ConTo consl;ruet, a £1apanese~-+lh'ench dictiom~ry, we chose English its tim inte.rme(liary l;m/,;u;q,/(', beta, rise JN)anesev-+English and Englishv-d)'rench dictionaries e.xist in electronic forms and because publMw, d aN)anese~l,'rench dicl;ionm'ies provide enough vocabulary in comparison with the resulting dict;iona.ry.In Section 2 we describe a method for exl:ra(:t;-ing equiv,'denei(;s for a given wor(I. ]l;s fmMamentel concepts m:e stated in Secti(m :3. Tim whole. procedure used to construct th(', new dictionary is shown in Section 4 ~tn(l in Se(:t,i(,n l] t:he r('suli;ing dictionary is evaluated.aapml(,se-English, English-J~tpltilese, EuglishFren(:h, French-F, iw;lish , a;q~mmse-l,'renc]l and Freneh-Jal);mese dictionaries are rest)eel:ively denot:ed l)icj _~, Oico._Q, Dice_ ,:e,
The flipped classroom has become famous as an effective educational method that flips the purpose of classroom study and homework. In this paper, we propose a video learning system for flipped classrooms, called Response Collector, which enables students to record their responses to preparation videos. Our system provides response visualization for teachers and students to understand what they have acquired and questioned. We performed a practical user study of our system in a flipped classroom setup. The results show that students preferred to use the proposed method as the inputting method, rather than naive methods. Moreover, sharing responses among students was helpful for resolving individual students' questions, and students were satisfied with the use of our system.
Abstract-There are several estimators of conditional probability from observed frequencies of features. In this paper, we propose using the lower limit of confidence interval on posterior distribution determined by the observed frequencies to ascertain conditional probability. In our experiments, this method outperformed other popular estimators.
In this paper, we propose a way to improve the compression based dissimilarity measure, CDM. We propose to use a modified value of the file size, where the original CDM uses an unmodified file size. Our application is a music score analysis. We have chosen piano pieces from five different composers. We have selected 75 famous pieces (15 pieces for each composer). We computed the distances among all pieces by using the modified CDM. We use the K-nearest neighbor method when we estimate the composer of each piece of music. The modified CDM shows improved accuracy. The difference is statistically significant.
Sometimes, we do not use a maximum likelihood estimator of a probability but it's a smoothed estimator in order to cope with the zero frequency problem. This is often the case when we use the Naive Bayes classifier. Laplace smoothing is a popular choice with the value of Laplace smoothing estimator being the expected value of posterior distribution of the probability where we assume that the prior is uniform distribution. In this paper, we investigate the confidence intervals of the estimator of Laplace smoothing. We show that the likelihood function for this confidence interval is the same as the likelihood of a maximum likelihood estimated value of a probability of Bernoulli trials. Although the confidence interval of the maximum likelihood estimator of the Bernoulli trial probability has been studied well, and although the approximate formulas for the confidence interval are well known, we cannot use the interval of maximum likelihood estimator since the interval contains the value 0, which is not suitable for the Naive Bayes classifier. We are also interested in the accuracy of existing approximation methods since these approximation methods are frequently used but their accuracy is not well discussed. Thus, we obtain the confidence interval by numerically integrating the likelihood function. In this paper, we report the difference between the confidence interval that we computed and the confidence interval by approximate formulas. Finally, we include a URL, where all of the intervals that we computed are available.
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