Research Academic Computer Technology Institute (RACTI) Patras Greece1 An Algorithmic Framework for Adaptive Web Content Christos Makris, Yannis Panagis,

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Research Academic Computer Technology Institute (RACTI) Patras Greece1 An Algorithmic Framework for Adaptive Web Content Christos Makris, Yannis Panagis, Evangelos Sakkopoulos and Athanasios Tsakalidis

Research Academic Computer Technology Institute (RACTI) Patras Greece2 The unprecedented growth of the Internet usage, websites are being developed in an uncontrollable, ad-hoc manner, a fact frequently reflected to unpredictable visit patterns. Thus, a critical task for a website maintainer is to use enumerable metrics in order to identify substructures of the site that are objectively popular. Web Usage Mining has emerged as a method to assist such a task. The fundamental basis for all mining operations entails processing web server access logfiles Introduction

Research Academic Computer Technology Institute (RACTI) Patras Greece3 This work contributes two main approaches: it presents initial results using an optimal offline site adaptation – reorganization approach based on a set of different popularity metrics and, additionally, it presents an online personalization mechanism to display the most “hot” -popular and recent – site subgraphs in a recommendation list adaptive to the users’ individual preferences. Both approaches build on well-known results in data structures in the areas of optimal trees and adaptive data structures. Contribution

Research Academic Computer Technology Institute (RACTI) Patras Greece4 To receive web usage feedback, web sites have been accompanied with logging mechanisms that have been evolving over time A shift to Java servlets, PHP and Microsoft.NET. URL re-writing, HTML server-side pre-rendering or pre-compilation, client-side code injection and custom logging databases are utilized Background

Research Academic Computer Technology Institute (RACTI) Patras Greece5 Absolute: Absolute Accesses (AAi) to a specific page i of a site Relative: Hence, a i incorporates topological information, namely page depth within site d i, the number of pages at the same depth n i and the number of pages within site pointing to it r i. Thus a i = d i + n i /r i. Spatial: First accesses originating from the site (neighboring pages), second directly via bookmarks stored at a client browser third by incoming links from the outside world Metrics (1)

Research Academic Computer Technology Institute (RACTI) Patras Greece6 Routed: the idea was to increase page relative weight, inversely proportional to its access probability; Metrics (2)

Research Academic Computer Technology Institute (RACTI) Patras Greece7 The mechanism scans the website graph in order to keep only the non-intersecting subpaths. Suppose that the site is modelled as a graph G(V,E) kept in an adjacency matrix representa­tion, with matrix A. After the completion of the identification of “Maximal Forward Paths”, the website access sequences (paths) are kept Paths

Research Academic Computer Technology Institute (RACTI) Patras Greece8 Algorithms for organizing web content according to mined access patterns: the offline, uses computed importance weights, to optimally reorganize the structure of a website so that it minimizes the navigation entropy. the online, adapts the page presentation after each visit to a certain page Re-Organize

Research Academic Computer Technology Institute (RACTI) Patras Greece9 We assume that we work on a set of website elements, single web pages or website components, each of which has been assigned a unique number (BFS, DFS) and a normalized popularity metric (trivial frequency or normalized probability distribution of objects) Prerequisitives

Research Academic Computer Technology Institute (RACTI) Patras Greece10 Offline case

Research Academic Computer Technology Institute (RACTI) Patras Greece11 Online case The previous approach was static in the sense that access results are gathered after a period of observation, access metrics are computed and then restructuring is performed A simple and elegant strategy to achieve this goal, without even the need to know the specific popularity of certain web elements, is to use an adaptive data structure. In the following we constrain for the sake of clarity our discussion to web pages.

Research Academic Computer Technology Institute (RACTI) Patras Greece12 Online case (2) The data structure that can be used is the adaptive list. The adaptive list is a doubly-connected list of unordered items. Each time an item is accessed, it is brought to the front (left end) of the list. This adaptation rule is called Move-to-Front. In a possible implementation we can present users the leftmost k elements of the list, where k is a predefined constant. This amounts to presenting user with the k pages that she is most likely to visit in the future.

Research Academic Computer Technology Institute (RACTI) Patras Greece13 Conclusions and Future Work Initial results has shown encouraging results on the implementation of the presented techniques in laboratory web sites and application. Additional experiments are currently conducted in order to strengthen our approach. Future steps include the description of a framework that it would evaluate the combination of reorganization metrics with different sets of redesign proposals. We also consider as open issue the definition of an overall website grading method that would quantify the quality

Research Academic Computer Technology Institute (RACTI) Patras Greece14 Thank You for Your Attention! Do not hesitate to contact me for any extra details at: