• Journal of KIISE:Databases
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• v.31 no.4
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• pp.395-408
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• 2004

A conjunctive Boolean text query refers to a query that searches for tort documents containing all of the specified keywords, and is the most frequently used query form in information retrieval systems. Typically, the query specifies a long list of keywords for better precision, and in this case, the order of keyword processing has a significant impact on the query speed. Currently known approaches to this ordering are based on heuristics and, therefore, cannot guarantee an optimal ordering. We can use a systematic approach by leveraging a database query processing algorithm like the dynamic programming, but it is not suitable for a text query with a typically long list of keywords because of the algorithm's exponential run-time (Ο(n2$^{n-1}$)) for n keywords. Considering these problems, we propose a new approach based on a property called the join sequence separability. This property states that the optimal join sequence is separable into two subsequences of different join methods under a certain condition on the joined relations, and this property enables us to find a globally optimal join sequence in Ο(n2$^{n-1}$). In this paper we describe the property formally, present an optimization algorithm based on the property, prove that the algorithm finds an optimal join sequence, and validate our approach through simulation using an analytic cost model. Comparison with the heuristic text query optimization approaches shows a maximum of 100 times faster query processing, and comparison with the dynamic programming approach shows exponentially faster query optimization (e.g., 600 times for a 10-keyword query).

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.207-218
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• 2008

With the growth of the Internet, multimedia streaming becomes an important means to deliver video contents over the Internet and the amount of the streaming multimedia contents is also getting increased. However, it becomes difficult to guarantee the quality of service in real-time over the IP network environment with instantaneously varying bandwidth. In this paper, we propose an optimal adaptation framework for streaming contents over the Internet in the sense that the perceptual quality of the multi-angie content with multiple visual objects is maximized given the constraints such as available bandwidth and transcoding cost. In the multi-angle video service framework, the user can select his/her preferred alternate views among the given multiple video streams captured at different view angles for a same event. This enhanced experience often entails streaming problems in real-time over the network, such as instantaneous bandwidth changes in the Internet. In order to cope with this problem, we assume that multi-angle video contents are encoded at different bitrates and the appropriate video streams are then selected or transcoded for delivery to meet such bandwidth constraints. For the user selective consumption of the various bitstreams in the multi-angle video service, the bitstream in each angle can be encoded in various bitrate, and the user can select a sub-bitrstream in the given bitrstreams or transcode the corresponding content in order to deliver the optimally adapted video contents to the instantaneously changing network condition. Therefore, we define the transcoding cost which means the time taken for transcoding the video stream and formulate a unified optimization framework which maximizes the perceptual quality of the multiple video objects in the given constraints such as the transcoding cost and the network bandwidth. Finally, we present plenty of the experimental results to show the effectiveness of the proposed method.