著者

藤巻 遼平 広瀬 俊亮 中田 貴之

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.4, pp.540-548, 2010

被引用文献数

1 1

---

Although Subsequence Time Series (STS) clustering has been one of the most popular techniques to extract typical subsequence patterns from time-series data, previous studies have gave surprising reports that cluster centers obtained using STS clustering closely resemble ``sine waves'' with little relation to input time-series data. This means that STS clustering cannot be used for its original purpose, extraction of typical subsequences. Despite this serious fact, its mathematical structure has seldom been studied. The main contribution of this paper is that we give a theoretical analysis of STS clustering from a frequency-analysis viewpoint and identify that sine waves are generated due to the superposition of time series subsequences, which have the same spectra but different phases. Another contribution is that we propose a clustering algorithm, which uses a phase alignment preprocessing, to avoid sine-wave patterns.

著者

長谷川 貴之 鍜治 伸裕 吉永 直樹 豊田 正史

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.90-99, 2014

被引用文献数

1

---

While there have been many attempts to estimate the emotion of a speaker from her/his utterance, few studies have explored how her/his utterance affects the emotion of the listener. This has motivated us to investigate two novel tasks: predicting the emotion of the listener and generating a response that evokes a specific emotion in the listeners mind. We target Japanese Twitter posts as a source of dialogue data and automatically build training data for learning the predictors and generators. The feasibility of our approaches is assessed by using 1099 utterance-response pairs that are built by five human workers.

著者

稲葉 通将 神園 彩香 高橋 健一

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.29, no.1, pp.21-31, 2014

被引用文献数

9

---

Recently, computerized dialogue systems are studied actively. Non-task-oriented dialogue systems that handle domain-free dialogues like chats are expected be applied in various fields, but many challenges still exist in developing them. This paper addresses the problem of utterance generation for non-task-oriented dialogue systems. We search twitter data by topic words and acquire sentences. The sentences are filtered by rules and scored on the basis of training data. We acquire the sentences which have a high score as utterances. The results of an experiment demonstrate that the proposed method can generate appropriate utterances with a high degree of accuracy.

著者

銅谷 賢治

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.90, 2002 (Released:2003-07-10)

著者

中嶋 宏 森島 泰則 山田 亮太 Scott Brave Heidy Maldonado Clifford Nass 川路 茂保

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.184-196, 2004-11-01

被引用文献数

1 15

---

In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

著者

後藤 真孝 緒方 淳 江渡 浩一郎

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.25, no.1, pp.104-113, 2010

被引用文献数

2 1

---

In this paper, we describe a public web service, <EM>``PodCastle''</EM>, that provides full-text searching of speech data (Japanese podcasts) on the basis of automatic speech recognition technologies. This is an instance of our research approach, <EM>``Speech Recognition Research 2.0''</EM>, which is aimed at providing users with a web service based on Web 2.0 so that they can experience state-of-the-art speech recognition performance, and at promoting speech recognition technologies in cooperation with anonymous users. PodCastle enables users to find podcasts that include a search term, read full texts of their recognition results, and easily correct recognition errors by simply selecting from a list of candidates. Even if a state-of-the-art speech recognizer is used to recognize podcasts on the web, a number of errors will naturally occur. PodCastle therefore encourages users to cooperate by correcting these errors so that those podcasts can be searched more reliably. Furthermore, using the resulting corrections to train the speech recognizer, it implements a mechanism whereby the speech recognition performance is gradually improved. Our experience with this web service showed that user contributions we collected actually improved the performance of PodCastle.

著者

西山 莉紗 竹内 広宜 渡辺 日出雄 那須川 哲哉

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.541-548, 2009

被引用文献数

1 2

---

It is important for R&D managers, consultants, and other people seeking broad knowledge in technology fields to survey technical literature such as research papers, white papers, and technology news articles. One of the important kinds of information for those people regards the effectiveness of new technologies in their own businesses. General search engines are good at selecting documents revealing the details of a specific technology or a technology field, but it is hard to obtain useful information about how a technology will apply to individual business cases from such search results. There is a need for a technology survey assistance tool that helps users find technologies with suitable capabilities. In this paper, two technical tasks were tackled to develop the prototype of this assistance tool: Extraction of advantage phrases and scoring for the advantage phrases to find novel applications in the target technology field. We describe a new method to identify advantage phrases in technical documents and our scoring function that gives higher scores to novel applications of the technology. The results of evaluations showed our phrase identification method with only a few phrasal patterns performs almost as well as human annotators, and the proposed scoring conforms better to the decisions made by professionals than random sort.

著者

池ヶ谷 有希 野口 靖浩 小暮 悟 伊藤 敏彦 小西 達裕 近藤 真 麻生 英樹 高木 朗 伊東 幸宏

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.291-310, 2007-11-01

被引用文献数

3

---

This paper describes how to perform syntactic parsing and semantic analysis in a dialog system. The paper especially deals with how to disambiguate potentially ambiguous sentences using the contextual information. Although syntactic parsing and semantic analysis are often studied independently of each other, correct parsing of a sentence often requires the semantic information on the input and/or the contextual information prior to the input. Accordingly, we merge syntactic parsing with semantic analysis, which enables syntactic parsing taking advantage of the semantic content of an input and its context. One of the biggest problems of semantic analysis is how to interpret dependency structures. We employ a framework for semantic representations that circumvents the problem. Within the framework, the meaning of any predicate is converted into a semantic representation which only permits a single type of predicate: an identifying predicate "aru". The semantic representations are expressed as sets of "attribute-value" pairs, and those semantic representations are stored in the context information. Our system disambiguates syntactic/semantic ambiguities of inputs referring to the attribute-value pairs in the context information. We have experimentally confirmed the effectiveness of our approach; specifically, the experiment confirmed high accuracy of parsing and correctness of generated semantic representations.

著者

田中 貴紘 松村 京平 藤田 欣也

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.6, pp.683-693, 2010

被引用文献数

2 2

---

In this paper, we proposed the user uninterruptibility estimation method based on focused Application-Switching (AS) during PC work for establishing information display timing control scheme with less intelligent activity disturbance for users. At first, we collected and analyzed the PC operation records and the subjective uninterruptibility of users. From the analysis, we selected features in AS timing that affect user uninterruptibility. Then, we provided the estimation method based on co-occurring features that are observed in AS timing, and confirmed the availability of our method.

著者

松井 藤五郎 犬塚 信博 世木 博久

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.110, 2001 (Released:2003-07-10)

著者

松尾 豊 友部 博教 橋田 浩一 中島 秀之 石塚 満

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.46-56, 2005-11-01

被引用文献数

31 28

---

Social relation plays an important role in a real community.

著者

小西 克巳 遠山 敏章 渡辺 明日香

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.25-36, 2010

---

This paper proposes a fashion-related image gathering algorithm and a retrieval system. Since it is difficult to define the fashion-related image exactly in mathematical sense, computers can not recognize whether given images are fashion-related even if they use computer vision techniques. It is also difficult to gather and search only fashion-related images on the Internet automatically for the same reason. In order to overcome these difficulties, we focus on human computing power, which helps computers to find fashion-related images from tons of images on the Internet. This paper provides an algorithm to gather high quality fashion-related images and propses a fashion-related image retrieval system, both of which utilize the information and meta data obtained in a fashion-related image sharing site. Evaluation experiments show that the proposed algorithm can gather fashion-related images efficiently and that the proposed retrival system can find desired images more effectively than Google Image Search.

著者

尾崎 知伸 大川 剛直

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.23, no.6, pp.514-525, 2008

被引用文献数

1

---

Recently, pattern mining in structured domain, such as sequences, trees and graphs, is becoming increasingly abundant and several algorithms for especially frequent pattern mining have been developed. On the other hand, the research area of correlation mining in transaction databases, that extracts the underlying dependency among objects, attracts a big attention and extensive studies have been reported. Although we can easily expect to get a more powerful tool for structured data by introducing correlation mining, the most of current research on correlation mining are designed for transaction databases and little attention is paid to mining correlations from structured data. Motivated by these backgrounds, in this paper, we bring the concept of hyperclique pattern in transaction databases into the graph mining and consider the discovery of sets of highly-correlated subgraphs in graph-structured databases. To achieve this objective, a novel algorithm named HSG is proposed. By considering the generality ordering on sets of subgraphs, HSG employs the depth-first/breadth-first search strategy with powerful pruning techniques based on both of the anti-monotone property of support value and the upper bound of h-confidence measure. Experiments with artificial and real world datasets were conducted to assess the effectiveness of the proposed algorithm. The results of experiments show that HSG succeeds in discovering sets of highly-correlated subgraphs within reasonable computation time.

著者

石原 一志 駒谷 和範 尾形 哲也 奥乃 博

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.229-236, 2005-11-01

被引用文献数

5 2

---

Environmental sounds are very helpful in understanding environmental situations and in telling the approach of danger, and sound-imitation words (sound-related onomatopoeia) are important expressions to inform such sounds in human communication, especially in Japanese language. In this paper, we design a method to recognize sound-imitation words (SIWs) for environmental sounds. Critical issues in recognizing SIW are how to divide an environmental sound into recognition units and how to resolve representation ambiguity of the sounds. To solve these problems, we designed three-stage procedure that transforms environmental sounds into sound-imitation words, and <I>phoneme group expressions</I> that can represent ambiguous sounds. The three-stage procedure is as follows: (1) a whole waveform is divided into some chunks, (2) the chunks are transformed into sound-imitation syllables by phoneme recognition, (3) a sound-imitation word is constructed from sound-imitation syllables according to the requirements of the Japanese language. Ambiguity problem is that an environmental sound is often recognized differently by different listeners even under the same situation. Phoneme group expressions are new phonemes for environmental sounds, and they can express multiple sound-imitation words by one word. We designed two sets of phoneme groups: ``a set of basic phoneme group'' and ``a set of articulation-based phoneme group'' to absorb the ambiguity. Based on subjective experiments, the set of basic phoneme groups proved more appropriate to represent environmental sounds than the articulation-based one or a set of normal Japaneses phonemes.

著者

Tetsuji Kuboyama Kouichi Hirata Hisashi Kashima Kiyoko F.Aoki-Kinoshita Hiroshi Yasuda

出版者

The Japanese Society for Artificial Intelligence

雑誌

Transactions of the Japanese Society for Artificial Intelligence (ISSN:13460714)

巻号頁・発行日

vol.22, no.2, pp.140-147, 2007 (Released:2007-01-25)

参考文献数

17

被引用文献数

5 11 27

---

Learning from tree-structured data has received increasing interest with the rapid growth of tree-encodable data in the World Wide Web, in biology, and in other areas. Our kernel function measures the similarity between two trees by counting the number of shared sub-patterns called tree q-grams, and runs, in effect, in linear time with respect to the number of tree nodes. We apply our kernel function with a support vector machine (SVM) to classify biological data, the glycans of several blood components. The experimental results show that our kernel function performs as well as one exclusively tailored to glycan properties.

著者

Shin-ichi Minato Kimihito Ito

出版者

The Japanese Society for Artificial Intelligence

雑誌

Transactions of the Japanese Society for Artificial Intelligence (ISSN:13460714)

巻号頁・発行日

vol.22, no.2, pp.156-164, 2007 (Released:2007-01-25)

参考文献数

17

被引用文献数

2 4

---

In this paper, we present a method of finding symmetric items in a combinatorial item set database. The techniques for finding symmetric variables in Boolean functions have been studied for long time in the area of VLSI logic design, and the BDD (Binary Decision Diagram) -based methods are presented to solve such a problem. Recently, we have developed an efficient method for handling databases using ZBDDs (Zero-suppressed BDDs), a particular type of BDDs. In our ZBDD-based data structure, the symmetric item sets can be found efficiently as well as for Boolean functions. We implemented the program of symmetric item set mining, and applied it to actual biological data on the amino acid sequences of influenza viruses. We found a number of symmetric items from the database, some of which indicate interesting relationships in the amino acid mutation patterns. The result shows that our method is helpful for extracting hidden interesting information in real-life databases.

著者

Shin-ichi Minato Hiroki Arimura

出版者

The Japanese Society for Artificial Intelligence

雑誌

Transactions of the Japanese Society for Artificial Intelligence (ISSN:13460714)

巻号頁・発行日

vol.22, no.2, pp.165-172, 2007 (Released:2007-01-25)

参考文献数

11

被引用文献数

1 5 9

---

Frequent item set mining is one of the fundamental techniques for knowledge discovery and data mining. In the last decade, a number of efficient algorithms for frequent item set mining have been presented, but most of them focused on just enumerating the item set patterns which satisfy the given conditions, and it was a different matter how to store and index the result of patterns for efficient data analysis. Recently, we proposed a fast algorithm of extracting all frequent item set patterns from transaction databases and simultaneously indexing the result of huge patterns using Zero-suppressed BDDs (ZBDDs). That method, ZBDD-growth, is not only enumerating/listing the patterns efficiently, but also indexing the output data compactly on the memory to be analyzed with various algebraic operations. In this paper, we present a variation of ZBDD-growth algorithm to generate frequent closed item sets. This is a quite simple modification of ZBDD-growth, and additional computation cost is relatively small compared with the original algorithm for generating all patterns. Our method can conveniently be utilized in the environment of ZBDD-based pattern indexing.

著者

Nozomi Kobayashi Kentaro Inui Yuji Matsumoto

出版者

The Japanese Society for Artificial Intelligence

雑誌

Transactions of the Japanese Society for Artificial Intelligence (ISSN:13460714)

巻号頁・発行日

vol.22, no.2, pp.227-238, 2007 (Released:2007-01-25)

参考文献数

19

被引用文献数

3 17 38

---

The task of opinion extraction and structurization is the key component of opinion mining, which allow Web users to retrieve and summarize people's opinions scattered over the Internet. Our aim is to develop a method for extracting opinions that represent evaluation of concumer products in a structured form. To achieve the goal, we need to consider some issues that are relevant to the extraction task: How the task of opinion extraction and structurization should be designed, and how to extract the opinions which we defined. We define an opinion unit consisting of a quadruple, that is, the opinion holder, the subject being evaluated, the part or the attribute in which it is evaluated, and the evaluation that expresses positive or negative assessment. In this task, we focus on two subtasks (a) extracting subject/aspect-evaluation relations, and (b) extracting subject/aspect-aspect relations, we approach each extraction task using a machine learning-based method. In this paper, we discuss how customer reviews in web documents can be best structured. We also report on the results of our experiments and discuss future directions.