The speech interaction in-vehicle was mainly realized by the speech recognition. The human-machine interaction around was usually disturbed by the noise, and the speech received by the receiver was not the original pu...
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To accurately and actively provide users with their potentially interested information or services is the main task of a recommender system. Collaborative filtering is one of the most widely adopted recommender method...
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To accurately and actively provide users with their potentially interested information or services is the main task of a recommender system. Collaborative filtering is one of the most widely adopted recommender methods, whereas it is suffering the issue of sparse rating data that will severely degenerate the quality of recommendations. To address this issue, the article proposes a novel method, named the FTRA (Fusing Trust and Ratings), trying to improve the performance of collaborative filtering recommendation by means of elaborately integrating twofold sparse information, i.e., the conventional rating data given by users and the social trust network among the same users. The performance of FTRA is rigorously validated by comparing it with six representative methods on a real-world dataset. The experimental results show that the FTRA outperforms all other competitors in terms of both precision and recall. More importantly, our work suggests that the strategy of augmenting sparse rating data by fusing trust networks does significantly improve the quality of conventional collaborative filtering recommendation, and its quality could be further improved by means of designing more effective integrating schemes.
In this paper, we introduce a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the multi-chromosomal reversal median problem. We convert the large-scale genome in...
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ISBN:
(纸本)9783037853245
In this paper, we introduce a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the multi-chromosomal reversal median problem. We convert the large-scale genome into TSP maps at first. Then we use a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the problem. In our improved algorithm, we increase the search speed by implement multi-branch parallel search of ACO. Our extensive experiments on simulated datasets show that this median solver is efficient.
Automatic image annotation has been an active research topic in the last decade due to its potentially large impact on image retrieval, object recognition and image understanding. Many approaches have been proposed fo...
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This paper presents a new edge-counting based method using Word Net to compute the similarity. The method achieves a similarity that perfectly fits with human rating and effectively simulate the human tHought process ...
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Visual voice lip-reading, so the computer can understand what the speakers want to express direction by looking at their lips. Lip reading is the easiest way to compare the early characters and templates from the froz...
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Community structure is one of non-trivial topological properties ubiquitously demonstrated in real-world complex networks. Related theories and approaches are of fundamental importance for understanding the functions ...
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Feature selection is an effective technique to put the high dimension of data down, which is prevailing in many application domains, such as text categorization and bio-informatics, and can bring many advantages, such...
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In this paper, we propose PSOfold, a particle swarm optimization for RNA secondary structure prediction. PSOfold is based on the recently published IPSO. We present two strategies to improve the performance of IPSO. F...
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The core idea of clustering algorithm is the division of data into groups of similar objects. Some clustering algorithms are proven good performance on document clustering, such as k-means and UPGMA etc. However, few ...
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