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A survey of Web metrics
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Volume 34 ,  Issue 4  (December 2002) table of contents
Pages: 469 - 503  
Year of Publication: 2002
ISSN:0360-0300
Authors
Devanshu Dhyani  Nanyang Technological University, Singapore, Singapore
Wee Keong Ng  Nanyang Technological University, Singapore, Singapore
Sourav S. Bhowmick  Nanyang Technological University, Singapore, Singapore
Publisher
ACM  New York, NY, USA
Bibliometrics
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ABSTRACT

The unabated growth and increasing significance of the World Wide Web has resulted in a flurry of research activity to improve its capacity for serving information more effectively. But at the heart of these efforts lie implicit assumptions about "quality" and "usefulness" of Web resources and services. This observation points towards measurements and models that quantify various attributes of web sites. The science of measuring all aspects of information, especially its storage and retrieval or informetrics has interested information scientists for decades before the existence of the Web. Is Web informetrics any different, or is it just an application of classical informetrics to a new medium? In this article, we examine this issue by classifying and discussing a wide ranging set of Web metrics. We present the origins, measurement functions, formulations and comparisons of well-known Web metrics for quantifying Web graph properties, Web page significance, Web page similarity, search and retrieval, usage characterization and information theoretic properties. We also discuss how these metrics can be applied for improving Web information access and use.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Albert, R. and Barabasi, A. 2000. Topology of evolving networks: Local events and uncertainty. Phys. Rev. Lett. 84, 56--60.
 
2
Albert, R., Jeong, H., and Barabasi, A. 1999. The diameter of the world wide web. Nature 401, 130--131.
 
3
Barabasi, A. and Albert, R. 1999. Emergence of scaling in random networks. Science 286 (Oct.), 509--512.
 
4
Barabasi, A., Albert, R., and Jeong, A. 1999. Mean-field theory for scale free random networks. Phys. A 272, 173--187.
 
5
Barabasi, A., Albert, R., and Jeong, J. 2000. Scale-free characteristics of random networks: The topology of the world wide web. Phys. A, 281, 69--77.
 
6
 
7
 
8
 
9
 
10
Boyce, B. R., Meadow, C. T., and Kraft, D. H. 1994. Measurement in Information Science. Academic Press Inc. Orlando, Fla.
 
11
12
13
 
14
 
15
 
16
Chakrabarti, S., Dom, B., Gibson, D., Kumar, R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 1998a. Experiments in topic distillation. In Proceedings of the SIGIR Workshop on Hypertext IR.
 
17
 
18
 
19
 
20
 
21
Dhyani, D. 2001. Measuring the web: Metrics, models and methods. Master's Dissertation, School of Computer Engineering, Nanyang Technological University, Singapore.
 
22
Egghe, L. and Rousseau, R. 1990. Introduction to Informetrics. Elsevier Science Publishers. Amsterdam, The Netherlands.
23
 
24
 
25
 
26
 
27
Kleinberg, J., Kumar, R., Raghavan, P., Rajagopalan, S., and Tomkins, A. 1999. The web as a graph: Measurements, models, and methods. In Proceedings of the 5th International Conference on Computing and Combinatorics (COCOON).
 
28
 
29
Larson, R. 1996. Bibliometrics of the world wide web: An exploratory analysis of the intellectual structure of cyberspace. In Annual Meeting of the American Society of Information Science.
 
30
Lawrence, S. and Giles, C. L. 1998. Searching the world wide web. Science 280 (Apr.).
 
31
Lawrence, S. and Giles, C. L. 1999. Searching the web: General and scientific information access. IEEE Commun. 37, 1, 116--122.
 
32
 
33
34
 
35
 
36
Montgomery, D. C. and Runger, G. C. 1994. Applied Statistics and Probability for Engineers. Wiley, New York.
 
37
Murray, B. H. and Moore, A. 2000. Sizing the internet. White paper. Available from http:// www.cyveillance.com/web/us/downloads/Sizing_the_Internet.pdf (July).
 
38
Perkowitz, M. and Etzioni, O. 1997. Adaptive web sites: An AI challenge. In Proceedings of the 15th International Joint Conference on Artificial Intelligence.
 
39
 
40
41
 
42
43
 
44
45
 
46
Ross, S. 1983. Stochastic Processes. Wiley, New York.
 
47
Selberg, E. and Etzioni, O. 1995. Multi-service search and comparison using the MetaCrawler. In Proceedings of the 4th International World Wide Web Conference.
 
48
 
49
Snell, L. 1998. Introduction to Probability. McGraw-Hill International Edition, Englewood Cliffs, N.J.
50
 
51
 
52
 
53
Yuwono, B., Lam, S., Ying, J., and Lee, D. 1995. A world wide web resource discovery system. In Proceedings of the 4th International World Wide Web Conference.

CITED BY  29

Collaborative Colleagues:
Devanshu Dhyani: colleagues
Wee Keong Ng: colleagues
Sourav S. Bhowmick: colleagues