Abstract
Keyword-based information retrieval finds webpages with queries composed of keywords to provide users with needed information. However, since the keywords are only a part of the necessary information, it may be hard to search intended results from the keyword-based methods. Furthermore, users should make efforts to select proper keywords many times in general because they cannot know which keyword is effective in obtaining meaningful information they really want. In this paper, we propose a novel algorithm, called PQ_Rank, which can find intended webpages more exactly than the existing keyword-based ones. To rank webpages more effectively, it considers not only keywords but also all of the words included in webpages, named page queries. Experimental results show that PQ_Rank outperforms PageRank, a famous algorithm used by Google, in terms of MAP, average recall, and NDCG.
This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF No. 2013005682 and 20080062611).
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Pyun, G., Yun, U. (2014). A Novel Ranking Technique Based on Page Queries. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_1
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DOI: https://doi.org/10.1007/978-3-642-40675-1_1
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