Research Article
A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking
@INPROCEEDINGS{10.4108/icst.iniscom.2015.258417, author={pijitra jomsri and Dulyawit Prangchumpol}, title={A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking}, proceedings={1st International Conference on Industrial Networks and Intelligent Systems}, publisher={EAI}, proceedings_a={INISCOM}, year={2015}, month={4}, keywords={- hybrid model ; research paper searching; social bookmarking}, doi={10.4108/icst.iniscom.2015.258417} }- pijitra jomsri
Dulyawit Prangchumpol
Year: 2015
A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking
INISCOM
ICST
DOI: 10.4108/icst.iniscom.2015.258417
Abstract
Social bookmarking and publication sharing systems are essential tools for web resource discovery. The performance and capabilities of search results from research paper bookmarking system are vital. Many researchers use social bookmarking for searching papers related to their topics of interest. This paper proposes a combination of similarity based indexing “tag title and abstract” and static ranking to improve search results. In this particular study, the year of the published paper and type of research paper publication are combined with similarity ranking called (HybridRank). Different weighting scores are employed. The retrieval performance of these weighted combination rankings are evaluated using mean values of NDCG. The results suggest that HybridRank and similarity rank with weight 75:25 has the highest NDCG scores. From the preliminary result of experiment, the combination ranking technique provide more relevant research paper search results. Furthermore the chosen heuristic ranking can improve the efficiency of research paper searching on social bookmarking websites.
