| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2009: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2008: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Research Abstract |
In recent years, there has been growing interest in keyword search over traditional relational databases. Usually a relational database is represented as a graph structure; an appropriate subgraph is computed as an answer to a keyword query. In these studies, the units of query results is based on the concept of 'minimality', that is, each answer subgraph is the smallest subgraph containing each query keyword. However, the concept of
minimality' cannot be applied to keyword search over a graph representing heterogeneous information in a personal information management system. It is because an appropriate answer is not necessarily a subgraph comprising the nodes having at least one occurrence of each query. As a result, further expansion of the concept of 'minimality' needs to be need to be considered. In this research, we proposed the concept of "beyond minimality" for computing answer units in keyword search over a graph representing heterogeneous information. We also explored algebrai
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c operations to generate such answer units.
In a traditional information retrieval system, it is common to rank search result in a descending order of relevance. In other words, search result, rather than just a collection of elements, is a ranked list type. Thus, as query result in a traditional database system is a simple collection of tuple elements, query optimization is achieved through various strategies---one of them being the manipulation of algebraic operations. However, it is obvious that the similar kind of optimization cannot be guaranteed in keyword search over a personal information management system.
Electronic textbooks and PowerPoint slides which refer to those textbooks have specific characteristics in a personal information management system. Such data can be categorized as a special kind of synchronized media streams can contain additional temporal information. In order to efficiently and effectively find information in a large collection of synchronized media streams, we have proposed a data model that represents information in a two-dimensional space. This space can be manipulated by our query processor. Less
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