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

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

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

李 銘義 公文 誠 足立 紀彦

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.16, no.1, pp.94-101, 2001 (Released:2002-02-28)

参考文献数

15

被引用文献数

1

---

The objective of this article is to provide the basic formulation of the affordance of environment. Study on affordance has been mostly focusing on the significance of perception, behavior and workspace, while leaving the problem of application unaddressed. Using the proposed method, it is possible to apply reinforcement learning algorithm on the robot within a certain environment, making the abstraction of affordance of the environment with interaction between the reinforcement learning agent and the environment available. Conclusion is made in the latter part of the paper that the percipient(robot) should simplify the number of perception in order to get enough valid equivalence relationship which abstracts affordance from environment with in the limit of incomplete perception; and the structure of the environment(workspace) would restrict the robot’s behavior. The prospect of this study, therefore, focuses on the interactive processes between the robot and the workspace from which the robot could set up it’s perception for particular tasks, and on how the robot could continuously manage it’s perception.

著者

河原 吉伸 矢入 健久 町田 和雄

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.23, no.2, pp.76-85, 2008 (Released:2008-01-29)

参考文献数

20

---

In this paper, we propose a class of algorithms for detecting the change-points in time-series data based on subspace identification, which is originaly a geometric approach for estimating linear state-space models generating time-series data. Our algorithms are derived from the principle that the subspace spanned by the columns of an observability matrix and the one spanned by the subsequences of time-series data are approximately equivalent. In this paper, we derive a batch-type algorithm applicable to ordinary time-series data, i.e., consisting of only output series, and then introduce the online version of the algorithm and the extension to be available with input-output time-series data. We illustrate the superior performance of our algorithms with comparative experiments using artificial and real datasets.

著者

長島 一真 森田 純哉 竹内 勇剛

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.36, no.5, pp.AG21-E_1-13, 2021-09-01 (Released:2021-09-01)

参考文献数

43

---

To date, many studies concerned with intrinsic motivation in humans and artificial agents based on a reinforcement learning framework have been conducted. However, these studies have rarely explained the correspondence between intrinsic motivation and other essential cognitive functions. This study aims to build a method to express curiosity in new environments via the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture. To validate the effectiveness of this proposal, we implement several models of varying complexity using the method, and we confirm that the model’s behavior is consistent with human learning. This method focuses on the“ production compilation” and ”utility” modules, which are generic functions of ACT-R. It regards pattern matching with the environment as a source of intellectual curiosity. We prepared three cognitive models of path planning representing different levels of thinking. We made them learn in multiple-breadth maze environments while manipulating the strength of intellectual curiosity, which is a type of intrinsic motivation. The results showed that intellectual curiosity in learning an environment negatively affected the model with a shallow level of thinking but was influential on the model with a deliberative level of thinking. We consider the results to be consistent with the psychological theories of intrinsic motivation. Furthermore, we implemented the model using a conventional reinforcement learning agent and compared it with the proposed method.

著者

清水 祐一郎 土斐崎 龍一 鍵谷 龍樹 坂本 真樹

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.30, no.1, pp.319-330, 2015-01-06 (Released:2015-01-06)

参考文献数

32

被引用文献数

1 2

---

The present study proposes a method which generates Japanese onomatopoeia corresponding to impressions inputted by users. Japanese onomatopoeia is frequently used in comics and advertisements. Effective onomatopoeia in those fields are directly associated with sensuous experiences of readers or consumers, but it is very difficult to create such expressions. Therefore, the system which generates effective novel onomatopoeia corresponding to the impression specified by users has been expected to be as a technology which supports creators. Our system uses 43 SD scales as those expressing our intuitive impressions. These scales consist of scales expressing impressions of a haptic senses, visual senses and affective senses. Users of the system can choose the kinds of SD scales to be used to create onomatopoeia among from 1 to 43 SD scales. The system uses the genetic algorithm (GA) to create onomatopoeia corresponding to inputted impressions. We consider onomatopoeic expressions as a individuals of GA, which are expressed by an array of numerical values. Namely, each numerical value of an individual denotes each phonological symbol in Japanese. By comparing impressions inputted by user with those of each generated onomatopoeia, the system proposes onomatopoeia corresponding to impressions of users. The system evaluation showed that impressions of onomatopoeic expressions generated by our system were similar to the impressions inputted by users.

著者

小林 由弥 鈴木 雅大 松尾 豊

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.37, no.2, pp.I-L75_1-17, 2022-03-01 (Released:2022-03-01)

参考文献数

63

---

Ability to understand surrounding environment based on its components, namely objects, is one of the most important cognitive ability for intelligent agents. Human beings are able to decompose sensory input, i.e. visual stimulation, into some components based on its meaning or relationships between entities, and are able to recognize those components as “object ”. It is often said that this kind of compositional recognition ability is essential for resolving so called Binding Problem, and thus important for many tasks such as planning, decision making and reasoning. Recently, researches about obtaining object level representation in unsupervised manner using deep generative models have been gaining much attention, and they are called ”Scene Interpretation models”. Scene Interpretation models are able to decompose input scenes into symbolic entities such as objects, and represent them in a compositional way. The objective of our research is to point out the weakness of existing scene interpretation methods and propose some methods to improve them. Scene Interpretation models are trained in fully-unsupervised manner in contrast to latest methods in computer vision which are based on massive labeled data. Due to this problem setting, scene interpretation models lack inductive biases to recognize objects. Therefore, the application of these models are restricted to relatively simple toy datasets. It is widely known that introducing inductive biases to machine learning models is sometimes very useful like convolutional neural networks, but how to introduce them via training depends on the models and is not always obvious. In this research, we propose to incorporate self-supervised learning to scene interpretation models for introducing additional inductive bias to the models, and we also propose a model architecture using Transformer which is considered to be suitable for scene interpretation when combined with self-supervised learning. We show proposed methods outperforms previous methods, and is able to adopt to Multi-MNIST dataset which previous methods could not deal with well.

著者

渕本 壱真 湊 真一 植野 真臣

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.37, no.5, pp.A-M23_1-11, 2022-09-01 (Released:2022-09-01)

参考文献数

34

---

Recently, the necessity of“ parallel test forms ”for which each form comprises a different set of items, but which still has equivalent measurement accuracy has been emerging. An important issue for automated test assembly is to assemble as many parallel test forms as possible. Although many automated test assembly methods exist, the maximum clique using the integer programming method is known to assemble the greatest number of tests with the highest measurement accuracy. However, the method requires one month or more to assemble 450,000 tests due to the high time complexity of integer programming. This study proposes a new automated test assembly using Zerosuppressed Binary Decision Diagrams (ZDD). A ZDD is a graphical representation for a set of item combinations. This is derived by reducing a binary decision tree. In the proposed method, each node in the binary decision tree corresponds to an element of an item bank and has two edges if the item (node) is contained in a uniform test. Furthermore, all equivalent nodes (having the same measurement accuracy and the same test length) are shared. Finally, this study provides simulation and actual data experiments to demonstrate the effectiveness of the proposed method. The proposed method can assemble 450,000 tests within 24 hours.

著者

水本 智也 小町 守 永田 昌明 松本 裕治

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.28, no.5, pp.420-432, 2013-09-01 (Released:2013-07-10)

参考文献数

16

被引用文献数

3 3

---

Recently, natural language processing research has begun to pay attention to second language learning. However, it is not easy to acquire a large-scale learners' corpus, which is important for a research for second language learning by natural language processing. We present an attempt to extract a large-scale Japanese learners' corpus from the revision log of a language learning social network service.This corpus is easy to obtain in large-scale, covers a wide variety of topics and styles, and can be a great source of knowledge for both language learners and instructors. We also demonstrate that the extracted learners' corpus of Japanese as a second language can be used as training data for learners' error correction using a statistical machine translation approach.We evaluate different granularities of tokenization to alleviate the problem of word segmentation errors caused by erroneous input from language learners.We propose a character-based SMT approach to alleviate the problem of erroneous input from language learners.Experimental results show that the character-based model outperforms the word-based model when corpus size is small and test data is written by the learners whose L1 is English.

著者

西山 莉紗 竹内 広宜 渡辺 日出雄 那須川 哲哉

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.541-548, 2009 (Released:2009-10-20)

参考文献数

19

被引用文献数

3 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

西村 良太 森 雷太 太田 健吾 北岡 教英

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.37, no.3, pp.IDS-F_1-13, 2022-05-01 (Released:2022-05-01)

参考文献数

30

---

In this study, we propose a method for generating response utterances which take into account contexts and topics of the dialog by complementing omitted words such as subjects in the input utterances of dialog systems. In order to complement omitted words in the input utterances, an automatic anaphora resolution based on the centering theory is performed. To achieve highly accurate anaphora resolution, we also performed spoken-to-written style conversion based on sequence-to-sequence model using LSTM as a preprocessing. The results of evaluation experiments using NUCC, the Nagoya University Conversation Corpus showed that our proposed complementation method works robustly against errors in spoken-to-written style conversion.

著者

後藤 みの理 加納 政芳 加藤 昇平 國立 勉 伊藤 英則

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.21, no.1, pp.55-62, 2006 (Released:2006-01-06)

参考文献数

26

被引用文献数

7 11

---

We think that psychological interaction is necessary for smooth communication between robots and people. One way to psychologically interact with others is through facial expressions. Facial expressions are very important for communication because they show true emotions and feelings. The ``Ifbot'' robot communicates with people by considering its own ``emotions''. Ifbot has many facial expressions to communicate enjoyment. We developed a method for generating facial expressions based on human subjective judgements mapping Ifbot's facial expressions to its emotions. We first created Ifbot's emotional space to map its facial expressions. We applied a five-layer auto-associative neural network to the space. We then subjectively evaluated the emotional space and created emotional regions based on the results. We generated emotive facial expressions using the emotional regions.

著者

小林 優佳 久島 務嗣 吉田 尚水 藤村 浩司 岩田 憲治

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.37, no.3, pp.IDS-D_1-14, 2022-05-01 (Released:2022-05-01)

参考文献数

63

---

This paper proposes a new method for slot filling of unknown slot values (i.e., those are not included in the training data) in spoken dialogue systems. Slot filling detects slot values from user utterances and handles named entities such as product and restaurant names. In the real world, there is a steady stream of new named entities and it would be infeasible to add all of them as training data. Accordingly, it is inevitable that users will input utterances with unknown slot values and spoken dialogue systems must correctly estimate them. We provide a value detector that detects keywords representing slot values ignoring slots and a slot estimator that estimates slots for detected keywords. Context information can be an important clue for estimating slot values because the values in a given slot tend to appear in similar contexts. The value detector is trained with positive samples, which have keywords corresponding to slot values replaced with random words, thereby enabling the use of context information. However, any approach that can detect unknown slot values may produce false alarms because the features of unknown slot values are unseen and it is difficult to distinguish keywords of unknown slot values from non-keywords, which do not correspond to slot values. Therefore, we introduce a negative sample method that replaces keywords with nonkeywords randomly, which allows the slot estimator to learn to reject non-keywords. Experimental results show that the proposed method achieves an 6,15 and 78% relative improvement in F1 score compared with an existing model on three datasets, respectively.

著者

謝 凡 秋山 英三

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.36, no.5, pp.AG21-A_1-8, 2021-09-01 (Released:2021-09-01)

参考文献数

22

---

To enhance the stability of the financial markets, price limits have been implemented in numerous financial markets. The effects to markets’ stability and traders’ profitability of price limits have been discussed by previous research. But it has not been discussed when there is difference between traders on speed of information acquisition. The asymmetry of information acquisition between traders can be observed in many situations, e.g., overseas investors and domestic investors, insiders and outsiders. Because methods, languages, etc. they use to get information are different, they obtain information about the fundamental values of financial commodities with different speeds. We used a double-auction artificial market to simulate when difference on speed of information acquisition exists, how price limits effect the stability of the financial market, and the profitability of traders who has different speeds to obtain the information about fundamental value. We found if there is difference of speed for getting information between traders, price limits do not always enhance the stability of market. When the band of price limits is loose, the volatility of market price will rise if the ratio of traders with fast speed of information acquisition is relatively large. And when the band of price limits is loose, some traders who has slower speed of information acquisition may be hurt by price limits. Our work shows it is necessary to consider the difference on speed of information acquisition when designing some market institutions like price limits.

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

伊藤 惇貴 加納 政芳 中村 剛士 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.364-371, 2015-01-06 (Released:2015-01-06)

参考文献数

18

被引用文献数

4 2

---

Onomatopoeias refer to words that represent the sound, appearance, or voice of things, which makes it possible to create expressions that bring a scene to life in a subtle fashion. Using onomatopoeias therefore makes process of robot motion generation more easily and intuitively. In previous research, objective quantified values of onomatopoeias have been used as indices of robot motion. In Japanese language, however, onomatopoeias also include mimetic and emotive words. Impression of these words arises from the experience of each people, therefore, its impression might differ among people. In this paper, we propose a method for adjusting the objective quantified values (sound symbolism attributes) of onomatopoeias. Using our method, users of robots are able to create its motions representing the user's image better.