Background: One of the disadvantages of the Impact Factor (IF) is self-citation. The SCImago Journal Rank (SJR) indicator excludes self-citations and considers the quality, rather than absolute numbers, of citations o...
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Background: One of the disadvantages of the Impact Factor (IF) is self-citation. The SCImago Journal Rank (SJR) indicator excludes self-citations and considers the quality, rather than absolute numbers, of citations of a journal by other journals. The present study re-evaluated the influence of self-citation on the 2007 IF for 18 major orthopaedic journals and investigated the difference in ranking between IF and SJR. Methods: The journals were analysed for self-citation both overall and divided into a general group (n = 8) and a specialized group (n = 10). Self-cited and self-citing rates, as well as citation densities and IFs corrected for self-citation (cIF), were calculated. The rankings of the 18 journals by IF and by SJR were compared and the absolute difference between these rankings (Delta R) was determined. Results: Specialized journals had higher self-citing rates (p = 0.01, Delta median = 9.50, 95%CI-19.42 to 0.42), higher self-cited rates (p = 0.0004, Delta median = -10.50, 95% CI-15.28 to -5.72) and greater differences between IF and cIF (p = 0.003, Delta median = 3.50, 95%CI -6.1 to 13.1). There was no significant correlation between self-citing rate and IF for both groups (general: r = 0.46, p = 0.27;specialized: r = 0.21, p = 0.56). When the difference in ranking between IF and SJR was compared between both groups, sub-specialist journals were ranked lower compared to their general counterparts (Delta R: p = 0.006, Delta median = 2.0, 95% CI -0.39 to 4.39). Conclusions: Citation analysis shows that specialized orthopaedic journals have specific self-citation tendencies. The correlation between self-cited rate and IF in our sample was large but, due to small sample size, not significant. The SJR excludes self-citations in its calculation and therefore enhances the underestimation in ranking of specialized journals.
For Influence Maximization(IM) problem based on social network,effective and personalized probability learning method was still not theoretical *** this paper,we proposed a PPV probability model based on IM problem,wh...
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ISBN:
(纸本)9781510835368
For Influence Maximization(IM) problem based on social network,effective and personalized probability learning method was still not theoretical *** this paper,we proposed a PPV probability model based on IM problem,which effectively learnt influence probabilities and personal-ized influence for each node *** clustering user groups and analyzing similarity of users from both offline action log and online social network topological structure,we estimated reliable parameters of our probability model,differed user's influence with different features on its neighbors,and improved probability learning *** Rank algorithm and fuzzy cognitive map concept help to validate our model in PPV *** show that our approach outperforms the state-of-the-art *** preference property g and transition property p,which is called PPV in our model,explains features of influence between user pairs,accuracy of personalized influence probability is improved.
In this paper, we are devoted to the construction and analysis of research network. Firstly, on the basis of data Erdos1, a co-author network is built and two novel measures are proposed to analyze properties of the c...
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In this paper, we are devoted to the construction and analysis of research network. Firstly, on the basis of data Erdos1, a co-author network is built and two novel measures are proposed to analyze properties of the co-author network. A data extraction method using string matching technique is developed and the network is visualized using UCINET. Then, the first-order and second-order entropy are defined to depict the complexity of the network, and the node's invalidity probability and load-bearing capacity are defined to depict the robustness of the network.
Site-based search engines are always the bases for most web-based business *** business applications need specific search *** paper introduces a specifically designed search engine - ToSE (Topic-oriented Search Engine...
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Site-based search engines are always the bases for most web-based business *** business applications need specific search *** paper introduces a specifically designed search engine - ToSE (Topic-oriented Search Engine) to achieve business intelligence for the applications of comparative shopping and intelligent negotiation. With the development of electronic commerce websites, a tremendous amount of merchandise information has been published on *** plays a very important role for e-business *** from a few of classified candidate e-business sites,ToSE collects price pages and parses price ***-text price contexts are then analyzed and transformed into structured data to support *** price information on Internet is changeful,ToSE must complete one updating cycle within an acceptable *** URL spanning tree algorithm is proposed to speed up traversing the hyperlink graph of *** a price-sensitive pagerank algorithm is proposed to score the most valuable and believable price information.
In this article, a novel approach called EPNBC has been proposed by combining the biological information with the naïve Bayesian classifier and pagerank algorithm to predict potential essential proteins. In EPNBC...
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ISBN:
(纸本)9781450396929
In this article, a novel approach called EPNBC has been proposed by combining the biological information with the naïve Bayesian classifier and pagerank algorithm to predict potential essential proteins. In EPNBC, the naïve Bayesian classifier is used to process the original PPI network, and a new protein interaction network with more interaction relationships is obtained. Then, two similarity matrices were obtained by using Gaussian interaction profile kernel similarity based on the protein interaction relationship and gene expression data, and a weighted protein interaction network was obtained. The improved pagerank algorithm was used to score the nodes in the network and output the protein scores in descending order. Experimental results showed that EPNBC was superior to dozens of other methods in identifying essential proteins.
Genetically engineered mouse models are used in high-throughput phenotyping screens to understand genotype-phenotype associations and their relevance to human diseases. However, not all mutant mouse lines with detecta...
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Genetically engineered mouse models are used in high-throughput phenotyping screens to understand genotype-phenotype associations and their relevance to human diseases. However, not all mutant mouse lines with detectable phenotypes are associated with human diseases. Here, we propose the "Target gene selection system for Genetically engineered mouse models" (TarGo). Using a combination of human disease descriptions, network topology, and genotype-phenotype correlations, novel genes that are potentially related to human diseases are suggested. We constructed a gene interaction network using protein-protein interactions, molecular pathways, and co-expression data. Several repositories for human disease signatures were used to obtain information on human disease-related genes. We calculated disease- or phenotype-specific gene ranks using network topology and disease signatures. In conclusion, TarGo provides many novel features for gene function prediction.
Lucene was an excellent technology frame of full-text retrieval engine of open source code. It was widely used for outstanding characters of open source code, excellent indexed construction and effective system constr...
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Lucene was an excellent technology frame of full-text retrieval engine of open source code. It was widely used for outstanding characters of open source code, excellent indexed construction and effective system construction. Initially, it analysed the architecture and the key classes of Lucene, and points out the disadvantage of search algorithm. Then, it gave the example in informative navigation system. Finally, search engine was designed and implemented using the pagerank algorithm, to overcome the shortage of searching algorithm in Lucene.
As the growing amount of data stored on the Internet, the work of searching for information becomes *** traditional collection method cannot achieve a certain effect, it is cumbersome and *** natural language processi...
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ISBN:
(纸本)9781510891357
As the growing amount of data stored on the Internet, the work of searching for information becomes *** traditional collection method cannot achieve a certain effect, it is cumbersome and *** natural language processing technology and web crawler technology to collect and analyze data about student evaluation, the purpose is to obtain the key factors affecting teachers' comprehensive evaluation results and propose the methods to solve the *** the traditional Web crawler technology, there is a lack of certain intelligence, initiative, *** design of the best priority crawler framework has improved and optimized its *** the improved pagerank value, user demand correlation degree, and NDC algorithm denoising are added, it can effectively solve a series of problems such as long retrieval time, overlapping information, incomplete information, and improve the accuracy of information collection.
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