Visualization and Online Analytical Processing for IR Systems: A Case Study on CS Research Papers Search
碩士 === 國立中央大學 === 資訊工程學系碩士在職專班 === 98 === Information overload is an increasing problem which often causes inefficiency. Take junior graduates as an example, searching good research papers can take a lot of time. Existing retrieval systems often display search results based on some internal ranking...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/63887329387383322174 |
| Summary: | 碩士 === 國立中央大學 === 資訊工程學系碩士在職專班 === 98 === Information overload is an increasing problem which often causes inefficiency. Take junior graduates as an example, searching good research papers can take a lot of time. Existing retrieval systems often display search results based on some internal ranking score. In this paper, we propose the integration of information extraction with OLAP (online analytical processing) and visualization technique to achieve interactive search experience. We define two extraction targets: application environment (AE) and involved method/technique (MT) as the basic elements that define the research problem and the contribution of a paper. Both manually constructed rules and machine learning based approaches are applied to compared the performances. The experimental results on 500 titles show that AE has an F-measure of 0.73 while MT has an F-measure of 0.6. With the extracted application environment and involved method/technology, users can then use visualization and OLAP tool to get a better view of the search results.
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