered as context. Thus, we take account of such context for action recognition. Our system is consist of rule base architecture of bi-directional associative memory to use context of object-hand relationship for inference. We evaluate our method on benchmark first person video dataset, and empirical results illustrate the efficiency of our model.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125781988","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

Consideration of Life Rhythm for Hearing-Dog Robots Searching for User 助听犬机器人寻找用户的生命节奏思考

2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00031

S. Furuta, Tsuyoshi Nakamura, Y. Iwahori, S. Fukui, M. Kanoh, Koji Yamada

引用次数: 3