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Issue No.12 - December (2010 vol.22)
pp: 1803-1808
Vagelis Hristidis , Florida International University, Miami
Yannis Papakonstantinou , University of California-San Diego, La Jolla
Ramakrishna Varadarajan , University of Wisconsin-Madison
Authority flow and proximity search have been used extensively in measuring the association between entities in data graphs, ranging from the web to relational and XML databases. These two ranking factors have been used and studied separately in the past. In addition to their semantic differences, a key advantage of proximity search is the existence of efficient execution algorithms. In contrast, due to the complexity of calculating the authority flow, current systems only use precomputed authority flows in runtime. This limitation prohibits authority flow to be used more effectively as a ranking factor. In this paper, we present a comparative analysis of the two ranking factors. We present an efficient approximation of authority flow based on proximity search. We analytically estimate the approximation error and how this affects the ranking of the results of a query.
Database searching, approximation methods, algorithms.
Vagelis Hristidis, Yannis Papakonstantinou, Ramakrishna Varadarajan, "Using Proximity Search to Estimate Authority Flow", IEEE Transactions on Knowledge & Data Engineering, vol.22, no. 12, pp. 1803-1808, December 2010, doi:10.1109/TKDE.2010.127
[1] S. Agrawal, S. Chaudhuri, and G. Das, "DBXplorer: A System for Keyword-Based Search over Relational Databases," Proc. Int'l Conf. Data Eng. (ICDE), 2002.
[2] A. Balmin, V. Hristidis, and Y. Papakonstantinou, "ObjectRank: Authority-Based Keyword Search in Databases," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2004.
[3] G. Bhalotia, C. Nakhey, A. Hulgeri, S. Chakrabarti, and S. Sudarshan, "Keyword Searching and Browsing in Databases Using BANKS," Proc. Int'l Conf. Data Eng. (ICDE), 2002.
[4] S. Brin and L. Page, "The Anatomy of a Large-Scale Hypertextual Web Search Engine," Proc. Int'l World Wide Web (WWW) Conf., 1998.
[5] Y. Chen, Q. Gan, and T. Suel, "I/O-Efficient Techniques for Computing PageRank," Proc. ACM Int'l Conf. Information and Knowledge Management (CIKM), 2002.
[6] R. Fagin, R. Kumar, and D. Shivakumar, "Comparing Top k Lists," Proc. ACM-SIAM Symp. Discrete Algorithms (SODA), 2003.
[7] C. Faloutsos, K.S. McCurley, and A. Tomkins, "Fast Discovery of Connection Subgraphs," Proc. ACM SIGKDD, 2004.
[8] D. Fogaras, B. Racz, K. Csalogany, and T. Sarlos, "Towards Scaling Fully Personalized PageRank: Algorithms, and Lower Bounds, Experiments," Internet Math., vol. 2, no. 3, pp. 333-358, 2005.
[9] R. Goldman, N. Shivakumar, S. Venkatasubramanian, and H. Garcia-Molina, "Proximity Search in Databases," Proc. Int'l Conf. Very Large Data Bases (VLDB), 1998.
[10] T. Haveliwala, "Efficient Computation of PageRank," technical report, Stanford Univ., , 1999.
[11] T. Haveliwala and S. Kamvar, "The Second Eigenvalue of the Google Matrix," technical report, Stanford Univ., 2003.
[12] V. Hristidis, H. Hwang, and Y. Papakonstantinou, "Authority-Based Keyword Search in Databases," ACM Trans. Database Systems, vol. 33, no. 1, pp. 1:1-1:40, 2008.
[13] V. Hristidis and Y. Papakonstantinou, "DISCOVER: Keyword Search in Relational Databases," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2002.
[14] V. Hristidis, Y. Papakonstantinou, and A. Balmin, "Keyword Proximity Search on XML Graphs," Proc. Int'l Conf. Data Eng. (ICDE), 2003.
[15] J.H. Wilkinson, The Algebraic Eigenvalue Problem. Oxford Univ. Press, 1965.
[16] G. Jeh and J. Widom, "Scaling Personalized Web Search," Proc. Int'l World Wide Web (WWW) Conf., 2003.
[17] V. Kacholia, S. Pandit, S. Chakrabarti, S. Sudarshan, R. Desai, and H. Karambelkar, "Bidirectional Expansion for Keyword Search on Graph Databases," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2005.
[18] S. Kamvar, T. Haveliwala, C. Manning, and G. Golub, "Extrapolation Methods for Accelerating PageRank Computations," Proc. Int'l World Wide Web (WWW) Conf., 2003.
[19] B. Kimelfeld and Y. Sagiv, "Finding and Approximating Top-k Answers in Keyword Proximity Search," Proc. ACM SIGACT-SIGMOD-SIGART Symp. Principles of Database Systems (PODS), 2006.
[20] Y. Koren, S.C. North, and C. Volinsky, "Measuring and Extracting Proximity in Networks," Proc. ACM SIGKDD, 2006.
[21] G. Reich and P. Widmayer, Beyond Steiner's Problem: A VLSI Oriented Generalization. Springer, 1989.
[22] H. Tong, C. Faloutsos, and J.-Y. Pan, "Fast Random Walk with Restart and Its Applications," Proc. Int'l Conf. Data Mining (ICDM), 2006.
[23] R. Varadarajan, V. Hristidis, and T. Li, "Beyond Single-Page Web Search Results," IEEE Trans. Knowledge and Data Eng., vol. 20, no. 3, pp. 411-424, Mar. 2008.
[24] R. Varadarajan, V. Hristidis, and L. Raschid, "Explaining and Reformulating Authority Flow Queries," Proc. Int'l Conf. Data Eng. (ICDE), 2008.
[25] Y. Wu and L. Raschid, "ApproxRank: Estimating Rank for a Subgraph," Proc. Int'l Conf. Data Eng. (ICDE), 2009.
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