Faced with hundreds of thousands of news articles in the news websites,it is difficult for users to find the news articles they are interested in.Therefore,various news recommender systems were built.In the news recom...Faced with hundreds of thousands of news articles in the news websites,it is difficult for users to find the news articles they are interested in.Therefore,various news recommender systems were built.In the news recommendation,these news articles read by a user is typically in the form of a time sequence.However,traditional news recommendation algorithms rarely consider the time sequence characteristic of user browsing behaviors.Therefore,the performance of traditional news recommendation algorithms is not good enough in predicting the next news article which a user will read.To solve this problem,this paper proposes a time-ordered collaborative filtering recommendation algorithm(TOCF),which takes the time sequence characteristic of user behaviors into account.Besides,a new method to compute the similarity among different users,named time-dependent similarity,is proposed.To demonstrate the efficiency of our solution,extensive experiments are conducted along with detailed performance analysis.展开更多
A new type of despreader for direct sequence spread spectrum signal is proposed. Compared with traditional despreaders, the new despreader does not contain hard decision ware or handle binary sequence any more, and th...A new type of despreader for direct sequence spread spectrum signal is proposed. Compared with traditional despreaders, the new despreader does not contain hard decision ware or handle binary sequence any more, and the locally stored spread spectrum signals are pre-modulated baseband signals (such as Gaussian minimum shift keying (GMSK) signals), which are much more similar to the received spread spectrum signals. Moreover, the missed detection probability of the despreader is about one order of magnitude lower than that of traditional ones. Based on the maximum likelihood criterion and phase probability density function of demodulated signal, a new method of ana- lyzing the despreaders’ performance is put forward, which is proved to be more accurate than traditional methods according to the numerical results. Finally, an adaptive despreader under different signal-to-noise ratios is given.展开更多
基金supported by the Natural Science Foundation of China(No.61170174, 61370205)Tianjin Training plan of University Innovation Team(No.TD12-5016)
文摘Faced with hundreds of thousands of news articles in the news websites,it is difficult for users to find the news articles they are interested in.Therefore,various news recommender systems were built.In the news recommendation,these news articles read by a user is typically in the form of a time sequence.However,traditional news recommendation algorithms rarely consider the time sequence characteristic of user browsing behaviors.Therefore,the performance of traditional news recommendation algorithms is not good enough in predicting the next news article which a user will read.To solve this problem,this paper proposes a time-ordered collaborative filtering recommendation algorithm(TOCF),which takes the time sequence characteristic of user behaviors into account.Besides,a new method to compute the similarity among different users,named time-dependent similarity,is proposed.To demonstrate the efficiency of our solution,extensive experiments are conducted along with detailed performance analysis.
基金Supported by National Natural Science Foundation of China (No. 60572147) National "111" Program of Introducing Talents of Discipline to Universities (No. B08038)
文摘A new type of despreader for direct sequence spread spectrum signal is proposed. Compared with traditional despreaders, the new despreader does not contain hard decision ware or handle binary sequence any more, and the locally stored spread spectrum signals are pre-modulated baseband signals (such as Gaussian minimum shift keying (GMSK) signals), which are much more similar to the received spread spectrum signals. Moreover, the missed detection probability of the despreader is about one order of magnitude lower than that of traditional ones. Based on the maximum likelihood criterion and phase probability density function of demodulated signal, a new method of ana- lyzing the despreaders’ performance is put forward, which is proved to be more accurate than traditional methods according to the numerical results. Finally, an adaptive despreader under different signal-to-noise ratios is given.
