著者

佐久間 淳 安藤 晋 小林 重信

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.3, pp.163-175, 2008 (Released:2008-02-26)

参考文献数

17

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In the process of mixture model estimation using Expectation-Maximization (EM) methods, mixture densities are required to be measured at every step to obtain posterior probabilities. When the number of data n in a dataset or the number of mixtures m is large, the time complexity required for the evaluation of posterior probabilities is O(mn).

著者

加藤 恒昭 松下 光範

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.22, no.5, pp.553-562, 2007 (Released:2007-07-17)

参考文献数

20

被引用文献数

1 2

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Information compilation is a novel technology that allows it to compile various information intelligently, and to make it easy to understand and to access. In this paper, as an instance of the possibilities of information compilation, we show a framework that extracts and visualizes given time-series information and its changes, and provides users with a multi-modal summarization and also an interactive interface for accessing that information. It can meet information requests, in which users need to comprehend some trend and movement, and access a series of documents containing specific time-series information related. We emphasis the importance of changes of data during some time period rather than data points, as the unit of information extracted and represented. Based on this idea, we propose a visualization method in which qualitative and quantitative characteristics of changes of a given time-series information are plotted with textually represented comments, and a widely applicable information extraction method that regards the changes of time-series information as information primitives and extracts those for the visualization.

著者

片上 大輔 大久保 亮介 新田 克己

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.6, pp.459-472, 2006 (Released:2006-08-23)

参考文献数

13

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The purpose of this research is to predict the subjects which will become the fashion in an electronic bulletin board in the near future. We proposed the technique which analyzes propagation of the subject based on link information. To extract the pattern of propagation, we proposed several criteria to measure the fashion degree of the subject based on link information which appears in contributed articles. We realized prediction method with unknown subject in fashion using the classification by Support Vector Machine. We conducted experiments to verify the validity of this technique with known collected fashion-subjects.

著者

青山 一美 南野 活樹 下村 秀樹

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.22, no.4, pp.375-388, 2007 (Released:2007-04-18)

参考文献数

11

被引用文献数

1 3 2

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An autonomous agent in the real world should learn its own sensor-motor coordination through interactions with the environment; otherwise the behaviors can not be grounded and they can easily be inappropriate in the variety of the environment. The sensor-motor signals are usually complex time sequence, therefore the cognitive action system of the agent has to handle them.In this paper, we propose a computational model of the cognitive action system that consists of a sensor space HMM-SOM, a motor space HMM-SOM and connection mapping between the two HMM-SOMs. A HMM-SOM can be recognized as a set of HMMs that are placed in a SOM space. It can model a set of complex time series signal in a self-organizing manner.We apply this HMM-SOM based cognitive action system on vision-motion and auditory-articulation signals. The experimental results show that this system is basically capable of constructing sensor-motor coordination structure in a self-organizing manner, handling complex time series signals.

著者

尾崎 知伸 渡沼 智己 大川 剛直

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.2, pp.173-182, 2007 (Released:2007-01-25)

参考文献数

43

被引用文献数

1

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Recently, the research area of mining in structured data has been actively studied. However, since most techniques for structured data mining so far specialize in mining from single structured data, it is difficult for these techniques to handle more realistic data which is related to various types of attribute and which consists of plural kinds of structured data. Since such kind of data is expected to be going to rapidly increase, we need to establish a flexible and highly accurate technique that can inclusively treat such kind of data. In this paper, as one of the techniques to deal with such kind of data, we propose data mining algorithms of mining classification rules in multidimensional structured data. First, an algorithm with two pruning capabilities of mining correlated patterns is introduced. Then, top-k multidimensional correlated patterns are discovered by using this algorithm repeatedly in the fashion like a beam search. We also show the algorithms for constructing classifiers based on the discovered patterns. Experiments with real world data were conducted to assess the effectiveness of the proposed algorithms. The results show that the proposed algorithms can construct comprehensible and accurate classifiers within a reasonable running time.

著者

幸島 明男 和泉 憲明 車谷 浩一 中島 秀之

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.19, no.4, pp.322-333, 2004 (Released:2004-05-28)

参考文献数

34

被引用文献数

2

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In the vision of the semantic web, agents are defined as the programs that collect information from diverse sources, process the information, and exchange the results with other programs. In order to extend application areas of the agents from the Internet to the real world, we propose CONSORTS, a multiagent architecture for content managements in ubiquitous computing. In this paper, we, first, describe two important concepts in order to realize the agent-based content managements in ubiquitous computing, ``physically grounding'' and ``cognitive resources managements.'' Second, we describe the outline of the CONSORTS (ver. 1) and its RDF-based spatial information representation. Finally, we show an application of the CONSORTS, context-aware information assist services in a museum.

著者

原田 実 水野 高宏

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.85-93, 2001 (Released:2002-02-28)

参考文献数

15

被引用文献数

3 6

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Up to now, the research on the automation of object-oriented analysis, especially extracting objectoriented design elements from the problem specification written in Japanese, has been continued in the Harada laboratory since 1993. As this first process, we have developed the semantic analysis system SAGE which could be practically useable both in the performance and in the accuracy. Given a dependency tree, where clauses constituting a sentence are related by dependency arcs, SAGE searches the EDR electronic dictionary, retrieves for any two clauses connected by a dependency arc the meaning of the principal word in each clause and the deep case between such two words, and assigns the probability of such meaning-case tuple. Then, SAGE constructs an interpretation tree by allocating such meaning-case tuple and its probability to each arc in the dependency tree. Next, SAGE searches for the allocation having the maximum of the overall evaluation value given by the sum of the probability of the allocated meaning and cases. Finally, SAGE converts the resulting interpretation tree into the set of semantic frames containing the information of each word and relations with other words. In developing the system, we achieved speed-up of the construction of the interpretation tree by reducing the search space with pruning useless meaning-case tuples and by using the branch and bound method. Moreover the accuracy improvement of the analysis was achieved by applying the following four methods: (A)in constructing the interpretation tree, assigning 0 probability to all the combination of word meanings with which there are no “case” information in the concept description dictionary, (B)using the experimental rules to presume the deep cases from the surface cases to each dependency between verb clauses, (C)improving the fitness of the sentences retrieved from corpus by using part of speech, and (D)decreasing the number of meaning candidates by using reading information. As a result, the average interpretation construction time of one sentence with nine clauses or less was 2 seconds on a PC with the Pentium III processor using 320MB memory. The correct answer rate of the meaning was 82.1%, and that of the case was 77.8%.