It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
The index is crucial for information retrieval efficiency. Different with text data, tagged data contained rich semantics, which is useful to promote the quality of search results. It is observed that most existing indexes for keyword search do not consider semantics of tags. After an analysis of tagged data, we proposed the concept of result entity basing on the theory of relational database. We present a formula to quantify semantics of tags and then introduce a novel semantic index for keyword search. Experimental results demonstrated that our approach can help to reduce the size of the keyword inverted list in tagged document dramatically and improve the retrieval quality.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
1 School of Science and Technology, Zhejiang International Studies University, Hangzhou 310012, China
2 Zhejiang Province E-commerce Promotion Centre, Hangzhou 311100, China