Nianlong Luo

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With the development of recommendation systems, reasonable designed recommendation algorithms and application on actual systems have been important fields of personalized recommendation. System characteristics and users' specific needs become two key considerations of these algorithms. Since many actual systems are user-intensive and their items are(More)
In this paper, we propose a method for mining user interests based on topic map in an e-learning system. It is now widely assumed that in personalized information area user interests plays an important role in document recommendation. User interests generally reflect the user background and topics of interests. Topic Maps is an ISO standard for the(More)
In this paper, we propose a method for resource recommendation based on topic model in an e-learning system. The Web provides an extremely large and dynamic source of information. So it is now increasingly popular to provide personalized service in document recommendation. Personalized service can reduce information overload and, hence, increase user(More)
With the development of personalized recommendation systems, the research of collaborative filtering reached a bottleneck. Neither algorithm accuracy nor computational complexity can be improved significantly. In this paper, we present our statistics and analysis on some recognized datasets. The analysis shows that the real rating features of the users(More)
A common feature of DNA repair enzymes is their ability to recognize the damage independently of sequence in which they are found. The presence of a flipped out base inserted into the protein in several DNA-enzyme complexes suggests a contribution to enzyme specificity. Molecular simulations of damaged DNA indicate that the damage produces changes in DNA(More)
With the rapid development of online peer-to-peer (P2P) lending platforms in recent years, more and more people participate in the borrowing and lending transactions online. The risk attitude of online lenders normally determines the size of capital invested on the platforms during different periods. Although investment time series from each lender is(More)