Abstract
Association Link Network (ALN) is a kind of Semantic Link Network built by mining the association relations among multimedia Web resources for effectively supporting Web intelligent application such as Web-based learning, and semantic search. This paper explores the Small-World properties of ALN to provide theoretical support for association learning (i.e., a simple idea of “learning from Web resources”). First, a filtering algorithm of ALN is proposed to generate the filtered status of ALN, aiming to observe the Small-World properties of ALN at given network size and filtering parameter. Comparison of the Small-World properties between ALN and random graph shows that ALN reveals prominent Small-World characteristic. Then, we investigate the evolution of Small-World properties over time at several incremental network sizes. The average path length of ALN scales with the network size, while clustering coefficient of ALN is independent of the network size. And we find that ALN has smaller average path length and higher clustering coefficient than WWW at the same network size and network average degree. After that, based on the Small-World characteristic of ALN, we present an Association Learning Model (ALM), which can efficiently provide association learning of Web resources in breadth or depth for learners.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Adamic, L.-A.: The small world Web. In Lecture Notes in Computer Science. Springer, New York, 1696, 443–454 (1999)
Albert, R., Barabási, A.-L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74(1), 48–97 (2002)
Albert, R., Jeong, H., Barabási, A.-L.: Diameter of the world-wide Web. Nature 401, 130–131 (1999)
Andrei, B., Ravi, K., Farzin, M.: Graph structure in the Web. Comput. Network 33, 309–320 (2000)
Brin, S., Page, L.: The anatomy of a large scale hyper textual Web search engine. In: Proc. 7th WWW, (1998)
Cao, J., Wang, J., Law, K., Zhang, S., Li, M.: An interactive service customization model. J. Inform. Software Tech. 48(4), 280–296 (2006)
Chakrabarti, S., Dom, B., Gibson, D. et al.: Automatic resource compilation by analyzing hyperlink structure and associated text. In: Proc. 7th WWW, (1998)
Chang, H.P., Shih, Tk, Li, Q., Wang, C.C., Wang, T.H., Chao, L.R.: An adaptive caching strategy for m-learning based on SCORM sequencing and navigation. World Wide Web 11(3), 387–406 (2008)
Chen, J., Li, Q., Jia, W.: Automatically generating an E-textbook on the web. World Wide Web 8, 377–394 (2005)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1, 269–271 (1959)
Fronczak, A., Fronczak, P., Hołyst, J.A.: Average path length in random networks. Phys. Rev. E 70, 056110-1–056110-7 (2004)
Hoser, B., Hotho, A., Jäschke, R. et al.: Semantic network analysis of ontologies. Third European Semantic Web Conf., (2006)
Kim, H.-M., Biehl, M.: Exploiting the small-worlds of the semantic web to connect heterogeneous, local ontologies. Inform. Tech. Manag. 6, 89–96 (2005)
Lau, R.W.H., Si, A., Kam, L.: Personalized hierarchical organization of web documents. J. Internet Technol. 2(4), 253–261 (2001)
Li, F., Lau, R.: Emerging technologies and applications on interactive entertainments. J. Multimed. 6(2), 107–114 (2011)
Li, Q., Lau, R.W.H., Shih, T.K., et al.: Technology supports for distributed and collaborative learning over the internet. ACM Transactions on Internet Technology, 8(2), 10:1–10:24 (2008)
Li, Q., Zhao, J., Zhu, X.: Multimedia data modeling through a semantic view mechanism. World Wide Web 11(2), 287–311 (2008)
Luo, X.F., Fang, N., et al.: Semantic representation of scientific documents for the e-science Knowledge Grid. Concurrency Comput. Pract. Exp. 20(7), 839–862 (2008)
Luo, X.F., Xu, Zh, Yu, J., et al.: Building association link network for semantic link on web resources. IEEE Trans. Autom. Sci. Eng. 8(3), 482–494 (2011)
Luo, X.F., Zhang, J., Liu, F.F., et al.: Merging textual knowledge represented by element fuzzy cognitive maps. J. Softw. 5(2), 225–234 (2010)
Milgram, S.: The small-world problem. Psychol. Today 1(1), 61–67 (1967)
Moxley, E., Tao, M., Manjunath, B.S.: Video annotation through search and graph reinforcement mining. IEEE Trans. Multimed. 12(3), 184–193 (2010)
Newman, M.E.J.: The structure and function of complex networks. SIAM Rev. 45, 167–256 (2003)
Ng, B., Li, F., Lau, R., Si, A., Siu, A.: A performance study on multi-server DVE systems. Inform. Sci. 154, 85–93 (2003)
Song, Y., Wang, W., Zhang, A.: Automatic annotation and retrieval of images. World Wide Web 6(2), 209–231 (2003)
Stamou, G., van Ossenbruggen, J., Pan, J.Z., Schreiber, G., Smith, J.R.: Multimedia annotations on the semantic web. IEEE Multimed. 13(1), 86–90 (2006)
Wang, G.R., Yuan, Y., Sun, Y.J., Xin, J.C., Zhang, Y.: PeerLearning: a content-based e-learning material sharing system based on P2P network. World Wide Web 13(3), 275–305 (2010)
Watts, D.J., Strogatz, S.H.: Collective dynamics of “Small-World” networks. Nature 393, 440–442 (1998)
Yen, N.Y., Shih, T.K., Jin, Q., et al.: Adaptive object re-ranking mechanism for ubiquitous learning environment. J. Multimed. 6(2), 129–138 (2011)
Zhang, S.X., Luo, X.F., Xuan, J.Y., Chen, X., Xu, W.M.: Discovering small-world in association link networks for web-based learning, MTDL’11, 19–24 (2011)
Zhang, Zh., Chen, L., Zhou, Sh., et al.: Analytical solution of average path length for Apollonian networks. Phys. Rev. E 77, 017102-1–017102-4 (2008)
Zhuge, H.: Communities and emerging semantics in semantic link network: discovery and learning. IEEE Trans. Knowl. Data Eng. 21(6), 785–799 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, S., Luo, X., Xuan, J. et al. Discovering small-world in association link networks for association learning. World Wide Web 17, 229–254 (2014). https://doi.org/10.1007/s11280-012-0171-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11280-012-0171-7