This paper proposes a method to make and analyze “contact-keywords history” from GPS logging data. We develop the method to infer gourmet preferences. The history consists of time-series attributes related to spots (shops, restaurants, etc.) in GPS logging data. These days, many contents-search or recommendation services for large volumes of contents in the Internet are available. Typically, the systems on these services need to have quite precise user requests before they can offer desirable contents. It is a hard work for a user to give enough information for the systems. Since most portable devices including mobile phones have GPS function, we can easily get GPS data and utilize them for user preferences. We evaluate the proposed method through practical GPS data.
This paper proposes a method for authorship identification based on phrase patterns that occur in the Japanese language, using literary work, student’s work, journals to carry out actual proof analysis. The results showed that a writer’s writing characteristics could be told clearly in phrase patterns. Using Random Forests, the correct ratio for identifying the authors from two arbitrary authors of literary works as well as student compositions was 99% and 92% for journals. In order to show the effectiveness of the proposed method, a comparison between phrase patterns and trigram of POS was conducted. There was no obvious difference found in the rate of correct identification of writer between phrase patterns C and POS trigram. However, when the data of the phrase patterns C were combined with morphological data, it can obtain a higher rate of correct identification of the writer than having combined the data of POS trigram with morphological data. Based on this, we carried out an analysis on the authorship doubt surrounding Kawabata Yasunari’s works and the works of Mishima Yukio, HMakoto and Sawana Hisao. Phrase patterns analysis suggested there was no doubt surrounding the authorship in Kawabata’s work.
Consider the situation when a set of new items are administered as the part of several forms including anchor items. In this case, in order to add the new items to the existing item bank, we could either 1) estimate the item parameters of the items in each form and equate them using the information contained in the anchor items (separate calibration), or 2) combine the new item response data to the old data set and calibrate whole the items again using the multiple group IRT (concurrent calibration). However, as the number of groups becomes large, the existing multiple group IRT calibration program fails to converge due to the lack of available memory. In this study we examined the proper method to merge groups in order to avoid the above problem. Simulation studies showed that the separate calibration estimates were closest to the true value, and the concurrent calibration with reduced groups was similar to the separate calibration if the mean values of latent ability were similar among the merged groups.
As suggested in the case of “the 100 charismas of tourism”, local communities can be improved if at least one ultra-altruistic person engages in cooperative behavior for the benefit of the community. This paper investigated determinants of such pro-social behavior toward a local community by “regional charismas.” For the purpose, a questionnaire survey was conducted based on determinant factors of altruistic behavior proposed by previous research. The respondents were 1) “the 100 charisma of tourism” (n = 95), 2) “residents living in the same region as the charismas” (n= 400), and 3) residents living in other regions (n = 500). By comparing different groups, individual and regional factors of pro-social behavior by “charismas” were examined. The results suggested that Schwartz’s “norm activating factor” and “perceived benefits” regarding pro-social behavior directly related to individual factors of charismas’ behavior, and “sympathy” among residents directly related to regional factors.
For count data of rare events, a Poisson distribution is most frequently used to model the phenomenon under consideration. However, it is sometimes observed in various applications that the zero count is too many or too few than the count expected under the usual Poisson model. In such cases so-called zero-modified Poisson (ZMP) distributions would be fitted to the observed data. This paper discusses the performance of estimation procedures of the parameter involved in the ZMP distribution. First we attempt to clarify the meaning of the zero-modification parameter in the zero-deflated Poisson (ZDP) distribution in comparison to the zero-inflated Poisson (ZIP) distribution. After reviewing the maximum likelihood estimation procedures for the parameters of ZMP models, a simulation study is conducted to assess the performance of confidence intervals of the zero-modification parameter from the viewpoint of coverage probability. It is found that when sample size is small and the Poisson parameter is small, the performance of interval estimation is not so well. However, for the case of moderate and large sample sizes the coverage probabilities of the confidence intervals are almost equal to the nominal confidence coefficient.