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TOWARDS ADAPTIVE WEBSITES: A CONCEPTUAL FRAMEWORK
AND CASE STUDY
Department of Computer Science, November 2005
Presented by
Akash Y Shindhe
AGENDA Introduction
Motivation What are Adaptive Websites? Approaches to Adaptation The Index Page Synthesis Use Case
The PageGather Algorithm Description of The Algorithm Experimental Method Time Complexity Comparison with Related Algorithms
Conclusions Related Work Summary Resources
MOTIVATION
Designing a complex web site so it readily yields its information is tricky, because:1. Different visitors have distinct goals2. Same user may seek different information at different
times3. Many sites outgrow their original design, accumulating
links and pages in unlikely places4. A site may be designed for a particular use, but may be
used in unanticipated ways in practice
Too often, web sites are fossils cast in HTML, while web navigation is dynamic, time-dependent, and idiosyncratic
WHAT ARE ADAPTIVE WEBSITES?Adaptive websites are sites that
automatically improve their organization and presentation by learning from visitor access patterns
They mine the data buried in web server logs to produce more easily navigable websites
To demonstrate the feasibility of adaptive websites, the index page synthesis use case is considered
APPROACHES TO ADAPTATION Aim is to make a website “better”, so we need
a clear quality measure Quality measure as a function of variables:
How often users find what they are looking for How many clicks users have to make to get to their
goal How much time users spend reading link text and
scrolling through pages Two approaches to adaptation:
Content-based : organizes and presents pages based on their content.
Access-based : uses the way past visitors have interacted with the site to guide how information is structured.
Content-based and access-based adaptations are complementary and may be used together
THE INDEX PAGE SYNTHESIS CASE STUDY (1)
Page synthesis is the automatic creation of web pages
An index page is a page consisting of links to a set of pages that cover a particular topic
Index page synthesis problem: given a web site and a visitor access log, create new index pages containing collections of links to related but currently unlinked pages
THE INDEX PAGE SYNTHESIS CASE STUDY (2)
The Index Page Synthesis Problem:1. What are the contents (i.e. hyperlinks) of the
index page?2. How are the hyperlinks on the page ordered?3. How are the hyperlinks labeled?4. What is the title of the page? Does it
correspond to a coherent concept?5. Is it appropriate to add the page to the site?
If so, where?
SOLUTIONS
2 Algorithms have been suggested by the authors of the paper
PageGatherIndexFinder
THE PAGEGATHER ALGORITHM
1. The PageGather algorithm is a statistical cluster mining algorithm
2. Clustering algorithms take a collection of objects as their input and produce a partition of the collection
3. Cluster mining is a variation on traditional clustering that may place a single object in multiple overlapping clusters
4. PageGather uses cluster mining to find collections of related pages at a website
DESCRIPTION OF PAGEGATHER
1. Process the access log into visits2. Compute the co-occurrence frequencies
between pages and create a similarity matrix
3. Create the graph corresponding to the matrix, and find maximal cliques (or connected components) in the graph
4. Rank the clusters found, and choose which to output
5. Eliminate overlap among the clusters6. Present it to the webmaster for evaluation
TIME COMPLEXITY What is the running time of PageGather? Let L be the number of page views in the log
and N the number of pages at the site Step (1) requires O(L log L) time: page views
must be sorted by origin and time Step (2) requires O(L + N2) time: must process
the log and create a matrix of size O(N2) In step (3) we may find either connected
components (linear in the size of the graph) or cliques (exponential in general, but since size of discovered clusters is bound to k, this step is a polynomial of degree k)
COMPARISON WITH RELATED ALGORITHMS
PageGather significantly outperforms other statistical clustering algorithms, but is not as well as human-authored clusters
IMPLEMENTATIONS And More:
Use both user’s path and model to guess what pages they are interested in seeing e.g., AVANTI Project [1]
Automatic user categorization Hybrid approach Footprints [2] uses the metaphor of travellers creating
footpaths in the grass over time Using meta-information e.g., XML, Apple’s Meta-
Content Format, STRUDEL [3] Client-side customization
CONCLUSIONS (1)
PageGather and IndexFinder outperform traditional methods including: the Apriori data mining algorithm, standard clustering algorithms and the COBWEB conceptual clustering algorithm
PageGather and IndexFinder are instances of novel, domain-independent approaches to unsupervised data mining
Extensions and applications to these approaches outside the domain of adaptive websites can be found
CONCLUSIONS (2)
Future work may focus on the automatic placement of new index pages at the website
Automatically suggesting names for the new pages, and deciding where in the site they should be located
Index page synthesis itself is a step towards the long-term goal of change in view: adaptive websites that automatically suggest re-organisations of their contents based on visitor access patterns
RELATED WORK By the authors:
Mainly updates to the original paper (most recent one in 2001)
By others:Adaplix [5] : A system that extends HTML
by introducing conditional statements and an inductive logic programming component to learn the user's browsing preferences
WebWatcher [6]: A “tour guide” of the web. It accompanies the user from page to page, highlighting hyperlinks that it believes will be of interest
SUMMARY
We have covered: Adaptive Websites The Index Page Synthesis Use Case The PageGather Algorithm The IndexFinder Algorithm Implementations Related Work
ANY QUESTIONS?
RESOURCES [1] J. Fink, A Kobsa, and A. Nill.
User-oriented Adaptivity and Adaptability in the AVANTI Project. In Designing for the Web: Empirical Studies, Microsoft Usability Group, Redmond (WA)., 1996.
[2] A. Wexelblat and P. Maes. Footprints: History-rich web browsing. In Proc. Conf. Computer-Assisted Information Retrieval (RIAO), pages 75-84, 1997.
• [3] M. Fernandez, D. Florescu, J. Kang, A. Levy, and D. Suciu. System Demonstration - Strudel: A Web-site Management System. In ACM SIGMOD Conference on Management of Data, 1997.
[4] D. Fisher. Knowledge Acquisition Via Incremental Conceptual Clustering. Machine Learning, 2:139-172, 1987
[5] Nico Jacobs. Adaplix: Towards Adaptive Websites. In P. De Bra and L. Hardman, editors, Proceedings van de Informatiewetenschap'99 Conferentie, pages 22--28. Eindhoven University of Technology, November 1999
[6] URL : http://www.cs.cmu.edu/~webwatcher, accessed on 22 November 2005