Implementation of the String Matching Method on AnggahUngguhing Balinese Language Dictionary Although the learning media of the Anggah Ungguhing Balinese language has been done anytime and anywhere through a mobile application, this application has several obstacles. In detail, the contributions of this study are: 1) to develop a dictionary application that can be used in offline mode, so that it can be used anytime and anywhere. 2) to apply the string matching method to word search correction in the translator process so that the user gets the correct word from the type of keyword. 3) to develop a new vocabulary sending feature used for users to take part in managing the Anggah Ungguhing Balinese language. 4) to describe studentsxe2x80x99 learning responses in Anggah Ungguhing Balinese language using mobile application. Positive findingsinnovations targeted at this study that support the development of science, technology, and social culture are as follows. 1) the availability of database update features for Anggah Ungguhing Balinese language that can be used for offline mode. 2) the availability of correction features using the string matching method for word search correction in the translator process in the dictionary application. 3) the availability of a new vocabulary delivery feature is used for users to take part in managing the vocabulary of Anggah Ungguhing Balinese language. 4) the studentsu0027 responses to the Anggah Ungguhing Balinese language have been described based on mobile application in the learning process with an excellent range.

Towards Language Service Creation and Customization for LowResource Languages The most challenging issue with lowresource languages is the difficulty of obtaining enough language resources. In this paper, we propose a language service framework for lowresource languages that enables the automatic creation and customization of new resources from existing ones. To achieve this goal, we first introduce a serviceoriented language infrastructure, the Language Grid; it realizes new language services by supporting the sharing and combining of language resources. We then show the applicability of the Language Grid to lowresource languages. Furthermore, we describe how we can now realize the automation and customization of language services. Finally, we illustrate our design concept by detailing a case study of automating and customizing bilingual dictionary induction for lowresource Turkic languages and Indonesian ethnic languages.