keyword search over relational databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema...
详细信息
keyword search over relational databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. A method of automatically reformulating user queries by user feedback aimed at the results of KSORD is introduced in this paper, which is named UFBP (user feedback based on probability). After the first time of retrieval, according to the users' feedback information, UFBP computes terms to be added into the expanded query based on probability and reformulates the new query using query expansion. After KSORD executing the new query automatically, more relevant results are presented to user. Experimental results verify its effectiveness.
Compared with traditional magnetic disks, Flash memory has many advantages and has been used as external storage media for a wide spectrum of electronic devices (such as PDA, MP3, Digital Camera and Mobile Phone) in r...
详细信息
Closed frequent itemsets(CFI) mining uses less memory to store the entire information of frequent itemsets thus is much suitable for mining stream. In this paper, we discuss recent CFI mining methods over stream and p...
详细信息
Sequential pattern mining is an important problem in continuous, fast, dynamic and unlimited stream mining. Recently approximate mining algorithms are proposed which spend too many system resources and can only obtain...
详细信息
Both Content analysis and link, analysis have its advantages in measuring relationships among documents. In this paper. we propose a new method to combine these two methods to compute the similarity of research papers...
详细信息
ISBN:
(纸本)9783540881919
Both Content analysis and link, analysis have its advantages in measuring relationships among documents. In this paper. we propose a new method to combine these two methods to compute the similarity of research papers so that we can do clustering of these papers more accurately. In order to improve the efficiency of similarity calculation, we develop a strategy to deal with the relationship graph separately, without affecting the accuracy. We also design an approach to assign different weights to different links to the papers, which can enhance the accuracy of similarity calculation. The experimental results conducted oil ACM data Set show that our new algorithm. S-SimRank, outperforms other algorithms.
database-as-a-Service is a promising data management paradigm in which data is encrypted before being sent to the untrusted server. Efficient querying on encrypted data is a performance critical problem which has vari...
详细信息
Collaborative filtering is an important personalized recommendation technique applied widely in E-commerce. It is not adapted to multi-interest or title recommendation for the 'general neighbourhood' problem w...
详细信息
Detecting and exploiting correlations among columns in relational databases are of great value for query optimizers to generate better query execution plans (QEPs). We propose a more robust and informative metric, nam...
详细信息
Extracting multi-records from web pages is useful, it allows us to integrate information from multiple sources to provide value-added services. Existing techniques still have some limitations because of their several ...
详细信息
暂无评论