A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and...A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.展开更多
To improve efficiency of search engines, the query result cache has drawn much attention re- cently. According to the query processing and user＇s query logs locality, a new hybrid result cache strategy which associat...To improve efficiency of search engines, the query result cache has drawn much attention re- cently. According to the query processing and user＇s query logs locality, a new hybrid result cache strategy which associates with caching heat and worth is proposed to compute cache score in accord- ance with cost-aware strategies. Exactly, query repeated distance and query length factor are utilized to improve the static result policy, and the dynamic policy is adjusted by the caching worth. The hy- brid result cache is implemented in term of the document content and document ids （docIds） se- quence. Based on a score format and the new hybrid structure, an initial algorithm and a new rou- ting algorithm are designed for result cache. Experiments＇ results show that the improved caching policies decrease the average response time effectively, and increase the system throughput signifi- cantly. By choosing comfortable combination of page cache and docIds cache, the new hybrid cac- hing strategy almost reduces more than 20% of the only cache and docId-only cache. average query time compared with the basic page-展开更多
基金The National Natural Science Foundation of China(No.60503020,60373066,60403016,60425206),the Natural Science Foundation of Jiangsu Higher Education Institutions ( No.04KJB520096),the Doctoral Foundation of Nanjing University of Posts and Telecommunication (No.0302).
文摘A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.
基金Supported by the National Natural Science Foundation of China(No.61173024)
文摘To improve efficiency of search engines, the query result cache has drawn much attention re- cently. According to the query processing and user＇s query logs locality, a new hybrid result cache strategy which associates with caching heat and worth is proposed to compute cache score in accord- ance with cost-aware strategies. Exactly, query repeated distance and query length factor are utilized to improve the static result policy, and the dynamic policy is adjusted by the caching worth. The hy- brid result cache is implemented in term of the document content and document ids （docIds） se- quence. Based on a score format and the new hybrid structure, an initial algorithm and a new rou- ting algorithm are designed for result cache. Experiments＇ results show that the improved caching policies decrease the average response time effectively, and increase the system throughput signifi- cantly. By choosing comfortable combination of page cache and docIds cache, the new hybrid cac- hing strategy almost reduces more than 20% of the only cache and docId-only cache. average query time compared with the basic page-
