Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 ...Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 during concurrent outbreaks in Marburg and Frankfurt,Germany,and in Belgrade,Serbia,linked to laboratory use of African green monkeys imported from Uganda.Subsequent outbreaks and isolated cases have been reported in various African countries,including Angola,the Democratic Republic of the Congo,Equatorial Guinea,Ghana,Guinea,Kenya,Rwanda,South Africa(in an individual with recent travel to Zimbabwe),Tanzania,and Uganda.Initial human MVD infections typically occur due to prolonged exposure to mines or caves inhabited by Rousettus aegyptiacus fruit bats,the natural hosts of the virus.展开更多
速度和效果是聚类算法面临的两大问题.DBSCAN(density based spatial clustering of applications with noise)是典型的基于密度的一种聚类方法,对于大型数据库的聚类实验显示了它在速度上的优越性.提出了一种基于密度的递归聚类算法(re...速度和效果是聚类算法面临的两大问题.DBSCAN(density based spatial clustering of applications with noise)是典型的基于密度的一种聚类方法,对于大型数据库的聚类实验显示了它在速度上的优越性.提出了一种基于密度的递归聚类算法(recursive density based clustering algorithm,简称RDBC),此算法可以智能地、动态地修改其密度参数.RDBC是基于DBSCAN的一种改进算法,其运算复杂度和DBSCAN相同.通过在Web文档上的聚类实验,结果表明,RDBC不但保留了DBSCAN高速度的优点,而且聚类效果大大优于DBSCAN.展开更多
Due to a great deal of valuable information contained in the Web log file, the result of Web mining can be used to enhance the decision making for electronic commerce (EC) operation and management. Because of ambiguo...Due to a great deal of valuable information contained in the Web log file, the result of Web mining can be used to enhance the decision making for electronic commerce (EC) operation and management. Because of ambiguous and abundance of the Web log file, the least decision making model based on rough set theory was presented for Web mining. And an example was given to explain the model. The model can predigest the decision making table, so that the least solution of the table can be acquired. According to the least solution, the corresponding decision for individual service can be made in sequence. Web mining based on rough set theory is also currently the original and particular method.展开更多
Improvement on mining the frequently visited groups of web pages was studied. First, in the data preprocessing phrase, we introduce an extra frame filtering step that reduces the negative influence of frame pages on t...Improvement on mining the frequently visited groups of web pages was studied. First, in the data preprocessing phrase, we introduce an extra frame filtering step that reduces the negative influence of frame pages on the result page groups. Through recognizing the frame pages in the site documents and constructing the frame subframe relation set, the subframe pages that influence the final mining result can be efficiently filtered. Second, we enhance the mining algorithm with the consideration of both the site topology and the content of the web pages. By the introduction of the normalized content link ratio of the web page and the group interlink degree of the page group, the enhanced algorithm concentrates more on the content pages that are less interlinked together. The experiments show that the new approach can effectively reveal more interesting page groups, which would not be found without these enhancements.展开更多
The backdoor or information leak of Web servers can be detected by using Web Mining techniques on some abnormal Web log and Web application log data. The security of Web servers can be enhanced and the damage of illeg...The backdoor or information leak of Web servers can be detected by using Web Mining techniques on some abnormal Web log and Web application log data. The security of Web servers can be enhanced and the damage of illegal access can be avoided. Firstly, the system for discovering the patterns of information leakages in CGI scripts from Web log data was proposed. Secondly, those patterns for system administrators to modify their codes and enhance their Web site security were provided. The following aspects were described: one is to combine web application log with web log to extract more information,so web data mining could be used to mine web log for discovering the information that firewall and Information Detection System cannot find. Another approach is to propose an operation module of web site to enhance Web site security. In cluster server session, Density -Based Clustering technique is used to reduce resource cost and obtain better efficiency.展开更多
Web-log contains a lot of information related with user activities on the Internet. How to mine user browsing interest patterns effectively is an important and challengeable research topic. On the analysis of the pres...Web-log contains a lot of information related with user activities on the Internet. How to mine user browsing interest patterns effectively is an important and challengeable research topic. On the analysis of the present algorithm’s advantages and disadvantages we propose a new concept: support-interest. Its key insight is that visitor will backtrack if they do not find the information where they expect. And the point from where they backtrack is the expected location for the page. We present User Access Matrix and the corresponding algorithm for discovering such expected locations that can handle page caching by the browser. Since the URL-URL matrix is a sparse matrix which can be represented by List of 3-tuples, we can mine user preferred sub-paths from the computation of this matrix. Accordingly, all the sub-paths are merged, and user preferred paths are formed. Experiments showed that it was accurate and scalable. It’s suitable for website based application, such as to optimize website’s topological structure or to design personalized services. Key words Web Mining - user preferred path - Web-log - support-interest - personalized services CLC number TP 391 Foundation item: Supported by the National High Technology Development (863 program of China) (2001AA113182)Biography: ZHOU Hong-fang (1976-), female.Ph. D candidate, research direction: data mining and knowledge discovery in databases.展开更多
The structure of Web site became more complex than before. During the design period of a Web site, the lack of model and method results in improper Web structure, which depend on the designer's experience. From th...The structure of Web site became more complex than before. During the design period of a Web site, the lack of model and method results in improper Web structure, which depend on the designer's experience. From the point of view of software engineering, every period in the software life must be evaluated before starting the next period's work. It is very important and essential to search relevant methods for evaluating Web structure before the site is completed. In this work, after studying the related work about the Web structure mining and analyzing the major structure mining methods (Page\|rank and Hub/Authority), a method based on the Page\|rank for Web structure evaluation in design stage is proposed. A Web structure modeling language WSML is designed, and the implement strategies for evaluating system of the Web site structure are given out. Web structure mining has being used mainly in search engines before. It is the first time to employ the Web structure mining technology to evaluate a Web structure in the design period of a Web site. It contributes to the formalization of the design documents for Web site and the improving of software engineering for large scale Web site, and the evaluating system is a practical tool for Web site construction.展开更多
A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is...A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is used to identifying which active session a request should belong to. The competitive method is applied to determine the end of the sessions. Compared with other algorithms, more successful sessions are additionally detected by semantic outlier analysis.展开更多
With the explosive growth of information sources available on the World Wide Web, how to combine the results of multiple search engines has become a valuable problem. In this paper, a search strategy based on genetic ...With the explosive growth of information sources available on the World Wide Web, how to combine the results of multiple search engines has become a valuable problem. In this paper, a search strategy based on genetic simulated annealing for search engines in Web mining is proposed. According to the proposed strategy, there exists some important relationship among Web statistical studies, search engines and optimization techniques. We have proven experimentally the relevance of our approach to the presented queries by comparing the qualities of output pages with those of the original downloaded pages, as the number of iterations increases better results are obtained with reasonable execution time.展开更多
Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a...Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.展开更多
As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major ca...As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system. In case of collaborative recommendation systems, these try to seek out users who share same tastes that of given user as well as recommends the websites according to the liking given user. Whereas the content based recommendation systems tries to recommend web sites similar to those web sites the user has liked. In the recent research we found that the efficient technique based on association rule mining algorithm is proposed in order to solve the problem of web page recommendation. Major problem of the same is that the web pages are given equal importance. Here the importance of pages changes according to the frequency of visiting the web page as well as amount of time user spends on that page. Also recommendation of newly added web pages or the pages that are not yet visited by users is not included in the recommendation set. To overcome this problem, we have used the web usage log in the adaptive association rule based web mining where the association rules were applied to personalization. This algorithm was purely based on the Apriori data mining algorithm in order to generate the association rules. However this method also suffers from some unavoidable drawbacks. In this paper we are presenting and investigating the new approach based on weighted Association Rule Mining Algorithm and text mining. This is improved algorithm which adds semantic knowledge to the results, has more efficiency and hence gives better quality and performances as compared to existing approaches.展开更多
The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many r...The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many researchers to apply Data Mining techniques on it. This paper gives a detailed state-of-the-art survey of on-going research in this new area. It shows the positive effects of Semantic Web Mining, the obstacles faced by researchers and propose number of approaches to deal with the very complex and heterogeneous information and knowledge which are produced by the technologies of Semantic Web.展开更多
文摘Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 during concurrent outbreaks in Marburg and Frankfurt,Germany,and in Belgrade,Serbia,linked to laboratory use of African green monkeys imported from Uganda.Subsequent outbreaks and isolated cases have been reported in various African countries,including Angola,the Democratic Republic of the Congo,Equatorial Guinea,Ghana,Guinea,Kenya,Rwanda,South Africa(in an individual with recent travel to Zimbabwe),Tanzania,and Uganda.Initial human MVD infections typically occur due to prolonged exposure to mines or caves inhabited by Rousettus aegyptiacus fruit bats,the natural hosts of the virus.
文摘速度和效果是聚类算法面临的两大问题.DBSCAN(density based spatial clustering of applications with noise)是典型的基于密度的一种聚类方法,对于大型数据库的聚类实验显示了它在速度上的优越性.提出了一种基于密度的递归聚类算法(recursive density based clustering algorithm,简称RDBC),此算法可以智能地、动态地修改其密度参数.RDBC是基于DBSCAN的一种改进算法,其运算复杂度和DBSCAN相同.通过在Web文档上的聚类实验,结果表明,RDBC不但保留了DBSCAN高速度的优点,而且聚类效果大大优于DBSCAN.
文摘Due to a great deal of valuable information contained in the Web log file, the result of Web mining can be used to enhance the decision making for electronic commerce (EC) operation and management. Because of ambiguous and abundance of the Web log file, the least decision making model based on rough set theory was presented for Web mining. And an example was given to explain the model. The model can predigest the decision making table, so that the least solution of the table can be acquired. According to the least solution, the corresponding decision for individual service can be made in sequence. Web mining based on rough set theory is also currently the original and particular method.
文摘Improvement on mining the frequently visited groups of web pages was studied. First, in the data preprocessing phrase, we introduce an extra frame filtering step that reduces the negative influence of frame pages on the result page groups. Through recognizing the frame pages in the site documents and constructing the frame subframe relation set, the subframe pages that influence the final mining result can be efficiently filtered. Second, we enhance the mining algorithm with the consideration of both the site topology and the content of the web pages. By the introduction of the normalized content link ratio of the web page and the group interlink degree of the page group, the enhanced algorithm concentrates more on the content pages that are less interlinked together. The experiments show that the new approach can effectively reveal more interesting page groups, which would not be found without these enhancements.
文摘The backdoor or information leak of Web servers can be detected by using Web Mining techniques on some abnormal Web log and Web application log data. The security of Web servers can be enhanced and the damage of illegal access can be avoided. Firstly, the system for discovering the patterns of information leakages in CGI scripts from Web log data was proposed. Secondly, those patterns for system administrators to modify their codes and enhance their Web site security were provided. The following aspects were described: one is to combine web application log with web log to extract more information,so web data mining could be used to mine web log for discovering the information that firewall and Information Detection System cannot find. Another approach is to propose an operation module of web site to enhance Web site security. In cluster server session, Density -Based Clustering technique is used to reduce resource cost and obtain better efficiency.
文摘Web-log contains a lot of information related with user activities on the Internet. How to mine user browsing interest patterns effectively is an important and challengeable research topic. On the analysis of the present algorithm’s advantages and disadvantages we propose a new concept: support-interest. Its key insight is that visitor will backtrack if they do not find the information where they expect. And the point from where they backtrack is the expected location for the page. We present User Access Matrix and the corresponding algorithm for discovering such expected locations that can handle page caching by the browser. Since the URL-URL matrix is a sparse matrix which can be represented by List of 3-tuples, we can mine user preferred sub-paths from the computation of this matrix. Accordingly, all the sub-paths are merged, and user preferred paths are formed. Experiments showed that it was accurate and scalable. It’s suitable for website based application, such as to optimize website’s topological structure or to design personalized services. Key words Web Mining - user preferred path - Web-log - support-interest - personalized services CLC number TP 391 Foundation item: Supported by the National High Technology Development (863 program of China) (2001AA113182)Biography: ZHOU Hong-fang (1976-), female.Ph. D candidate, research direction: data mining and knowledge discovery in databases.
文摘The structure of Web site became more complex than before. During the design period of a Web site, the lack of model and method results in improper Web structure, which depend on the designer's experience. From the point of view of software engineering, every period in the software life must be evaluated before starting the next period's work. It is very important and essential to search relevant methods for evaluating Web structure before the site is completed. In this work, after studying the related work about the Web structure mining and analyzing the major structure mining methods (Page\|rank and Hub/Authority), a method based on the Page\|rank for Web structure evaluation in design stage is proposed. A Web structure modeling language WSML is designed, and the implement strategies for evaluating system of the Web site structure are given out. Web structure mining has being used mainly in search engines before. It is the first time to employ the Web structure mining technology to evaluate a Web structure in the design period of a Web site. It contributes to the formalization of the design documents for Web site and the improving of software engineering for large scale Web site, and the evaluating system is a practical tool for Web site construction.
基金Supported by the Huo Yingdong Education Foundation of China(91101)
文摘A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is used to identifying which active session a request should belong to. The competitive method is applied to determine the end of the sessions. Compared with other algorithms, more successful sessions are additionally detected by semantic outlier analysis.
基金Supported by the National Natural Science Foundation of China (60673093)
文摘With the explosive growth of information sources available on the World Wide Web, how to combine the results of multiple search engines has become a valuable problem. In this paper, a search strategy based on genetic simulated annealing for search engines in Web mining is proposed. According to the proposed strategy, there exists some important relationship among Web statistical studies, search engines and optimization techniques. We have proven experimentally the relevance of our approach to the presented queries by comparing the qualities of output pages with those of the original downloaded pages, as the number of iterations increases better results are obtained with reasonable execution time.
基金Supported by the National Natural Science Foundation of China(60472099)Ningbo Natural Science Foundation(2006A610017)
文摘Because data warehouse is frequently changing, incremental data leads to old knowledge which is mined formerly unavailable. In order to maintain the discovered knowledge and patterns dynamically, this study presents a novel algorithm updating for global frequent patterns-IPARUC. A rapid clustering method is introduced to divide database into n parts in IPARUC firstly, where the data are similar in the same part. Then, the nodes in the tree are adjusted dynamically in inserting process by ＂pruning and laying back＂ to keep the frequency descending order so that they can be shared to approaching optimization. Finally local frequent itemsets mined from each local dataset are merged into global frequent itemsets. The results of experimental study are very encouraging. It is obvious from experiment that IPARUC is more effective and efficient than other two contrastive methods. Furthermore, there is significant application potential to a prototype of Web log Analyzer in web usage mining that can help us to discover useful knowledge effectively, even help managers making decision.
文摘As the growing interest of web recommendation systems those are applied to deliver customized data for their users, we started working on this system. Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system. In case of collaborative recommendation systems, these try to seek out users who share same tastes that of given user as well as recommends the websites according to the liking given user. Whereas the content based recommendation systems tries to recommend web sites similar to those web sites the user has liked. In the recent research we found that the efficient technique based on association rule mining algorithm is proposed in order to solve the problem of web page recommendation. Major problem of the same is that the web pages are given equal importance. Here the importance of pages changes according to the frequency of visiting the web page as well as amount of time user spends on that page. Also recommendation of newly added web pages or the pages that are not yet visited by users is not included in the recommendation set. To overcome this problem, we have used the web usage log in the adaptive association rule based web mining where the association rules were applied to personalization. This algorithm was purely based on the Apriori data mining algorithm in order to generate the association rules. However this method also suffers from some unavoidable drawbacks. In this paper we are presenting and investigating the new approach based on weighted Association Rule Mining Algorithm and text mining. This is improved algorithm which adds semantic knowledge to the results, has more efficiency and hence gives better quality and performances as compared to existing approaches.
文摘The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many researchers to apply Data Mining techniques on it. This paper gives a detailed state-of-the-art survey of on-going research in this new area. It shows the positive effects of Semantic Web Mining, the obstacles faced by researchers and propose number of approaches to deal with the very complex and heterogeneous information and knowledge which are produced by the technologies of Semantic Web.
