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Real-time keywords potentially demonstrate positive effects when they are provided in cross-cultural communication. Previously real-time keywords generated by a speaker during talking were investigated, and it was found it contributes to build mutual understanding and knowledge. However the use of keywords was not
Library search systems that use "keywords" are very useful for people who know what they are looking for; however, this system is not helpful for those who do not have specific knowledge of what they are looking for. The purpose of this research is to propose a Kansei-library search system. Based on observing how
visualization. From testing result, we reach 89% success rate of keyword extraction using RIDF term weighting method and collecting messages by certain category. General topic about governor election and 13 subtopics was successfully extracted from set data flood in Jakarta.
structured (PS) music data, WAV real example (RE) music data and keyword sound (WS) text-information data. Firstly, we introduce our system architecture. Secondly, we propose anew construction method for music feature libraries in order to achieve more satisfactory results. Thirdly, we present and design the novel mix-indexing
proposed to provide users with a personalized news service. The system takes advantage of the network information crawling, web-based text mining and personalized recommendations technologies to realize automated extraction of news tag. The innovation of this mode is that the tag contains both categories and keywords. It
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.