The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
fields and provides to the researchers the application form best matched to the researcher's current research field. We have developed recommendation system of Grant-in-Aid system for researchers by using JSPS (Japan Society for the Promotion of Science) keywords. The system can determine some rules associated between the
underlying levels of semantic uncertainty in terms of Web events, and then utilize these for Webpage recommendations. Our idea is to consider a Web event as a system composed of different keywords, and the uncertainty of this keyword system is related to the uncertainty of the particular Web event. Based on keyword association
Classical algorithms of keywords extraction can hardly get low computational complexity and high accuracy. The association rule mining based algorithm is proposed in this paper. This algorithm adopts improved FP-Growth algorithm to extract word co-occurrence information, utilizes the similarity algorithm to eliminate
generate and calculate the associated relations and their strengths between documents within a domain. Each document is represented by a bag of words and their weights. We first build domain knowledge background based on the association rules at keyword level, and then we apply those association rules to generate and
Can keyword-hashtag networks, derived from Big Data environments such as Twitter, yield clinicians a powerful tool to extrapolate patterns that may lead to development of new medical therapy and/or drugs? In our paper, we present a systematic network mining method to answer this question. We present HashnetMiner, a
With the development of Intemet and the distributed database technology, a great deal of data is stored in the disrtibuted Web nodes and it is impossible to be stored in one single node on account of communication, efficiency and security. So it's a very important research in the data mining domain. This paper makes a thorough research on mining association rules in the distributed database system...
A novel text association rule approach FHAR algorithm is presented. To overcome the defect of traditional keywords which does not take into account the semantic relation between keywords, FHAR algorithm in the paper is based on concept vector. The density of semantic field and the weight of meaning are used to
, irrelevant tweets were further segregated by means of a unigram dictionary containing education-oriented keywords. The Apriori algorithm was then applied to the dataset thus obtained resulting in characteristic markers or patterns of these institutes.
intelligent searching system for Indonesian law documents which is enhanced by association analysis to discover the association of law related keywords, thus providing guidance for the user to find related verses.
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.