著者
秋葉 拓哉 林 孝紀 則 のぞみ 岩田 陽一
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.31, no.2, pp.B-F71_1-12, 2016-03-01 (Released:2016-02-18)
参考文献数
39

Estimating the relevance or proximity between vertices in a network is a fundamental building block of network analysis and is useful in a wide range of important applications such as network-aware searches and network structure prediction. In this paper, we (1) propose to use top-k shortest-path distance as a relevance measure, and (2) design an efficient indexing scheme for answering top-k distance queries. Although many indexing methods have been developed for standard (top-1) distance queries, no methods can be directly applied to top-k distance. Therefore, we develop a new framework for top-k distance queries based on 2-hop cover and then present an efficient indexing algorithm based on the recently proposed pruned landmark labeling scheme. The scalability, efficiency and robustness of our method are demonstrated in extensive experimental results. It can construct indices from large graphs comprising millions of vertices and tens of millions of edges within a reasonable running time. Having obtained the indices, we can compute the top-k distances within a few microseconds, six orders of magnitude faster than existing methods, which require a few seconds to compute these distances. Moreover, we demonstrate the usefulness of top-k distance as a relevance measure by applying them to link prediction, the most fundamental problem in graph data mining. We emphasize that the proposed indexing method enables the first use of top-k distance for such tasks.
著者
萩原 信吾 東条 敏
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.24, no.5, pp.405-416, 2009 (Released:2009-06-30)
参考文献数
34

In this paper, we propose a verification methodology of large-scale legal knowledge. With a revision of legal code, we are forced to revise also other affected code to keep the consistency of law. Thus, our task is to revise the affected area properly and to investigate its adequacy. In this study, we extend the notion of inconsistency besides of the ordinary logical inconsistency, to include the conceptual conflicts. We obtain these conflictions from taxonomy data, and thus, we can avoid tedious manual declarations of opponent words. In the verification process, we adopt extended disjunctive logic programming (EDLP) to tolerate multiple consequences for a given set of antecedents. In addition, we employ abductive logic programming (ALP) regarding the situations to which the rules are applied as premises. Also, we restrict a legal knowledge-base to acyclic program to avoid the circulation of definitions, to justify the relevance of verdicts. Therefore, detecting cyclic parts of legal knowledge would be one of our objectives. The system is composed of two subsystems; we implement the preprocessor in Ruby to facilitate string manipulation, and the verifier in Prolog to exert the logical inference. Also, we employ XML format in the system to retain readability. In this study, we verify actual code of ordinances of Toyama prefecture, and show the experimental results.
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
濱崎 雅弘 武田 英明 西村 拓一
出版者
一般社団法人 人工知能学会
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 (Released:2010-01-06)
参考文献数
25
被引用文献数
8 2

The Web technology enables numerous people to collaborate in creation. We designate it as massively collaborative creation via the Web. As an example of massively collaborative creation, we particularly examine video development on Nico Nico Douga, which is a video sharing website that is popular in Japan. We specifically examine videos on Hatsune Miku, 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
牧野 貴樹 合原 一幸
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.27, no.4, pp.253-262, 2012 (Released:2012-08-03)
参考文献数
24

It is not easy to test software used in studies of machine learning with statistical frameworks. In particular, software for randomized algorithms such as Monte Carlo methods compromises testing process. Combined with underestimation of the importance of software testing in academic fields, many software programs without appropriate validation are being used and causing problems. In this article, we discuss the importance of writing test codes for software used in research, and present a practical way for testing, focusing on programs using Monte Carlo methods.
著者
末吉 優 関 洋平
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.1, pp.WII-K_1-12, 2017-01-06 (Released:2017-01-20)
参考文献数
25

This paper proposes the following methods to search VOCALOID creators who publish music videos in Niconico video hosting service. For VOCALOID creator search, the user can utilize three clues: VOCALOID character name, music genre, and impressions. We defined the music genre by extending generic digital music genre with considering social tags annotated on VOCALOID music videos. We also implemented SVM-based music impression estimator utilizing viewer comments being over 0.8 points in F-values. We compared the proposal with three comparison methods in 12 search tasks and clarified the effectiveness of music genres and impressions.
著者
岩崎 祐貴 折原 良平 清 雄一 中川 博之 田原 康之 大須賀 昭彦
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.30, no.1, pp.152-160, 2015-01-06 (Released:2015-01-06)
参考文献数
30

Nowadays, anybody can easily express their opinion publicly through Consumer Generated Media. Because of this, a phenomenon of flooding criticism on the Internet, called flaming, frequently occurs. Although there are strong demands for flaming management, a service to reduce damage caused by a flaming after one occurs, it is very difficult to properly do so in practice. We are trying to keep the flaming from happening. It is necessary to identify the situation and the remark which are likely to cause flaming for our goal. Concretely, we propose methods to identify a potential tweet which will be a likely candidate of a flaming on Twitter, considering public opinion among Twitter users. Among three categories of flamings, our main focus is Struggles between Conflicting Values (SBCV), which is defined as a remark that forces one's own opinion about a topic on others. Forecasting of this type of flamings is potentially desired since most of its victims are celebrities, who need to care one's own social images. We proceed with a working hypothesis: a SBCV is caused by a gap between the polarity of the remark and that of public opinion. First, we have visualized the process how a remark gets flamed when its content is far from public opinion, by means of our original parameter daily polarity (dp). Second, we have built a highly accurate flaming prediction model with decision tree learning, using cumulative dp as an attribute along with parameters available from Twitter APIs. The experimental result suggests that the hypothesis is correct.
著者
鳥海 不二夫 榊 剛史 吉田 光男
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.35, no.4, pp.F-K45_1-7, 2020-07-01 (Released:2020-07-01)
参考文献数
20

The spread of COVID-19, the so-called new coronavirus, is currently having an enormous social and economic impact on the entire world. Under such a circumstance, the spread of information about the new coronavirus on SNS is having a significant impact on economic losses and social decision-making. In this study, we investigated how the new type of coronavirus has become a social topic in Japan, and how it has been discussed. In order to determine what kind of impact it had on people, we collected and analyzed Japanese tweets containing words related to the new corona on Twitter. First, we analyzed the bias of users who tweeted. As a result, it is clear that the bias of users who tweeted about the new coronavirus almost disappeared after February 28, 2020, when the new coronavirus landed in Japan and a state of emergency was declared in Hokkaido, and the new corona became a popular topic. Second, we analyzed the emotional words included in tweets to analyze how people feel about the new coronavirus. The results show that the occurrence of a particular social event can change the emotions expressed on social media.
著者
細馬 宏通 坊農 真弓 石黒 浩 平田 オリザ
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.29, no.1, pp.60-68, 2014-01-05 (Released:2014-01-07)
参考文献数
15

When the presence and the action of an android reach to those of human, andoroid can derive multi-modal action from human. How can human parties act with the android to organize the interaction and find the android as the social actor? We observed the development process of the play ``Three Sisters, Android Version'', and analyzed the multi-modal interaction between the android and human players in the process. As the result, the actors express the assessment of human likeness of the android with their utterances and body movements, and the border between human and machine was expressed with each modality in different way. Moreover, these expressions are not one-way product by the writer and director, but the product of repeated interactions between the actors and the android through the practice and rehearsals. Finally we discuss the possibility of ``media equation'' study using the direct observations of man-machine interaction.
著者
藏本 貴久 和泉 潔 吉村 忍 石田 智也 中嶋 啓浩 松井 藤五郎 吉田 稔 中川 裕志
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.28, no.3, pp.291-296, 2013 (Released:2013-03-28)
参考文献数
9
被引用文献数
5 2

In this study, we developed a new method of the long-term market analysis by using text-mining of news articles. Using our method, we conducted extrapolation tests to predict stock price averages by 19 industry and two market averages, TOPIX and Nikkei225 for about 10 years. As a result, 8 sectors in 21 sectors (about 40%) showed over about 60% accuracy, and 15 sectors in 21 sectors (over 70%) showed over about 55% accuracy. We also developed a web system of financial text-mining based on our method for financial professionals.
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
15

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
三浦 麻子 鳥海 不二夫 小森 政嗣 松村 真宏 平石 界
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.31, no.1, pp.NFC-A_1-9, 2016-01-06 (Released:2016-01-08)
参考文献数
27
被引用文献数
3

In this article, we investigate “retweeting in Twitter” or information transfer behavior in social media to figure out some characteristics of our information processing behavior in emergency situation from social psychological perspective. We made an exploratory log analysis of Twitter focusing on the relationship between diffusion of disaster information and user's emotional response on them. Disaster-related tweets which were retweeted over 10 times around the time of the Great East Japan Earthquake were extracted and emotional words in them were categorized and counted. Frequently retweeted tweets tended to include more negative (anxious or angry) or active emotional words than positive or inactive words. As results of multiple and quantile regression analyses, negative (especially anxious) or active emotional words in tweets had a significant effect on the increase of retweeting regardless of a kind of disasters. The results were discussed in terms of the difference with those based on common tweets.
著者
土坂 恭斗 尾関 基行 岡 夏樹
出版者
一般社団法人 人工知能学会
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, 2014-01-05 (Released:2014-02-07)
参考文献数
11

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
中村 友昭 長井 隆行 船越 孝太郎 谷口 忠大 岩橋 直人 金子 正秀
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.30, no.3, pp.498-509, 2015-05-01 (Released:2015-03-26)
参考文献数
30
被引用文献数
1

Humans develop their concept of an object by classifying it into a category, and acquire language by interacting with others at the same time. Thus, the meaning of a word can be learnt by connecting the recognized word and concept. We consider such an ability to be important in allowing robots to flexibly develop their knowledge of language and concepts. Accordingly, we propose a method that enables robots to acquire such knowledge. The object concept is formed by classifying multimodal information acquired from objects, and the language model is acquired from human speech describing object features. We propose a stochastic model of language and concepts, and knowledge is learnt by estimating the model parameters. The important point is that language and concepts are interdependent. There is a high probability that the same words will be uttered to objects in the same category. Similarly, objects to which the same words are uttered are highly likely to have the same features. Using this relation, the accuracy of both speech recognition and object classification can be improved by the proposed method. However, it is difficult to directly estimate the parameters of the proposed model, because there are many parameters that are required. Therefore, we approximate the proposed model, and estimate its parameters using a nested Pitman--Yor language model and multimodal latent Dirichlet allocation to acquire the language and concept, respectively. The experimental results show that the accuracy of speech recognition and object classification is improved by the proposed method.
著者
小川 祐樹 山本 仁志 宮田 加久子
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.29, no.5, pp.483-492, 2014-09-01 (Released:2014-08-27)
参考文献数
38
被引用文献数
2

The purpose of this paper is to test the Spiral of Silence theory in Internet society. Even today Noelle-Neumann's Spiral of Silence Theory is an important topic on the formation of public opinion. In the Spiral of Silence Theory up to now, the willingness to speak out has been handled as a dependent variable. However, there is significant bias in the question as to what extent the willingness to speak out actually influences the number of times a person speaks out. In addition, snowball sampling has been used, even in regard to the distribution of opinions of persons close to an individual. Accuracy increases because the attitudes of direct close users can be studied; however, only a small portion of close users can be studied. One defect of this approach is that it is actually quite costly. We use as a dependent variable the actual number of `tweets' on Twitter rather than willingness to speak out. In addition, for the attitude of close users, we used machine learning to estimate the attitudes of persons the users came in contact with, and we quantified homogeneity. We used and combined social investigations and behavior log analysis. With these, we were able to adopt simultaneously the following to a model: 1) individuals' internal situations, which can only be clarified by a questionnaire. 2) the actual quantity of behavior and the structure of communication networks, which can only be clarified through analysis of behavior logs. In the result, we found that a person's perception that their opinion in the majority and estimated homogeneity had a positive effect on the number of times a person spoke out. Our results suggest that the spiral of silence in regard to actual speaking out on Twitter.
著者
三宅 陽一郎
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.35, no.2, pp.B-J64_1-16, 2020-03-01 (Released:2020-03-01)
参考文献数
54

A game AI general theory has been researched and developed in game industry in the world, and a new game AI general theory of AI in digital game is supposed with three AIs. For a large scale of game, a game AI system consists of three types of AI such as meta-AI, character AI, and navigation AI. A meta-AI is to control a game dynamically from a bird-view by watching a player’s behavior. A character AI is a brain of a game character such as a buddy, a monster, or a villager to make a decision in real-time. A navigation AI is to recognize an environment of a game to find a path or a best location to move dynamically. Especially, character AI is a main topic to study in game development, and it includes many fields such as multi-layered structure, character animation, agent architecture, decision-making modules, and so on. A new method of decision-making of combination of behavior trees and state machines is supposed. It is called AI Graph. The game AI general theory was applied to an AI system of an action-RPG game “FINAL FANTASY XV”. The results are showed in the paper. All characters’ decision-making system in FINAL FANTASY XV are based on AI Graphs. An AI Graph Editor is a tool to make an AI Graph only by using a mouse and simple text inputs. A dynamics of the new method is showed by explaining AI Graph Editor precisely.
著者
田中 恒彦 岡嶋 美代 小松 孝徳
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.30, no.1, pp.282-290, 2015-01-06 (Released:2015-01-06)
参考文献数
26

We suggest as an important tool in psychotherapy the use of onomatopoeia. Mood disorder and Anxiety disorder are among the most prevalent mental disorders, and Behavior therapy (BT) is an evidence-based psychological treatment suitable for these cases. Interoceptive sensation is important in BT, because it serves as a barometer for responses. On the other hand, standard assessment methods such as subjects unit of disturbance scale (SUDs) is not optimal. In a different approach, we feel a certain form of it, e.g. Doki-Doki, at the same time when feeling emotion. However, the SUDs is assessed without taking somesthesis into consideration. In addition, BT requires information on somesthesis in order to optimally perform the therapy. Here we propose a solution to this problem, based on using onomatopoeia for SUDs. It can assess appropriately the interoceptive sensations by which a patient is accompanied in anxiety. We report two clinical cases using onomatopoeia for SUDs. This makes for an improved therapy. The internal sense appears during the course of the disease. A treatment is thus provided which is not tied to a diagnosis name, but rather by emphasizing the ``internal sense,'' which is more effective in producing an improvement towards curing.
著者
松本 慎平 川口 大貴 鳥海 不二夫
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.30, no.1, pp.393-402, 2015-01-01 (Released:2015-01-15)
参考文献数
31

At the time of the Great East Japan Earthquake, many Tweets of the disaster had been posted and Twitter had been effectively-utilized as an infrastructure for sharing disaster information and confirming safety. However in Twitter, there have been various kinds of information and also the volume is extremely huge, so a technology to effectively obtain the information on disaster or to filter users depending on their purpose of use are considered essential in order for Twitter to be effective at the time of disaster. Especially some kind of filtering mechanism to easily catch real humans' voices is assumed to be important for getting better performance out of Twitter at the time of disaster. The aim of this study is to numerically-express the characteristics of Twitter users by using the concept of entropy in response to each user's tweeting, replying, and retweeting activities, which are assumed to be the source of Twitter's real time feature, to show the details of Twitter users activities at the time of disaster, and to verify the possibility of this method for automatic user filtering. The real Twitter data distributed around the time of the earthquake is used to analyze, and especially in this paper, the difference of user attributes mainly between bot, cyborg and human is examined by using this data. From the experimental results, the characteristics of Twitter users were clarified with multidimensional quantitative values. The experimental results also showed the possibility for automatic user filtering.
著者
廣中 詩織 吉田 光男 岡部 正幸 梅村 恭司
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.1, pp.WII-M_1-11, 2017-01-06 (Released:2017-01-20)
参考文献数
24

The home locations of Twitter users can be estimated using a social network, which is generated by various relationships between users. There are many network-based location estimation methods with user relationships. However, the estimation accuracy of various methods and relationships is unclear. In this study, we estimate the users’home locations using four network-based location estimation methods on four types of social networks in Japan. We have obtained two results. (1) In the location estimation methods, the method that selects the most frequent location among the friends of the user shows the highest precision and recall. (2) In the four types of social networks, the relationship of follower has the highest precision and recall.
著者
小林 潤平 関口 隆 新堀 英二 川嶋 稔夫
出版者
一般社団法人 人工知能学会
雑誌
人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日
vol.32, no.2, pp.A-AI30_1-24, 2017-03-01 (Released:2017-03-01)
参考文献数
61
被引用文献数
2

We propose bunsetsu-based layouts to improve the efficiency of eye movements in reading Japanese text. When reading text, people tend to direct their gaze toward the center of a word. This is called the optimal viewing position. The optimal viewing position results in the shortest gaze durations and fewest re-fixations. In the case of Japanese text, the eyes tend to fixate on each characteristic Japanese linguistic unit (bunsetsu). An electronic Japanese text reader that facilitates accurate control of eye movements to bunsetsu segments could increase the reading rateand result in more efficient eye movements. In this study, we develop new techniques to decrease inefficient eye movements when reading Japanese text. In Experiment I, we investigate the effectiveness of the layout with bunsetsu-based line breaking. A bunsetsubased linefeed layout breaks a line between bunsetsu segments, i.e., splitting a bunsetsu segment is prohibited. The reading speed for the bunsetsu-based linefeed layout was faster compared to the conventional text layout with line lengths of 5–40 characters per line. The improvements in reading speed were likely due to the optimization of eye movements near the edge of a line. In the case of 5–11 characters per line, the improvements in reading speed were likely due to an increase in the number of lines that can be recognized by a single fixation. These results indicate that the bunsetsu-based linefeed layout is an effective technique to improve reading efficiency. In Experiment II, we develop a new micro-vibration text reader with bunsetsu-based segmentation. The new reader vibrates each bunsetsu segment in a different phase to enhance boundary information for eye guidance. The reading speed for the micro-vibration text was approximately 7%–12% faster compared to the stable text with line lengths of approximately 11–29 characters per line. The improvements in reading speed were likely due to a reduction in re-fixations within a bunsetsu segment and an increase in the number of lines that can be recognized by a single fixation without horizontal saccades. Moreover, 76% of the participants did not experience illegibility or incongruousness with the micro-vibration text reader. These results indicate that micro-vibration is an effective technique to improve the efficiency of reading text with line lengths of 11–29 characters per line without an increase in cognitive load or a decrease in comprehension. In Experiment III, we develop a new stepwise incremental indent layout with bunsetsu-based segmentation and a vertical scrolling operation. The reading speed obtained by the proposed layout of 4.4 characters per line was comparable to the fixed-line length layout of 29 characters per line. This improvement is primarily achieved by a reduction in the number of fixations. Moreover, 85% of the participants did not experience illegibility or incongruousness with the stepwise incremental indent layout reading. These results indicate that this layout is an effective technique to improve the efficiency of reading text with line lengths of 5 characters per line without an increase in cognitive load or a decrease in comprehension. These experimental results indicate that the Japanese electronic text reader with these proposed techniques can improve the reading speed of text with line lengths of 5–40 characters per line without an increase in cognitive load or decrease in comprehension.