• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.599-604
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• 2017

A useful application of smart assistants is to predict and suggest users' daily behaviors the way real assistants do. Conventional methods to predict behavior have mainly used explicit schedule information logged by a user or extracted from e-mail or SNS data. However, gathering explicit information for smart assistants has limitations, and much of a user's routine behavior is not logged in the first place. In this paper, we suggest a novel approach that combines explicit schedule information with patterns of routine behavior. We propose using inference based on a Markov decision process and learning with a reward function based on inverse reinforcement learning. The results of our experiment shows that the proposed method outperforms comparable models on a life-log dataset collected over six weeks.

• Journal of the Korean earth science society
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• v.30 no.7
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• pp.909-927
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• 2009

Inquiry became an essential methodology in science education. Recently, argumentation becomes more important in inquiry, but inquiry-based teaching in school science would not provide enough opportunities for students to have voluntary and active interactions during inquiry activities. Informal science learning can be an alternative for authentic inquiry. Accordingly, this study aims to find interaction patterns in dialogic inquiry of junior high school students in small groups in the natural history gallery. Inquiry elements and interaction patterns are analyzed with 42 dialogues of 13 small groups. As a result, seven interaction patterns are identified. First, five major interaction patterns were drawn as follows; Sharing questions, asking questions and simple response, asking questions and simple explanation, asking questions-simple explanation-(collecting data)-data based explanation, and asking questions-collecting data-data based explanation. Second, pattern 2, 'asking questions and simple response', is subdivided into three categories; passive and/or evasive response, inaccurate response, and repeated patterns of asking questions-simple response. The results of the study provide different patterns of dialogic interactions in a small group inquiry in informal contexts from formal contexts, and provide foundations to understand middle school students' interactive dialogues of inquiry occurred in the natural history gallery.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.134-153
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• 2008

The main purpose of the research is to illustrate the value of the spatial statistical approach to residential differentiation by providing a framework for exploratory spatial data analysis (ESDA) using a local spatial separation measure. ESDA aims, by utilizing a variety of statistical and cartographic visualization techniques, at seeking to detect patterns, to formulate hypotheses, and to assess statistical models for spatial data. The research is driven by a realization that ESDA based on local statistics has a great potential for substantive research. The main results are as follows. First, a local spatial separation measure is correspondingly derived from its global counterpart. Second, a set of significance testing methods based on both total and conditional randomization assumptions is provided for the local measure. Third, two mapping techniques, a 'spatial separation scatterplot map' and a 'spatial separation anomaly map', are devised for ESDA utilizing the local measure and the related significance tests. Fourth, a case study of residential differentiation between the highly educated and the least educated in major Korean metropolitan cities shows that the proposed ESDA techniques are beneficial in identifying bivariate spatial clusters and spatial outliers.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.