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Contexts and aspects have been distinguished as the significant factors in fabricating recommender systems. Most recommender systems aim at utilizing either non-contextual preferences or contextual preferences distinctly, while very few endeavors have been made to identify the significance of both. Hence an attempt has been made to study the influence of both, users' context dependent and context...
Majority of recommender systems have their basis on either of the aspectual factors or contextual factors where as very few systems endeavours to demonstrate the use of both factors collectively. Very few works have been done to identify more fine-grained aspect level contextual preferences and their significance in generating accurate predictions for the user. Accuracy has constantly been the centre...
Information explosion is a well known phenomenon now and there is a vast amount of research going on into how best to handle and process huge amounts of data. One such idea for processing enormous quantities of data is Google's Map/Reduce. Map/Reduce was first introduced by Google engineers - Jeffrey Dean and Sanjay Ghemawat [9]. It was designed for and is still used at Google for processing large...
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.