著者

濱崎 雅弘 武田 英明 西村 拓一

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.25, no.1, pp.157-167, 2010

被引用文献数

11 2

---

The Web technology enables numerous people to collaborate in creation. We designate it as <i>massively collaborative creation via the Web</i>. As an example of massively collaborative creation, we particularly examine video development on <i>Nico Nico Douga</i>, which is a video sharing website that is popular in Japan. We specifically examine videos on <i>Hatsune Miku</i>, a version of a singing synthesizer application software that has inspired not only song creation but also songwriting, illustration, and video editing. As described herein, creators of interact to create new contents through their social network. In this paper, we analyzed the process of developing thousands of videos based on creators' social networks and investigate relationships among creation activity and social networks. The social network reveals interesting features. Creators generate large and sparse social networks including some centralized communities, and such centralized community's members shared special tags. Different categories of creators have different roles in evolving the network, e.g., songwriters gather more links than other categories, implying that they are triggers to network evolution.

著者

Yuhei Umeda

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.32, no.3, pp.D-G72_1-12, 2017-05-01 (Released:2017-05-01)

参考文献数

33

被引用文献数

55

---

This paper focuses on a classification problem for volatile time series. One of the most popular approaches for time series classification is dynamic time warping and feature-based machine learning architectures. In many previous studies, these algorithms have performed satisfactorily on various datasets. However, most of these methods are not suitable for chaotic time series because the superficial changes in measured values are not essential for chaotic time series. In general, most time series datasets include both chaotic and non-chaotic time series; thus, it is necessary to extract the more essential features of a time series. In this paper, we propose a new approach for volatile time series classification. Our approach generates a novel feature by extracting the structure of the attractor using topological data analysis to represent the transition rules of the time series. As this feature represents the essential property of systems of the time series, our approach is effective for both chaotic and non-chaotic types. We applied a learning architecture inspired by a convolutional neural network to this feature and found that the proposed approach improves performance in a human activity recognition problem by 18.5% compared with conventional approaches.

著者

Nurul Lubis Sakriani Sakti Koichiro Yoshino Satoshi Nakamura

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.33, no.1, pp.DSH-D_1-10, 2018-01-01 (Released:2018-01-31)

参考文献数

29

被引用文献数

2

---

To completely mimic the naturalness of human interaction in Human-Computer Interaction (HCI), emotion is an essential aspect that should not be overlooked. Emotion allows for a rich and meaningful human interaction. In communicating, not only we express our emotional state, but we are also affected by our conversational counterpart. However, existing works have largely focused only on occurrences of emotion through recognition and simulation. The relationship between an utterance of a speaker and the resulting emotional response that it triggers is not yet closely examined. Observation and incorporation of the underlying process that causes change of emotion can provide useful information for dialogue systems in making a more emotionally intelligent decision, such as being able to take proper action with regard to user’s emotion, and to be aware of the emotional implication of their response. To bridge this gap, in this paper, we tackle three main tasks: 1) recognition of emotional states, 2) analysis of social-affective events in spontaneous conversational data, to capture the relationship between actions taken in discourse and the emotional response that follows, and 3) prediction of emotional triggers and responses in a conversational context. The proposed study differs from existing works in that it focuses on the change of emotion (emotional response) and its cause (emotional triggers) on top of the occurrence of emotion itself. The analysis and experimental results are reported in detail in this paper, showing promising initial results for future works and development.

著者

岡谷 英夫

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.30, no.1, pp.257-264, 2015

被引用文献数

2

---

Sensory words such as onomatopoeia are difficult for students of Japanese because their cultures are different. How onomatopoeia are dealt with in elementary school compulsory education has been reviewed with the aim of considering how it can be applied to students of Japanese as a second language. Five Japanese textbooks that are currently in use at elementary schools for native speakers of Japanese were examined to see which onomatopoeic words appear and to what extent. A total of 6,443 onomatopoeic words were listed in these textbooks. Of the vast range of 6,443 words from the originally wide variety of words as counted from grade 1 to grade 6 from all the Japanese language textbooks, 92 were high-frequency onomatopoeic words which are proposed as the "basic onomatopoeia for beginners" as well as what kind of onomatopoeia and to what extent. These 92 high-frequency onomatopoeic words appeared 3,416 times, or 53.02% of the total 6,443 onomatopoeic words. If these 92 onomatopoeic words were studied, then over 50% of onomatopoeic words would be comprehensible to learners of Japanese. In addition, which verbs appear in conjunction with these onomatopoeic words together with their frequency are indicated.

著者

The Tung Nguyen Koichiro Yoshino Sakriani Sakti Satoshi Nakamura

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.35, no.1, pp.DSI-C_1-12, 2020-01-01 (Released:2020-01-01)

参考文献数

24

被引用文献数

2

---

In the past few years, there has been an increasing number of works on negotiation dialog. These studies mainly focus on situations where interlocutors work cooperatively to agree on a mutual objective that can fulfill each of their own requirements. However, in real-life negotiation, such situations do not happen all the time, and participants can tell lies to gain an advantage. In this research, we propose a negotiation dialog management system that detects when a user is lying and a dialog behavior for how the system should react when faced with a lie. We design our system for a living habits consultation scenario, where the system tries to persuade users to adopt healthy living habits. We show that we can use the partially observable Markov decision process (POMDP) to model this conversation and use reinforcement learning to train the system’s policy. Our experimental results demonstrate that the dialog manager considering deceptive states outperformed a dialog manager without this consideration in terms of the accuracy of action selection, and improved the true success rate of the negotiation in the healthcare consultation domain.

著者

土坂 恭斗 尾関 基行 岡 夏樹

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.29, no.1, pp.213-218, 2014

---

Pokémon is one of the most famous video games, which has more than 3.4 million players around the world. The interesting part of this game is to guess invisible information and the character of the opponent. However, existing Non Player Character (NPC) of this game is not a good alternative opponent to a human player because the NPC does not have variety of characteristics. In this paper, we propose a novel method to represent reflection - impulsivity characteristics of NPC by differences of the first stage prior distribution in Bayesian estimation used for decision-making of the NPC. In the experiment, we ask human players to take on three types of the proposed NPC and to answer the impression of those NPCs. As the result, the players feel different impressions from the three types of NPCs although they cannot identify the three types of the character (reflection - intermediate - impulsivity).

著者

篠田 匡弘 田中 克明 冨樫 祐一 篠田 匡史

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会全国大会論文集

巻号頁・発行日

pp.212, 2002 (Released:2003-07-10)

著者

鈴木 宏昭

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.19, pp.145-153, 2004-11-01

被引用文献数

6 1

---

The dynamic constraint relaxation theory predicts crucial roles of the initial diversity and evaluation in creative problem-solving. We reported the experimental evidence supporting these predictions, using an insight problem. The experiments showed that the degrees of making different types of trials and the appropriate evaluation were closely related to individual differences in insight problem-solving, and that evaluation became more appropriate by making the problem-solving goal explicit. The review of the research in related fields showed that these experimental findings were in congruent with the evidence obtained from different types of creative activities.

著者

Kentaro Kanamori Takuya Takagi Ken Kobayashi Hiroki Arimura

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.6, pp.C-L44_1-12, 2021-11-01 (Released:2021-11-01)

参考文献数

51

---

Post-hoc explanation methods for machine learning models have been widely used to support decision-making. Counterfactual Explanation (CE), also known as Actionable Recourse, is one of the post-hoc explanation methods that provides a perturbation vector that alters the prediction result obtained from a classifier. Users can directly interpret the perturbation as an “action” to obtain their desired decision results. However, actions extracted by existing methods often become unrealistic for users because they do not adequately consider the characteristics corresponding to the data distribution, such as feature-correlations and outlier risk. To suggest an executable action for users, we propose a new framework of CE, which we refer to as Distribution-Aware Counterfactual Explanation (DACE), that extracts a realistic action by evaluating its reality on the empirical data distribution. Here, the key idea is to define a new cost function based on the Mahalanobis distance and the local outlier factor. Then, we propose a mixed-integer linear optimization approach to extracting an optimal action by minimizing the defined cost function. Experiments conducted on real datasets demonstrate the effectiveness of the proposed method compared with existing CE methods.

著者

藤澤 瑞樹 齋藤 豪 奥村 学

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.19, pp.483-492, 2004-11-01

参考文献数

9

被引用文献数

3

---

Previous commentary systems generate commentaries only from the viewpoint of a commentator. However there are various viewpoints for comments, and such different viewpoints invoke various comments. The amount of information about a situation may differ between the viewpoints, and the understandings of the situation may also differ between them. In this paper, we propose a method to generate commentaries automatically so that users can easily understand situations by taking into account the different understandings of the situations between viewpoints. Our method is composed of two parts. The first is generation of comment candidates about the current situation, unexpected actions, intentions of players by using a game tree. The second is comment selection which chooses comments related to the prior one so that listeners can compare the situations from different viewpoints. Based on our approach, we implemented an experimental system that generates commentaries on mahjong games. We discuss the output of the system.

著者

三宅 陽一郎

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会全国大会論文集

巻号頁・発行日

pp.2O5E305, 2019 (Released:2019-06-01)

---

ステートマシンとビヘイビアツリーにいる新しい意思決定システムを開発し、それを実際のゲームタイトルに導入した。これをAI Graph と呼び、ノードの定義を工夫することで、2つの意思決定アルゴリズムをハイブリッドでかつ連結して使用することを可能とした。また開発時の工夫として、一度使ったグラフを何度も再利用できるようにし、エージェントの意思決定を深く作り込むことを可能とした。

著者

高木 将一 中村 啓佑 沼尾 正行

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会全国大会論文集

巻号頁・発行日

pp.72, 2001 (Released:2003-07-10)

被引用文献数

1

著者

鳥海 不二夫 山本 仁志 諏訪 博彦 岡田 勇 和泉 潔 橋本 康弘

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.25, no.1, pp.78-89, 2010

被引用文献数

3 9

---

In recent years, application of Social Networking Services (SNS) and Blogs are growing as new communication tools on the Internet. Several large-scale SNS sites are prospering; meanwhile, many sites with relatively small scale are offering services. Such small-scale SNSs realize small-group isolated type of communication while neither mixi nor MySpace can do that. However, the studies on SNS are almost about particular large-scale SNSs and cannot analyze whether their results apply for general features or for special characteristics on the SNSs. From the point of view of comparison analysis on SNS, comparison with just several types of those cannot reach a statistically significant level. We analyze many SNS sites with the aim of classifying them by using some approaches. Our paper classifies 50,000 sites for small-scale SNSs and gives their features from the points of network structure, patterns of communication, and growth rate of SNS. The result of analysis for network structure shows that many SNS sites have small-world attribute with short path lengths and high coefficients of their cluster. Distribution of degrees of the SNS sites is close to power law. This result indicates the small-scale SNS sites raise the percentage of users with many friends than mixi. According to the analysis of their coefficients of assortativity, those SNS sites have negative values of assortativity, and that means users with high degree tend to connect users with small degree. Next, we analyze the patterns of user communication. A friend network of SNS is explicit while users' communication behaviors are defined as an implicit network. What kind of relationships do these networks have? To address this question, we obtain some characteristics of users' communication structure and activation patterns of users on the SNS sites. By using new indexes, friend aggregation rate and friend coverage rate, we show that SNS sites with high value of friend coverage rate activate diary postings and their comments. Besides, they become activated when hub users with high degree do not behave actively on the sites with high value of friend aggregation rate and high value of friend coverage rate. On the other hand, activation emerges when hub users behave actively on the sites with low value of friend aggregation rate and high value of friend coverage rate. Finally, we observe SNS sites which are increasing the number of users considerably, from the viewpoint of network structure, and extract characteristics of high growth SNS sites. As a result of discrimination on the basis of the decision tree analysis, we can recognize the high growth SNS sites with a high degree of accuracy. Besides, this approach suggests mixi and the other small-scale SNS sites have different character trait.

著者

石濱 直樹 福島 洋介

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会全国大会論文集

巻号頁・発行日

pp.211, 2001 (Released:2003-07-10)

著者

平田 佐智子 中村 聡史 小松 孝徳 秋田 喜美

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.30, no.1, pp.274-281, 2015

---

Japanese "onomatopoeic" words (also called mimetics and ideophones) are more frequent in spoken discourse, especially in informal daily conversations, than in writing. It is a common belief that onomatopoeia is particularly frequent in some areas, such as the Kinki region. To examine the plausibility of this folk dialectology, we investigated the frequency of onomatopoeia in the Minutes of the Diet as a corpus of spoken Japanese. We examined whether there is really a difference in the use of onomatopoeia among the eleven major regions of Japan. We analyzed the conversation data (limited to the last two decades) according to the hometowns of the speakers. The results revealed that there is no cross-regional difference in the overall frequency of onomatopoeia and non-onomatopoeic adverbs. However, a particular morphological type of onomatopoeia?i.e., "emphatic" onomatopoeia, such as hakkiri 'clearly'?did show a regional variation in frequency. The results suggest that different types of onomatopoeia have different functions. The present study introduced a "macro-viewpoint" method that is based on a large-scale database. Further investigations into the functional aspect of onomatopoeia will also benefit from a dialectological method that adopts a "micro-viewpoint" on the detailed descriptions of a small number of speakers from each region. We hope that the present quantitative approach to the sociolinguistics of onomatopoeia will offer a new perspective on dialectology and on the effective utilization of onomatopoeia in the field of information science.

著者

Seiya Kawano Koichiro Yoshino Satoshi Nakamura

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.4, pp.E-KC9_1-14, 2021-07-01 (Released:2021-07-01)

参考文献数

48

---

Building a controllable neural conversation model (NCM) is an important task. In this paper, we focus on controlling the responses of NCMs using dialogue act labels of responses as conditions. We introduce a reinforcement learning framework involving adversarial learning for conditional response generation. Our proposed method has a new label-aware objective that encourages the generation of discriminative responses by the given dialogue act label while maintaining the naturalness of the generated responses. We compared the proposed method with conventional methods that generate conditional responses. The experimental results showed that our proposed method has higher controllability conditioned by the dialogue acts even though it has higher or comparable naturalness to the conventional models.

著者

長谷川 禎彦 伊庭 斉志

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.22, pp.37-47, 2007-11-01

参考文献数

34

被引用文献数

1 4

---

Genetic Programming (GP) is a powerful optimization algorithm, which employs the crossover for genetic operation. Because the crossover operator in GP randomly selects sub-trees, the building blocks may be destroyed by the crossover. Recently, algorithms called PMBGPs (Probabilistic Model Building GP) based on probabilistic techniques have been proposed in order to improve the problem mentioned above. We propose a new PMBGP employing Bayesian network for generating new individuals with a special chromosome called <I>expanded parse tree</I>, which much reduces a number of possible symbols at each node. Although the large number of symbols gives rise to the large conditional probability table and requires a lot of samples to estimate the interactions among nodes, a use of the expanded parse tree overcomes these problems. Computational experiments on two subjects demonstrate that our new PMBGP is much superior to prior probabilistic models.

著者

中山 浩太郎 伊藤 雅弘 ERDMANN Maike 白川 真澄 道下 智之 原 隆浩 西尾 章治郎

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.24, no.6, pp.549-557, 2009

被引用文献数

3 4

---

Wikipedia, a collaborative Wiki-based encyclopedia, has become a huge phenomenon among Internet users. It covers a huge number of concepts of various fields such as arts, geography, history, science, sports and games. As a corpus for knowledge extraction, Wikipedia's impressive characteristics are not limited to the scale, but also include the dense link structure, URL based word sense disambiguation, and brief anchor texts. Because of these characteristics, Wikipedia has become a promising corpus and a new frontier for research. In the past few years, a considerable number of researches have been conducted in various areas such as semantic relatedness measurement, bilingual dictionary construction, and ontology construction. Extracting machine understandable knowledge from Wikipedia to enhance the intelligence on computational systems is the main goal of "Wikipedia Mining," a project on CREP (Challenge for Realizing Early Profits) in JSAI. In this paper, we take a comprehensive, panoramic view of Wikipedia Mining research and the current status of our challenge. After that, we will discuss about the future vision of this challenge.

著者

桑原 教彰 桑原 和宏 安部 伸治 須佐見 憲史 安田 清

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.20, pp.396-405, 2005-11-01

参考文献数

22

被引用文献数

6 4

---

Providing good home-based care to people with dementia is becoming an important issue as the size of the elderly population increases. One of the main problems in providing such care is that it must be constantly provided without interruption, and this puts a great burden on caregivers, who are often family members. Networked Interaction Therapy is the name we call our methods designed to relieve the stress of people suffering from dementia as well as that of their family members. This therapy aims to provide a system that interacts with people with dementia by utilizing various engaging stimuli. One such stimulus is a reminiscence video created from old photo albums, which is a promising way to hold a dementia sufferer's attention for a long time. In this paper, we present an authoring tool to assist in the production of a reminiscence video by using photo annotations. We conducted interviews with several video creators on how they used photo annotations such as date, title and subject of photos when they produced the reminiscence videos. According to the creators' comments, we have defined an ontology for representing the creators' knowledge of how to add visual effects to a reminiscence video. Subsequently, we developed an authoring tool that automatically produces a reminiscence video from the annotated photos. Subjective evaluation of the quality of reminiscence videos produced with our tool indicates that they give impressions similar to those produced by creators using conventional video editing software. The effectiveness of presenting such a video to people with dementia is also discussed.

著者

岡田 将吾 賀 小淵 小島 量 長谷川 修

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.22, pp.493-507, 2007-11-01

被引用文献数

1

---

This paper presents an unsupervised approach of integrating speech and visual information without using any prepared data(training data). The approach enables a humanoid robot, Incremental Knowledge Robot 1 (IKR1), to learn words' meanings. The approach is different from most existing approaches in that the robot learns online from audio-visual input, rather than from stationary data provided in advance. In addition, the robot is capable of incremental learning, which is considered to be indispensable to lifelong learning. A noise-robust self-organized incremental neural network(SOINN) is developed to represent the topological structure of unsupervised online data. We are also developing an active learning mechanism, called ``desire for knowledge'', to let the robot select the object for which it possesses the least information for subsequent learning. Experimental results show that the approach raises the efficiency of the learning process. Based on audio and visual data, we construct a mental model for the robot, which forms a basis for constructing IKR1's inner world and builds a bridge connecting the learned concepts with current and past scenes.