著者

木村 考宏 川村 隆浩 渡邊 勝太郎 松本 尚也 佐藤 智宣 櫛田 達矢 松邑 勝治

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.N-F73_1-12, 2016-03-01 (Released:2016-03-31)

参考文献数

9

被引用文献数

1 1

---

In order to develop innovative solutions in science and technology, Japan Science and Technology Agency (JST) has built J-GLOBAL knowledge (JGk), which provides papers, patents, researchers' information, technological thesaurus, and scientific data as Linked Data, which have been accumulated by JST since 1957. The total size of all datasets is about 15.7 billion triples, and the JGk website provides a SPARQL endpoint to access part of the datasets. This paper describes several issues on schema design to construct a large-scale Linked Data, and construction methods, especially for linking to external datasets, such as DBpedia Japanese. Finally, we describe performance problems and the future works.

著者

中村 覚 佐久間 淳 小林 重信 小野 功

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第22回全国大会(2008)

巻号頁・発行日

pp.83, 2008 (Released:2009-07-31)

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本論文では,クォートドリブン市場におけるマーケットメーカー(MM)の戦略獲得問題を,MMの利益および約定率の観点から多目的最適化問題として定式化し,多目的遺伝的アルゴリズムにより戦略の最適化を行う手法を提案する.

著者

則 のぞみ ボレガラ ダヌシカ 鹿島 久嗣

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.168-176, 2014-01-05 (Released:2014-01-07)

参考文献数

24

被引用文献数

1 1

---

Many phenomena in the real world can be represented as multinomial relations, which involve multiple and heterogeneous objects. For instance, in social media, users' various actions such as adding annotations to web resources or sharing news with their friends can be represented by multinomial relations which involve multiple and heterogeneous objects such as users, documents, keywords and locations. Predicting multinomial relations would improve many fundamental applications in various domains such as online marketing, social media analyses and drug development. However, the high-dimensional property of such multinomial relations poses one fundamental challenge, that is, predicting multinomial relations with only a limited amount of data. In this paper, we propose a new multinomial relation prediction method, which is robust to data sparsity. We transform each instance of a multinomial relation into a set of binomial relations between the objects and the multinomial relation of the involved objects. We then apply an extension of a low-dimensional embedding technique to these binomial relations, which results in a generalized eigenvalue problem guaranteeing global optimal solutions. We also incorporate attribute information as side information to address the ``cold start"problem in multinomial relation prediction. Experiments with various real-world social web service datasets demonstrate that the proposed method is more robust against data sparseness as compared to several existing methods, which can only find sub-optimal solutions.

著者

松村 真宏 河原 大輔 岡本 雅史 黒橋 禎夫 西田 豊明

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.22, no.1, pp.93-102, 2007 (Released:2007-01-05)

参考文献数

18

被引用文献数

1 3

---

To overcome the limitation of conventional text-mining approaches in which frequent patterns of word occurrences are to be extracted to understand obvious user needs, this paper proposes an approach to extracting questions behind messages to understand potential user needs. We first extract characteristic case frames by comparing the case frames constructed from target messages with the ones from 25M sentences in the Web and 20M sentences in newspaper articles of 20 years. Then we extract questions behind messages by transforming the characteristic case frames into interrogative sentences based on new information and old information, i.e., replacing new information with WH-question words. The proposed approach is, in other words, a kind of classification of word occurrence pattern. Qualitative evaluations of our preliminary experiments suggest that extracted questions show problem consciousness and alternative solutions -- all of which help to understand potential user needs.

著者

柴田 雅博 冨浦 洋一 西口 友美

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.6, pp.507-519, 2009 (Released:2009-09-04)

参考文献数

19

被引用文献数

5 7

---

We propose an open-ended dialog system that generates a proper sentence to a user's utterance using abundant documents on the World Wide Web as sources. Existing knowledge-based dialog systems give meaningful information to a user, but they are unsuitable for open-ended input. The system Eliza can handle open-ended input, but it gives no meaningful information. Our system lies between the above two dialog systems; it converses on various topics and gives meaningful information related to the user's utterances. The system selects an appropriate sentence as a response from documents gathered through the Web, on the basis of surface cohesion and shallow semantic coherence. The surface cohesion follows centering theory and the semantic coherence is calculated on the basis of the conditional distribution and inverse document frequency of content words (nouns, verbs, and adjectives.) We developed a trial system to converse about movies and experimentally found that the proposed method generated 66% appropriate responses.

著者

杉山 弘晃 目黒 豊美 東中 竜一郎 南 泰浩

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.183-194, 2015-01-06 (Released:2015-01-06)

参考文献数

18

被引用文献数

1 1

---

The development of open-domain conversational systems is difficult since user utterances are too flexible for such systems to respond properly. To address this flexibility, previous research on conversational systems has selected system utterances from web articles based on word-level similarity with user utterances; however, the generated utterances, which originally appeared in different contexts from the conversation, are likely to contain irrelevant information with respect to the input user utterance. To leverage the variety of web corpus in order to respond to the flexibility and suppress the irrelevant information simultaneously, we propose an approach that generates system utterances with two strongly related phrase pairs: one that composes the user utterance and another that has a dependency relation to the former. By retrieving the latter one from the web, our approach can generate system utterances that are related to the topics of user utterances. We examined the effectiveness of our approach with following two experiments. The first experiment, which examined the appropriateness of response utterances, showed that our proposed approach significantly outperformed other retrieval and rule-based approaches. The second one was a chat experiment with people, which showed that our approach demonstrated almost equal performance to a rule-based approach and outperformed other retrieval-based approaches.

著者

蜷川 繁

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第17回全国大会(2003)

巻号頁・発行日

pp.231, 2003 (Released:2004-02-03)

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本研究では遺伝的アルゴリズムを用いて,サブサンプション・アーキテクチャを用いた自律移動ロボットのプログラムの進化実験を行った.実ロボットを使って実験を行ったところ,数世代でゴールに到達する個体が得られた.

著者

白松 俊 トッサヴァイネン テーム 大囿 忠親 新谷 虎松

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.LOD-C_1-11, 2016-01-06 (Released:2016-01-08)

参考文献数

25

---

To address social issues about the sustainability of local societies, inter-organizational collaboration in public sphere is important. Although conventional social networking services (SNSs) have recently been used for public collaboration, the SNSs are not suitable to look for potential collaborators because the conventional SNSs emphasize recency of information and lack a function for sharing information about ``who are trying to address what kind of social issues''. We designed a data model for structuring public issues and goals and built a linked open dataset (LOD) based on the above data model. Moreover, we developed a method for calculating similarities of public goals and implemented a Web service for matching public goals for finding potential collaborators. Our method for similarity calculation incorporates surficial features, semantic features, and contextual features. We conducted an experiment to investigate an optimal balance of parameters of the contextual features, which is suitable for facilitating public collaboration. Furthermore, we held a participatory event for trial use by citizens and observed positive feedbacks from the participants.

著者

杉山 貴昭 船越 孝太郎 中野 幹生 駒谷 和範

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.3, pp.C-FB2_1-9, 2016-05-01 (Released:2016-05-25)

参考文献数

18

被引用文献数

1

---

When a robot interacts with users in public spaces, it receives various sounds such as surrounding noises and users' voices. And furthermore, the robot needs to interact with multiple people at the same time. If the robot incorrectly determines whether it should respond to these sounds, it will erroneously respond to surrounding noises or ignore user utterances directed to the robot. In this paper, we present a machine learning-based method to estimate a response obligation, i.e., whether the robot should respond to an input sound. We address a problem setting that is more similar to interactions in public spaces than those assumed in previous studies. While previous studies assume only utterances directed to one of interlocutors as input sounds, we deal with not only those utterances but also noises and monologues. To deal with various sounds, our method uses the results of input sound classification and user behaviors both in an input sound interval and after the interval. In particular, the user behaviors after the interval are introduced as a key factor for improving the estimation accuracy of response obligation, such as a tendency that a user stands and keeps still after he/she talks to the robot. We demonstrate the new features significantly improved the estimation performance. We also investigate performances with various combinations of features and reveal that the results of input sound classification and the user behaviors after the interval are helpful for the estimation.

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

pp.B-F71, (Released:2015-10-27)

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

山田 広明 橋本 敬

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.2, pp.491-497, 2015-03-01 (Released:2015-03-17)

参考文献数

11

被引用文献数

2

---

In order to investigate the formation mechanism of community activity, we constructed an agent-based model based on a scenario driven by subjective norm and self-efficacy utilizing a community task game. The model demonstrated the spontaneous formation of community activity. The formation and expansion were driven by two mechanisms: (1) self-efficacy maintained participation of agents having a neutral attitude towards community activity, (2) subjective norm caused an increase in participation by involving other adjacent neutral attitude agents. We suggest a reasonable strategy promoting the spontaneous formation of community activity on the basis of this mechanism.

著者

伊藤 昭 水野 将史 後藤 強 寺田 和憲

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第17回全国大会(2003)

巻号頁・発行日

pp.208, 2003 (Released:2004-02-03)

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知的な行動主体(エージェント)が社会で行動するためには、相手の行動を予測して、それに対して適切な行動をとる必要がある。このような、「相手を読む」ことの研究は、(囲碁のような)零和ゲーム、囚人のジレンマゲームのような、対称型非零和ゲームではあるものの、一般の零和ゲームではほとんどない。ここでは、「相手を読む」ことが本質的な標準ゲームを提案する。また、強化学習、進化プログラミングを用いて行動戦略の獲得を調べ、「良い」戦略の条件を検討する。また、対戦者両者が共に相手の行動を読んで自己の戦略を修正しようとするとき、どのような現象が観測されるのかを報告する。

著者

小島 諒介 佐藤 泰介

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.3, pp.301-310, 2014-05-01 (Released:2014-04-04)

参考文献数

23

---

In this paper we propose a new plan recognition method from observations of incomplete action sequences by regarding them as prefixes in a probabilistic context-free grammar (PCFG). In previous work that uses a PCFG for plan recognition, the PCFG receives a sentence, i.e. an observation of complete action sequences to recognize the plan behind it. However, when we deal with real plan recognition problems such as the Web access log analysis, we often cannot have complete sequences of actions and the traditional PCFG approach is not applicable. To overcome this difficulty, we extend the probability computation of PCFGs to prefix probability computation though it requires an infinite sum of probabilities. We applied the proposed method to infer the intended goals of Web site visitors from the online and partial observations of their actions. Also we compared the performance of plan recognition from observations of initial sequences of visitors' actions with that from full observations.

著者

後藤 友和 グエン トアンドゥク ボレガラ ダヌシカ 石塚 満

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.26, no.6, pp.649-656, 2011 (Released:2011-09-09)

参考文献数

13

---

Relational similarity can be defined as the similarity between two semantic relations R and R' that exist respectively in two word pairs (A,B) and (C,D). Relational search, a novel search paradigm that is based on the relational similarity between word pairs, attempts to find a word D for the slot ? in the query {(A,B), (C,?)} such that the relational similarity between the two word pairs (A, B) and (C, D) is a maximum. However, one problem frequently encountered by a Web-based relational search engine is that the inherent noise in Web text leads to incorrect measurement of relational similarity. To overcome this problem, we propose a method for verifying a relational search result that exploits the symmetric properties in proportional analogies. To verify a candidate result D for a query {(A, B), (C, ?)}, we replace the original question mark by D to create a new query {(A,B),(?,D)} and verify that we can retrieve C as a candidate for the new query. The score of C in the new query can be seen as a complementary score of D because it reflects the reliability of D in the original query. Moreover, transformations of words in proportional analogies lead to relational symmetries that can be utilized to accurately measure the relational similarity between two semantic relations. For example, if the two word pairs (A,B) and (C, D) show a high degree of relational similarity then the two word pairs (B,A) and (D,C) also have a high degree of relational similarity. We apply this idea in relational search by using symmetric queries such as {(B, A), (D, ?)} to create six queries for verifying a candidate answer D to improve the reliability of the verification process. Our experimental results on the Scholastic Aptitude Test (SAT) analogy benchmark show that the proposed method improves the accuracy of a relational search engine by a wide margin.

著者

吉田 稔 中川 裕志 寺田 昭

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.122-132, 2010 (Released:2010-01-06)

参考文献数

18

被引用文献数

1

---

This paper proposes a method for implementing real-time synonym search systems. Our final aim is to provide users with an interface with which they can query the system for any length strings and the system returns a list of synonyms of the input string. We propose an efficient algorithm for this operation. The strategy involves indexing documents by suffix arrays and finding adjacent strings of the query by dynamically retrieving its contexts (i.e., strings around the query). The extracted contexts are in turn sent to the suffix arrays to retrieve the strings around the contexts, which are likely to contain the synonyms of the query string.

著者

川畑 光希 松原 靖子 本田 崇人 今井 優作 田嶋 優樹 櫻井 保志

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第34回 (2020) (ISSN:27587347)

巻号頁・発行日

pp.4K2GS303, 2020 (Released:2020-06-19)

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顧客生涯価値(LTV)は顧客評価における重要な指標であり,LTVを正確に予測することで顧客に対しより適切なマーケティングを行うことが可能になる.本稿では,購買ログデータを対象とし,顧客ID,商品ID,時間の組みで表されるイベントシーケンスから潜在的な購買特性を発見し,それらに基づくLTV予測を行うための手法を提案する.実データを用いた実験では,提案手法が与えられた購買ログの中から有用な購買特性を発見し,従来手法よりも高い精度でLTV予測を行うことを確認した.

著者

髙岡 昂太 坂本 次郎 橋本 笑穂 北條 大樹 古川 結唯 菊池 愛美 佐藤 瑛洋 先光 毅士 山本 直美 鈴木 聡

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第34回 (2020) (ISSN:27587347)

巻号頁・発行日

pp.1D4GS1305, 2020 (Released:2020-06-19)

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日本では推計で毎年500人の子どもが虐待で死亡している。親が嘘をつく場合や、子どもが加害者から脅され話せないなど、正確な情報収集が難しい課題がある。ベテラン職員であっても判断を誤ることがあるため、虐待対応には判断の質の向上が喫緊に求められる。さらに、増加する虐待通告件数に対応する施策も満足に打てていないことが問題である。申請者らは現場職員の判断を支援し、かつ虐待件数増加に対応する施策決定に向けたAI実証実験を2019年7月より始めた。現場と達成目標をすり合わせた上で、一時保護すべきケースの見過ごしを無くすため、予測精度の高い勾配ブースティングを実装した。また、将来的な再発率や重篤度の算出には、現場の説明責任を担保するため、因果推論を行う確率モデリングを採用した。試行の進捗として①現場の業務フローの差異の把握、②データ収集の調整、③パラメーターチューニング、④UI/UXの改修を含むアジャイル開発、⑤ICTが得意または苦手なユーザーへの研修の配慮など、社会課題解決に向けた社会実装で得た知見について発表を行う。

著者

藤原 幸一 藤田 卓仙 山川 俊貴 久保 孝富 日永田 智絵 桐山 瑶子 川島 浩誉 川治 徹真 野田 隼人 田畑 淳

出版者

一般社団法人 人工知能学会

雑誌

人工知能 (ISSN:21882266)

巻号頁・発行日

vol.36, no.6, pp.674-683, 2021-11-01 (Released:2021-11-01)

著者

于 楊 日永田 智絵 堀井 隆斗 長井 隆行

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第34回 (2020)

巻号頁・発行日

pp.4F2OS25a03, 2020 (Released:2020-06-19)

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近年,スマートフォンやタブレットなどデジタル端末の発展により,ユーザーが視聴できる動画は膨大な量に達している.こうした中で,消費者のニーズに対応するパーソナライズされたビデオコンテンツの分類,検索および配信は依然として解決すべき課題である.一般に,人間は情緒的特性に基づいて映画や音楽を選ぶ傾向がある.従って,感情喚起を分析することで,この課題に対して一つの指針が得られる可能性がある.動画によって喚起される感情は,オーディオとビデオの両方のモダリティに関係している.そこで本研究では,マルチモーダル情報の統合によって動画による感情喚起を推定する深層学習モデルを提案する.映画データベースを用いた実験により,マルチモーダル情報を統合したことによる推定性能の変化について検証し,従来手法に比べ推定精度が向上することを示す.また最近話題となっているAutonomous Sensory Meridian Response (ASMR) 動画を解析し,感情喚起と閲覧回数,高・低評価数など視聴者の行動との関係性を検証する.

著者

諏訪 博彦

出版者

一般社団法人 人工知能学会

雑誌

人工知能 (ISSN:21882266)

巻号頁・発行日

vol.39, no.1, pp.19-20, 2024-01-01 (Released:2024-01-01)