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A context-aware personalized travel recommendation system based on geotagged social media data mining Abdul Majid a , Ling Chen a , Gencai Chen a , Hamid Turab Mirza a , Ibrar Hussain a & John Woodward b a College of Computer Science, Zhejiang University, 38 Zheda Road, Hangzhou, 310027, PR China b School of Computer Science, The University of Nottingham(More)
Article history: Received 18 September 2012 Received in revised form 28 October 2014 Accepted 8 November 2014 Available online xxxx Geo-tagged photos of users on social media sites (e.g., Flickr) provide plentiful location-based data. This data provide a wealth of information about user behaviours and their potential is increasing, as it becomes ever-more(More)
This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the(More)
MOTIVATION Subcellular localization of proteins is one of the most significant characteristics of living cells. Prediction of protein subcellular locations is crucial to the understanding of various protein functions. Therefore, an accurate, computationally efficient and reliable prediction system is required. RESULTS In this article, the predictions of(More)
Inflammation is one of the primary processes underlying respiratory distress syndrome (RDS) and its evolution into bronchopulmonary dysplasia (BPD). Recruitment and subsequent activation of macrophages in the lung are mediated by CC chemokines. The role of CC chemokines has not been extensively studied in the course of RDS. Serial tracheal aspirates (TA)(More)
Precise information about protein locations in a cell facilitates in the understanding of the function of a protein and its interaction in the cellular environment. This information further helps in the study of the specific metabolic pathways and other biological processes. We propose an ensemble approach called "CE-PLoc" for predicting subcellular(More)