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Internet users are shifting from searching on traditional media to social network platforms (SNPs) to retrieve up-to-date and valuable information. SNPs have two unique characteristics: frequent content update and small world phenomenon. However, existing works are not able to support these two features simultaneously. To address this problem, we develop a general framework to enable real time personalized...
SQL is a classical and powerful tool for querying relational databases. However, it is rather hard for inexperienced users to pose SQL queries, as they are required to be proficient in SQL syntax and have a thorough understanding of the underlying schema. To give users gratification, we propose SQLSUGG, an effective and user-friendly keyword-based method to help various users formulate SQL queries...
Query term suggestion that interactively expands the queries is an indispensable technique to help users formulate high-quality queries and has attracted much attention in the community of web search. Existing methods usually suggest terms based on statistics in documents as well as query logs and external dictionaries, and they neglect the fact that the topic information is very crucial because it...
A common approach to performing keyword search over relational databases is to find the minimum Steiner trees in database graphs. These methods, however, are rather expensive as the minimum Steiner tree problem is known to be NP-hard. Further, these methods cannot benefit from DBMS capabilities. We propose a new concept called Compact Steiner Tree (CSTree), which can be used to approximate the Steiner...
The leap from single-core to multi-core has permanently altered the course of computing, enabling increased productivity, powerful energy-efficient performance, and leading-edge advanced computing experiences. Although traditional single-thread XPath query evaluation algorithms can run properly on multi-core CPUs, they cannot take full use of the computing resources of multi-core CPUs. To take advantage...
Existing studies for mining frequent XML query patterns mainly introduce a straightforward candidate generate-and-test strategy and compute frequencies of candidate query patterns from scratch periodically by checking the entire transaction database, which consists of XML query patterns transformed from user queries. However, it is nontrivial to maintain such discovered frequent patterns in real XML...
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