Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32119
A Combination of Similarity Ranking and Time for Social Research Paper Searching

Authors: P. Jomsri


Nowadays social media are important tools for web resource discovery. The performance and capabilities of web searches are vital, especially search results from social research paper bookmarking. This paper proposes a new algorithm for ranking method that is a combination of similarity ranking with paper posted time or CSTRank. The paper posted time is static ranking for improving search results. For this particular study, the paper posted time is combined with similarity ranking to produce a better ranking than other methods such as similarity ranking or SimRank. The retrieval performance of combination rankings is evaluated using mean values of NDCG. The evaluation in the experiments implies that the chosen CSTRank ranking by using weight score at ratio 90:10 can improve the efficiency of research paper searching on social bookmarking websites.

Keywords: combination ranking, information retrieval, time, similarity ranking, static ranking, weight score

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1525


[1] CiteULike,
[2] Connotea,
[3] BibSonomy,
[4] Flickr,
[5] Delicious,
[6] P.Jomsri, S. Sanguansintukul, W. Choochaiwattana, "Improve Research paper Searching with social tagging-A Preliminary Investigation," in the Eight International Symposium on Natural Language Processing, Thailand, 2009,pp.152-156.
[7] P.Jomsri, S. Sanguansintukul, W. Choochaiwattana, "A Comparison of Search Engine Using "Tag Title and Abstract" with CiteULike - An Initial Evaluation," in the 4th IEEE Int. Conf. for Internet Technology and Secured Transactions (ICITST-2009),United Kingdom,2009.
[8] A. Capocci, and G.Caldarelli, "Folksonomies and Clustering in the Collaborative System CiteULike," arXiv Press, eprint No. 0710.2835, 2007.
[9] U. Farooq, T.G. Kannampallil, Y. Song, C.H. Ganoe, M.C., John, L. Giles, "Evalating Tagging Behavior in Social Bookmarking Systems: Metrics and design heuristics," in Proc. of the 2007 international ACM conference on Supporting group work (GROUP-07), Sanibel Island, Florida, USA, 2007,pp.351-360.
[10] T. Bogers, and A. van den Bosch, "Recommending Scientific Articles Using CiteULike," in Proc. of the 2008 ACM conference on Recommender systems(RecSys-08), Switzerland,2008 ,pp.287-290.
[11] E. Santos-Neto, M. Ripeanu, and A. Iamnitchi, " Tracking usage in collaborative tagging communities".
[12] K. Berberich, M. Vazirgiannis, , and G. Weikum, " T-Rank: Time- Aware Authority Ranking," in WAW 2004.
[13] N. Craswell ,S. Robertson, H. Zaragoza, ,and M. Taylor, "Relevance weighting for query independent evidence," in Proc.of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, Salvador, Brazil,2005.
[14] U. Farooq, C.H. Ganoe, , J.M. Carroll, and C.L. Giles, "Supporting distributed scientific collaboration: Implications fordesigning the CiteSeer collaborator," in IEEE Proc. of the Hawaii Int-l Conference on System Sciences, Waikoloa, Hawaii,2007.
[15] S. Bao, X. Wu, B. Fei, G. Z. Xue, and Y. Yu, "Optimizing Web Search Using Social Annotations," in Proc. of the 16th international conference on World Wide Web (www2007), New York, USA,2007.
[16] A. Mohammad Zareh Bidoki , P. Ghodsnia, N. Yazdani, and F. Oroumchian, "A3CRank: An adaptive ranking method based on connectivity, content and click-through data", J. Information Processing and Management, Vol. 46, pp.159ÔÇö169, 2010.
[17] Y. Sun, and C. Lee Giles, "Popularity Weighted Ranking for Academic Digital Libraries," in ECIR 2007, LNCS 4425, pp. 605-612, 2007.
[18] P. Heymann, G. Koutrika, and H. Garcia-Molina, "Can social bookmarking improve web search?," in WSDM -08: Proc. of the International Conference on Web Search and Web Data Mining, New York, NY, USA. 2008,pp. 195-206.
[19] A. Hotho, R. Jäschke, C. Schmitz, and G. Stumme, "Information retrieval in folksonomies: search and ranking," in The Semantic Web: Research and Applications, ,2006 ,pp. 411-426.
[20] Y. Yanbe, A. Jatowt, S. Nakamura, and K. Tanaka, "Can social bookmarking enhance search in the web?," in JCDL -07: Proc. of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, New York, NY, USA ,2007 ,pp. 107-116,.
[21] D. Carmel , H. Roitman, and E. Yom-Tov, "Social bookmark weighting for search and recommendation," in The VLDB J., vol.19,pp 761-775, December 2010.
[22] M. Richardson, A. Prakash, and E. Brill, "Beyond PageRank: Machine Learning for Static Ranking," in Proc. of the 15th international conference on World Wide Web, Edinburgh, Scotland (2006).
[23] Z. Dou, R. Song, and J.-R. Wen, "A large-scale evaluation and analysis of personalized search strategies," in Proc. of the 16th international conference on World Wide Web, 2007.
[24] K. Jarvelin, , and J. Kekalainen, "IR evaluation methods for retrieving highly relevant documents," in Proc. of the International World Wide Web ,2006.
[25] E. Hatcher, and O. Gospodnetic, "Lucene in Action," Manning Publications Co., United States of America 2006.
[26] R. Baeza-Yates, and B. Ribeiro-Neto, "Modern information retrieval," ACM Press/Addison-Wesley.