[1U4-IS-1a-01]The impact of sentiment scores extracted from product descriptions on customer purchase intention
〇Yi Sun1, Yukio Ohsawa1(1. The University of Tokyo)
2023年度 人工知能学会全国大会（第37回）
2023年6月6日〜6月9日熊本城ホール(熊本県熊本市) ＋ オンライン
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2023年度 人工知能学会全国大会（第37回）
2023年6月6日〜6月9日熊本城ホール(熊本県熊本市) ＋ オンライン
当該イベント内で検索します。
検索する検索結果(1,326)
[1U4-IS-1a-02]Knowledge-aware attentional neural network for explainable recommendation
〇Yun Liu1, Jun Miyazaki2, Ryutaro Ichise2(1. National Institute of Advanced Industrial Science and Technology, 2. Tokyo Institute of Technology)
[1U4-IS-1a-03]FinKG-JP: A Japanese Financial Knowledge Graph
〇Natthawut Kertkeidkachorn1, Rungsiman Nararatwong2, Ziwei Xu2, Ryutaro Ichise3,2(1. Japan Advanced Institute of Science and Technology, 2. National Institute of Advanced Industrial Science and Technology, 3. Tokyo Institute of Technology)
[1U4-IS-1a-04]Incorporating Domain-Specific Traits into Personality-Aware Recommendations for Financial Applications
〇Takehiro Takayanagi1, Kiyoshi Izumi1(1. The University of Tokyo)
[1U4-IS-1a-05]Customer Clustering and Customer-Specific Product Recommendation by Distance from Core Customer Group in a Multidimensional Space of Purchase Behavioral Features
〇Kazuhiro Koike1,2, Daishi Sagawa2, Kenji Tanaka2(1. ASKUL Corporation, 2. Univ. of Tokyo)
[2U1-IS-1b-01]Dyadic Level Emotional Contagious Scenario through ECG and EDA Sensory Information: A Preliminary Experiment
〇Ahmed Salem1, Kaoru Sumi1(1. Future University Hakodate)
[2U1-IS-1b-02]Towards Commonsense Reasoning in Outdoor Visual Linguistic Navigation
〇Anirudh Reddy Kondapally1,2, Kentaro Yamada2, Hitomi Yanaka1(1. The University of Tokyo, 2. Honda R&D Co.,Ltd., Tokyo, Japan)
[2U1-IS-1b-03]Learning Graph Neural Networks with Key Subgraphs using Explanation Confidence
〇Kaito Inoue1, Jianming Huang1, Zhongxi Fang1, Hiroyuki Kasai1,2(1. Department of Computer Science and Communications Engineering, Graduate School of Fundamental Science and Engineering, Waseda University, 2. Department of Communications and Computer Engineering, FSE School, Waseda University)
[2U1-IS-1b-04]Artificial Intelligence-Based Models to Predict the Activation State of Molecular Pathway in Diseases
〇Shihori Tanabe1, Sabina Quader2, Ryuichi Ono1, Horacio Cabral3, Kazuhiko Aoyagi4, Akihiko Hirose1, Edward J Perkins5, Hiroshi Yokozaki6, Hiroki Sasaki4(1. National Institute of Health Sciences, 2. Innovation Center of NanoMedicine (iCONM), 3. The Univ. of Tokyo, 4. National Cancer Center Research Institute, 5. US Army Engineer Research and Development Center, 6. Kobe Univ.)
[2U1-IS-1b-05]Anaphora and semantic resolution by introducing multitasking into coreference algorithms
〇Theo Jean Poncelet1, Tomoyuki Maekawa1, Michita Imai1(1. Keio University)
[2U6-IS-1c-01]Direct calorie classification of West African dishes with a small dataset
〇Michel Ezoa Avotchi DJANGORAN1, KIKUCHI MASATO1, TADACHIKA OZONO1(1. Nagoya Institute of Technology)
[2U6-IS-1c-02]An Inexact Penalty Method for Fast Unbalanced Optimal Transport Optimization
〇Xun Su1, Hiroyuki Kasai1(1. Waseda University)
[2U6-IS-1c-03]Improving symbolic music pre-training using bar-level variational inference
〇YINGFENG FU1, Yusuke Tanimura2, Hidemoto Nakada2(1. University of Tsukuba, 2. AIST)
[2U6-IS-1c-04]Adversarial Self-attention MisdirectionImproving vision transformers performance with adversarial pre-training
〇Luiz Henrique Mormille1, Masayasu Atsumi1(1. Soka Univ.)
[1U3-IS-2a-01]Semi-Autoregressive Transformer for Sign Language Production
〇Ehssan Wahbi1, Masayasu Atsumi1(1. Soka University )
[1U3-IS-2a-02]Improving the efficiency of training physics-informed neural networks using active learning
〇Yuri Aikawa1, Naonori Ueda2, Toshiyuki Tanaka1(1. Univ. of Kyoto, 2. NTT Communication Science Laboratories)
[1U3-IS-2a-03]One-class Damage Detector Using Fully-Convolutional Data Description for Prognostics
〇Takato Yasuno1, Masahiro Okano1, Riku Ogata1, Junichiro Fujii1(1. Yachiyo Engineering Co.,Ltd. RIIPS)
[1U3-IS-2a-04]Gated Variable Selection Neural Network for Multimodal Sleep Quality Assessment
〇Yue Chen1, Takashi Morita2, Tsukasa Kimura2, Takafumi Kato3, Masayuki Numao2, Ken-ichi Fukui2(1. Graduate School of Information Science and Technology, Osaka University, 2. SANKEN (The Institute of Scientific and Industrial Research), Osaka University, 3. Graduate School of Dentistry, Osaka University)
[1U3-IS-2a-05]Performance Evaluation of SORT Algorithms in Tracking of Fish in a School
〇Alin Khaliduzzaman1, Takato Shibayama1, Hitoshi Habe2, Takayuki Niizato3, Hiroaki Kawashima1(1. Graduate School of Information Science, University of Hyogo, 2. Kindai University, 3. University of Tsukuba)
[1U5-IS-2b-01]Comparing Feature Extraction Methods for Sarcasm Detection in Twitter
〇Jenq-Haur Wang1, Rahmat Fadli Isnanto2(1. National Taipei University of Technology, 2. Sriwijaya University)
[1U5-IS-2b-02]Multilevel Sentence Embeddings for Personality Prediction
〇Paolo Tirotta1, Akira Yuasa1, Masashi Morita1(1. NTT DATA)
[1U5-IS-2b-03]Enhancing Financial Question Answering with Structured Knowledge
〇Rungsiman Nararatwong1, Natthawut Kertkeidkachorn2, Ziwei Xu1, Ryutaro Ichise3,1(1. National Institute of Advanced Industrial Science and Technology, 2. Japan Advanced Institute of Science and Technology, 3. Tokyo Institute of Technology)
[1U5-IS-2b-04]Improving Financial Terminologies Recognition regarding Morphological Inflection
〇Ziwei XU1, Rungsiman Nararatwong1, Natthawut Kertkeidkachorn3, Ryutaro Ichise 2,1(1. National Institute of Advanced Industrial Science and Technology,Japan, 2. Tokyo Institute of Technology, 3. Japan Advanced Institute of Science and Technology)
[1U5-IS-2b-05]Predicting CTR of Responsive Search Ads Using Handcrafted Features
〇Melvin Charles Ortua Dy1(1. OPT, Inc.)
[2U4-IS-2c-01]Hybrid models combining neural networks (NN), Gaussian process regressions (GPR), and high-dimensional model representations (HDMR) for more powerful machine learningWe show how using staple techniques such as NN or GPR as building blocks of a more involved method can enhance ML capabilities in high dimension and or with sparse data
〇Sergei Manzhos1, Shunsaku Tsuda1, Hyojae Lee1, Manabu Ihara1(1. Tokyo Institute of Technology)
[2U4-IS-2c-02]MANet: Mixed Attention Network for Visual Explanation
〇JINGJING BAI1, Yoshinobu Kawahara2,3(1. Kyushu University, 2. Osaka Univeristy, 3. RIKEN)
[2U4-IS-2c-03]Emotion-guided Multi-modal Fusion for Personality Traits Recognition
〇Yusong WANG1, Dongyuan LI1, Jialun SHEN1, Kotaro FUNAKOSHI1, Manabu OKUMURA1(1. Tokyo Institute of Technology)
[2U4-IS-2c-04]Cognitive Workload Estimation from Raw EEG Signals using Deep Learning
〇Yoji Yamashita1, Yukako Ito2, Haluka Numata2, Nagisa Masuda2, Ikuko Yairi1,2(1. Sophia University, 2. Graduate School of Science and Technology, Sophia University)
[2U4-IS-2c-05]Rapid training of Perceiver in a low-cost computing environment
〇Kaiyu Suzuki1, Tomofumi Matsuzawa1(1. Tokyo University of Science)
[3U1-IS-3-01]Quantitative Evaluation of Multi-agent Simulation using Generative Adversarial Network -- An Alternative of Qualitative Evaluation for Artificial Market Simulation
〇Masanori HIRANO1, Kiyoshi IZUMI1(1. The University of Tokyo)
[3U1-IS-3-02]Stability analysis of a financial system
〇Igor Zavialov1, Kazushi Ikeda1(1. Nara Institute of Science and Technology)
[3U1-IS-3-03]Using Social Force Maps to model idiosyncratic Movement of Crowd Flow Agents
〇Carl Kjaergaard2,1, Kenji Tanaka1(1. Tokyo University, 2. GRID INC)
[3U1-IS-3-04]Multi-agent deep-learning based comparative analysis in basketball
〇Ziyi Zhang1, Rory Bunker1, Kazuya Takeda1, Keisuke Fujii 1(1. Nagoya University)
[3U1-IS-3-05]Analysis of Carbon Neutrality Scenarios of Industrial Consumers Combining Power Generation, Storage, and DR Using an Electricity Market Model
〇Long Cheng1, Kiyoshi Izumi1, Masanori Hirano1(1. The University of Tokyo)
[3U5-IS-4-01]A neuro-symbolic approach for multimodal reference expression comprehension
〇Aman Jain1,2, Anirudh Reddy Kondapally1,2, Kentaro Yamada2, Hitomi Yanaka1(1. The University of Tokyo, 2. Honda R&D Co.,Ltd., Tokyo, Japan)
[3U5-IS-4-02]Bilingual Japanese/English robot dialogues with knowledge graphs and conversational AI
〇Graham Wilcock1,2(1. CDM Interact, Helsinki, Finland, 2. University of Helsinki, Finland)
[3U5-IS-4-03]Contextual Coaching: Support for Well-being based on Environmental Sensor Information and Conversational AI
〇Kristiina Jokinen1(1. AI Research Center AIST Tokyo Waterfront)
[3U5-IS-4-04]A Dynamic Recommendation System of Time-Varying and Geotagged Images from Surveillance Cameras
Lieu Hen Chen1, 〇Pin Chu Chien1, Tsu Wen Hsu1, Ying Yu Chen1, Hao Ming Hung1(1. National Chi Nan University)
[3U5-IS-4-05]Text Recognition in Low Resolution Images Using Trainable Regularization
〇Supatta Viriyavisuthisakul1, Parinya Sanguansat2, Teeradaj Racharak1, Minh Le Nguyen1, Toshihiko Yamasaki3(1. Japan Advanced Institute of Science and Technology, 2. Panyapiwat Institute of Management , 3. The University of Tokyo)
[2U5-IS-5-01]Investigation of a method for measuring affection and aversion by electroencephalography using images and odor stimuli
〇Nao Enoki1, Yukako Ito2, Yusuke Yokota3, Yasushi Naruse3, Ikuko Yairi1(1. Sophia University, 2. Graduate School of Science and Technology, Sophia University, 3. National Institute of Information and Communications Technology)
[2U5-IS-5-02]Electroencephalography and Electrocardiogram Measurement of Flow Experience during Gameplay
〇Kousuke Arai1, Yusuke Yokota2, Yasushi Naruse2, Ikuko Yairi1(1. Sophia University, 2. National Institute of Information and Communications Technology)
[2U5-IS-5-03]Force-based modeling of heterogeneous roles in coordinated behavior of a triad
〇Jun Ichikawa1, Keisuke Fujii2,3,4(1. Shizuoka University, 2. Nagoya University, 3. RIKEN, 4. PRESTO)
[2U5-IS-5-04]Topic-switch adapted Japanese Dialogue System based on PLATO-2
〇Donghuo Zeng1, Jianming Wu1, Yanan Wang1, Kazunori Matsumoto1, Gen Hattori1, Kazushi Ikeda1(1. KDDI Research, Inc.)
[2U5-IS-5-05]Real-Time Conversational Agents for Persuasive Marketing Content
〇Pinkie Anggia1, Kaoru Sumi1(1. Future University Hakodate)
[3Xin4-01]人間中心AIを用いた対話的セグメンテーション手法の\\リモートセンシング画像に対する適用
〇篠原 崇之1、李 勇鶴1、 坂元 光輝 1、佐藤 俊明1(1.株式会社 パスコ)
[3Xin4-02]特殊詐欺検知AI特殊詐欺における高齢者の心理状態予測
〇近野 恵1、紺野 剛史1、吉岡 隆宏1、井手 健太1、白石 壮大1、桐生 正幸2(1.富士通株式会社、2.東洋大学)
[3Xin4-03]超大規模コーパスからの抽出コーパスによる言語モデルのタスク適応
〇本浦 庄太1、秋元 康佑1、槇尾 純太1、定政 邦彦1(1.日本電気株式会社)
[3Xin4-04]診療データを用いた予測モデルによる文抽出
〇三沢 翔太郎1、古川 大記2、大山 慎太郎3、狩野 竜示1、鑓水 大和1、谷口 友紀1、小野田 浩平1、佐藤 菊枝2、白鳥 義宗2(1.富士フイルム株式会社、2.名古屋大学医学部附属病院 メディカルITセンター、3.名古屋大学 予防早期医療創成センター)
[3Xin4-05]小規模需要家グループの短期需要予測に向けた 次世代スマートメータによる需要家個別データの活用可能性の検討
〇露木 雅文1、小牧 大輔1(1.株式会社 日立製作所)
[3Xin4-06]1on1ミーティング時のメモを用いたワークメンタリティの好不調の推定
〇宇野 渉1、仲間 大輔1(1.株式会社リクルートマネジメントソリューションズ)
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