Abstract
The World Wide Web (WWW) is rapidly becoming important for society as a medium for sharing data, information, and services, and there is a growing interest in tools for understanding collective behavior and emerging phenomena in the WWW. In this article we focus on the problem of searching and classifying communities in the Web. Loosely speaking a community is a group of pages related to a common interest. More formally, communities have been associated in the computer science literature with the existence of a locally dense subgraph of the Web graph (where Web pages are nodes and hyperlinks are arcs of the Web graph). The core of our contribution is a new scalable algorithm for finding relatively dense subgraphs in massive graphs. We apply our algorithm on Web graphs built on three publicly available large crawls of the Web (with raw sizes up to 120M nodes and 1G arcs). The effectiveness of our algorithm in finding dense subgraphs is demonstrated experimentally by embedding artificial communities in the Web graph and counting how many of these are blindly found. Effectiveness increases with the size and density of the communities: it is close to 100% for communities of thirty nodes or more (even at low density). It is still about 80% even for communities of twenty nodes with density over 50% of the arcs present. At the lower extremes the algorithm catches 35% of dense communities made of ten nodes. We also develop some sufficient conditions for the detection of a community under some local graph models and not-too-restrictive hypotheses. We complete our Community Watch system by clustering the communities found in the Web graph into homogeneous groups by topic and labeling each group by representative keywords.
- Abello, J., Resende, M. G. C., and Sudarsky, S. 2002. Massive quasi-clique detection. In Proceedings of the Latin American Theoretical Informatics Symposium (LATIN). 598--612. Google Scholar
Digital Library
- Amitay, E., Carmel, D., Darlow, A., Lempel, R., and Soffer, A. 2003. The connectivity sonar: Detecting site functionality by structural patterns. In Proceedings of the 14th ACM Conference on Hypertext and Hypermedia (HYPERTEXT). 38--47. Google Scholar
Digital Library
- Bharat, K., Broder, A. Z., Dean, J., and Henzinger, M. R. 2000. A comparison of techniques to find mirrored hosts on the WWW. J. Amer. Soc. Inform. Sci. 51, 12, 1114--1122. Google Scholar
Digital Library
- Bianchini, M., Gori, M., and Scarselli, F. 2005. Inside pagerank. ACM Trans. Inter. Tech. 5, 1, 92--128. Google Scholar
Digital Library
- Boldi, P., Codenotti, B., Santini, M., and Vigna, S. 2004. Ubicrawler: A scalable fully distributed Web crawler. Softw. Prac. Exper. 34, 8, 711--726. Google Scholar
Digital Library
- Boldi, P. and Vigna, S. 2004. The Webgraph framework I: Compression techniques. In Proceedings of the 13th International Conference on the World Wide Web. 595--601. Google Scholar
Digital Library
- Broder, A., Kumar, R., Maghoul, F., Raghavan, P., Rajagopalan, S., Stata, R., Tomkins, A., and Wiener, J. 2000a. Graph structure in the Web. Comput. Netw. 33, 1-6, 309--320. Google Scholar
Digital Library
- Broder, A. Z., Charikar, M., Frieze, A. M., and Mitzenmacher, M. 2000b. Min-wise independent permutations. J. Comput. Syst. Sci. 60, 3, 630--659. Google Scholar
Digital Library
- Broder, A. Z., Glassman, S. C., Manasse, M. S., and Zweig, G. 1997. Syntactic clustering of the web. In Selected Papers from the 6th International Conference on the World Wide Web. Elsevier Science Publishers Ltd., Essex, UK, 1157--1166. Google Scholar
Digital Library
- Capocci, A., Servedio, V. D. P., Caldarelli, G., and Colaiori, F. 2004. Communities detection in large networks. In Proceedings of the Algorithms and Models for the Web graph (WAW'04): Third International Workshop. 181--188.Google Scholar
- Chakrabarti, S., Dom, B. E., Kumar, S. R., Raghavan, P., Rajagopalan, S., Tomkins, A., Gibson, D., and Kleinberg, J. 1999. Mining the link structure of the World Wide Web. Comput. 32, 8, 60--67. Google Scholar
Digital Library
- Cho, J. and Garcia-Molina, H. 2000. WebBase and the Stanford interlib project. In Proceedings of the Kyoto International Conference on Digital Libraries: Research and Practice.Google Scholar
- Cover, T. M. and Thomas, J. A. 1991. Elements of Information Theory. John Wiley and Sons. Google Scholar
Digital Library
- Dourisboure, Y., Geraci, F., and Pellegrini, M. 2007. Extraction and classification of dense communities in the web. In Proceedings of the 16th International Conference on the World Wide Web. ACM, New York, NY, 461--470. Google Scholar
Digital Library
- Fang, R., Mikroyannidis, A., and Theodoulidis, B. 2006. A voting method for the classification of web pages. In Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology—Workshops. IEEE Computer Society, 610--613. Google Scholar
Digital Library
- Feige, U. 2002. Relations between average case complexity and approximation complexity. In Proceedings of the ACM Symposium on Theory of Computing (STOC). Google Scholar
Digital Library
- Feige, U. and Langberg, M. 2001. Approximation algorithms for maximization problems arising in graph partitioning. J. Algor. 41, 174--211. Google Scholar
Digital Library
- Feige, U., Peleg, D., and Kortsarz, G. 2001. The dense k-subgraph problem. Algorithmica 29, 3, 410--421.Google Scholar
Digital Library
- Flake, G. W., Lawrence, S., and Giles, C. L. 2000. Efficient identification of Web communities. In Proceedings of the Conference on Knowledge Discovery in Data (KDD). ACM Press, New York, NY, 150--160. Google Scholar
Digital Library
- Flake, G. W., Lawrence, S., Giles, C. L., and Coetzee, F. 2002. Self-organization of the web and identification of communities. IEEE Comput. 35, 3, 66--71. Google Scholar
Digital Library
- Geraci, F., Pellegrini, M., Maggini, M., and Sebastiani, F. 2007. Cluster generation and labeling for web snippets:a fast, accurate hierarchical solution. Internet Math. 3, 4, 413--443.Google Scholar
Cross Ref
- Gibson, D., Kleinberg, J., and Raghavan, P. 1998. Inferring web communities from link topology. In Proceedings of the ninth ACM Conference on Hypertext and Hypermedia (HYPERTEXT). ACM Press, New York, NY, 225--234. Google Scholar
Digital Library
- Gibson, D., Kumar, R., and Tomkins, A. 2005. Discovering large dense subgraphs in massive graphs. In Proceedings of the International Conference on Very Large Databases (VLDB). VLDB Endowment, 721--732. Google Scholar
Digital Library
- Girvan, M. and Newman, M. E. J. 2002. Community structure in social and biological networks. Proceedings of the National Academic Science, 7821--7826.Google Scholar
- Glover, E. J., Tsioutsiouliklis, K., Lawrence, S., Pennock, D. M., and Flake, G. W. 2002. Using web structure for classifying and describing web pages. In Proceedings of the International Conference on the World Wide Web (WWW). 562--569. Google Scholar
Digital Library
- Gulli, A. and Signorini, A. 2005. The indexable web is more than 11.5 billion pages. In Proceedings of the 11th International Conference on the World Wide Web (WWW). Special Interest Tracks and Posters. 902--903. Google Scholar
Digital Library
- Gyöngyi, Z. and Garcia-Molina, H. 2005. Web spam taxonomy. In Proceedings of the 1st International Workshop on Adversarial Information Retrieval on the Web.Google Scholar
- Hastad, J. 1999. Clique is hard to approximate within n1−ε. Acta Mathematica 182, 105--142.Google Scholar
Cross Ref
- Haveliwala, T. H., Gionis, A., and Indyk, P. 2000. Scalable techniques for clustering the web. In Proceedings of the WebDB Workshop. 129--134.Google Scholar
- Henzinger, M. 2002. Algorithmic challenges in Web search engines. Internet Math. 1, 1, 115--126.Google Scholar
Cross Ref
- Imafuji, N. and Kitsuregawa, M. 2003. Finding a web community by maximum flow algorithm with HITS score based capacity. In Proceedings of the 8th International Conference on Database Systems for Advanced Applications (DASFAA). 101--106. Google Scholar
Digital Library
- Ino, H., Kudo, M., and Nakamura, A. 2005. Partitioning of Web graphs by community topology. In Proceedings of the International Conference on the World Wide Web (WWW). ACM Press, New York, NY, 661--669. Google Scholar
Digital Library
- Kautz, H., Selman, B., and Shah, M. 1997. Referral Web: Combining social networks and collaborative filtering. Comm. ACM 40, 3, 63--65. Google Scholar
Digital Library
- Kumar, R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 1999a. Extracting large-scale knowledge bases from the Web. In Proceedings of the International Conference on Very Large Databases (VLDB). 639--650. Google Scholar
Digital Library
- Kumar, R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 1999b. Trawling the Web for emerging cyber-communities. Comput. Netw. 31, 11--16, 1481--1493. Google Scholar
Digital Library
- Kumar, R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 2005. Method and system for trawling the world-wide Web to identify implicitly-defined communities of Web pages. US patent 6886129.Google Scholar
- Kumar, S. R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 1999c. Extracting large-scale knowledge bases from the Web. VLDB J. 639--650. Google Scholar
Digital Library
- Lempel, R. and Moran, S. 2000. The stochastic approach for link-structure analysis (SALSA) and the TKC effect. Comput. Netw. 33, 1--6, 387--401. Google Scholar
Digital Library
- Lindemann, C. and Littig, L. 2007. Classifying Web sites. In Proceedings of the 16th International Conference on World Wide Web (WWW). 1143--1144. Google Scholar
Digital Library
- Newman, M. 2003. The structure and function of complex networks. SIAM Rev. 45, 2, 167--256.Google Scholar
Digital Library
- Reddy, P. K. and Kitsuregawa, M. 2001. An approach to relate the web communities through bipartite graphs. In Proceedings of the International Conference on Web Information Systems Engineering (WISE). 301--310. Google Scholar
Digital Library
- Stamou, S., Ntoulas, A., Krikos, V., Kokosis, P., and Christodoulakis, D. 2006. Classifying web data in directory structures. In Frontiers of WWW Research and Development—APWeb, 8th Asia-Pacific Web Conference. Lecture Notes in Computer Science, vol. 3841. Springer, 238--249. Google Scholar
Digital Library
- Wu, B. and Davison, B. D. 2005. Identifying link farm spam pages. In Proceedings of the International Conference on World Wide Web (WWW). ACM Press, New York, NY, 820--829. Google Scholar
Digital Library
Index Terms
Extraction and classification of dense implicit communities in the Web graph
Recommendations
Extraction and classification of dense communities in the web
WWW '07: Proceedings of the 16th international conference on World Wide WebThe World Wide Web (WWW) is rapidly becoming important for society as a medium for sharing data, information and services, and there is a growing interest in tools for understanding collective behaviors and emerging phenomena in the WWW. In this paper ...
Extract and rank web communities
WIMS '13: Proceedings of the 3rd International Conference on Web Intelligence, Mining and SemanticsA web community is a pattern in the WWW which is understood as a set of related web pages. In this paper, we propose an efficient algorithm to find the web communities on a given specific topic. Instead of working on the whole web graph, we work on a ...
Graph structure in the web: aggregated by pay-level domain
WebSci '14: Proceedings of the 2014 ACM conference on Web sciencePrevious research on the overall graph structure of the World Wide Web mostly focused on the page level, meaning that the graph that directly results from hyperlinks between individual web pages was analyzed. This paper aims to provide additional ...






Comments