International Workshop on Web Dynamics

(In conjunction with the 8th International Conference on Database Theory)

London, UK, 3 January 2001

Workshop Programme

The workshop will be held in the Senate House of the University of London.

On arrival on the morning of 3rd January, please come to the WebDyn registration desk which will be located on the ground floor of the Senate House.

8:30--9:00 Registration
9:00--9:15 Welcome
Invited Talk
9.15--10.15
Soumen Chakrabarti
Indian Institute of Technology, Bombay (abstract)
10:15--10:45 Coffee
10:45--12.15 A Web Site Navigation Engine (demo)
Mark Levene, Richard Wheeldon, Jon Bitmead
Toward a Structured Information Retrieval System on the Web:
Automatic Structure Extraction of Web Pages

Mathias Gery, Jean-Pierre Chevallet
Learning of Ontologies from the Web: the Analysis of Existent Approaches
Borys Omelayenko
12:15--1:10 Lunch
Invited Talk
1.00--2.00
Knut Magne Risvik, R&D Director Search Technology
Fast Search & Transfer ASA (abstract)
2:00--2:30 An Active Web-based Distributed Database System for E-Commerce
Hiroshi Ishikawa, Manabu Ohta
2:30--3:00 Coffee
Invited Talk
3.00--4.00
Luca Cardelli, Microsoft Research, Cambridge
Logics for Mobility (abstract)
4.15--5.15 A Probabilistic Approach to Model Adaptive Hypermedia Systems
Mario Cannataro, A.Cuzzocrea, Andrea Pugliese
Run-time Management Policies for Data Intensive Web sites
Christos Bouras, Agisilaos Konidaris
5.15 Discussion/Close
7:00 Meet for dinner at Chutney's Vegetarian/Vegan Indian Restaurant (optional!),
124 Drummond Street, London NW1 2PA


Also accepted to the workshop but not presented: Dynamics of Web Rings, Sebastian M. Maurer, Bernardo A. Huberman, Eytan Adar

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Abstracts of the Accepted Papers

Dynamics of Web Rings (not presented)
Sebastian M. Maurer, Bernardo A. Huberman, Eytan Adar

We present a theory of surfing in web rings, common link structures observed on the World Wide Web. In particular, we determine an optimum ring size for surfing, and show how to organize rings in a hierarchy so as to maximize the probability that a user will find the information he seeks. Given the surfing characteristics of users, which can be obtained from usage data, we also determine an optimum link structure.

Toward a Structured Information Retrieval System on the Web Automatic Structure Extraction of Web Pages
Mathias Gery, Jean-Pierre Chevallet

The World Wide Web is an distributed, heterogeneous and semi-structured information space. With the growth of available data, retrieving interesting information is becoming quite difficult and classical search engines give often very poor results. One of the main problems is the lack of explicit HTML pages structure, and more generally the lack of explicit Web sites structure. We show in this paper that it is possible to extract such a structure, which can be expressed following differents ways : semantics cut-off in a linear document, hypertext links (links, frames, etc) between several pages, dynamic pages, etc. We present some preliminary results of an analysis of a Web sample, extracting several levels of structure (a hierarchical tree structure, a graph-like structure), independently of the way in which this structure is implicitly described. Finally, we show how we will use this approach in an Information Retrieval System (IRS) based on a structured IR model, and thus manipulating a structured index of the Web. This IRS will use some IR methods used in the context of structured documents and hypertexts.

Learning of Ontologies from the Web: the Analysis of Existent Approaches
Borys Omelayenko

Everybody knows how difficult is to search and extract necessary information from the Web. The next generation of the Web called Semantic Web has to improve the Web with semantic (ontological) page annotations to enable knowledge-level querying and searches. Manual construction of these annotations will require tremendous efforts that forces future integration of machine learning with knowledge acquisition to enable highly automated ontology learning. The objective of the paper is to present state-of-the art and future directions of ontology learning from the Web. We point out the requirements for machine learning algorithms to be applied for ontology extraction from the Web documents, and survey the existent ontology learning and other closely related approaches. We investigate three components of the approaches: ontology domains treated, learning tasks that were automated and machine learning technologies that were applied. We discover several frequently used combinations of the components and point to several ontology learning tasks that are quite important for the future Web but are not under research focus now.

A Web Site Navigation Engine (demo)
Mark Levene, Richard Wheeldon, Jon Bitmead

Often users navigating (or ``surfing``) through a web site ``get lost in hyperspace``, when they lose the context in which they are browsing, and are unsure how to proceed in terms of satisfying their original goal. The unresolved problem in web site usability, of assisting users in finding their way, is termed the navigation problem. This problem is becoming even more accute with the continuing growth of web sites in terms of their structure, which is becoming more complex, and the vast amount information they intend to deliver. In contrast users are not willing to invest time to learn this structure and expect the delivery of the relevant content without delay. To tackle this problem we are developing a navigation system for semi-automating user navigation which builds trails of information, i.e. sequences of linked pages, which are relevant to the user query. The preferred trails are presented to the user in a tree-like structure which they can interact with. This is in sharp contrast to a search engine which merely outputs a list of pages which are relevant to the user query without addressing the problem of which trail the user should follow. We discuss the architecture of the navigation system and give a brief description of the navigation engine and user interface.

An Active Web-based Distributed Database System for E-Commerce
Hiroshi Ishikawa, Manabu Ohta

Electronic Commerce (EC) business models like e-brokers on the Web use WWW-based distributed XML databases such as product and customer data. To flexibly model such applications, we need a modeling language for EC businesses, specifically, its dynamic aspects or business processes. To this end, we have adopted a query language approach to modeling, extended by integrating active database functionality with it, and have designed an active query language for WWW-based XML databases, called XBML, suitable for specifying and controlling EC business processes. In this paper, we explain and validate the functionality of XBML by specifying e-broker and auction business models and describe the implementation of the XBML server, focusing on the distributed query processing in the WWW context.

A Probabilistic Approach to Model Adaptive Hypermedia using XML
Mario Cannataro, Andrea Pugliese

Web-based hypermedia systems allow user-driven access to information and services and content personalization. Application field where adaptive hypermedia systems could be used are on-line learning, electronic commerce, on-line advertising. This paper presents a probabilistic approach for the modelling of Adaptive Hypermedia Systems (AHS). The Application domain is modelled using weighted graphs of XML documents. The user`s behaviour is modelled using a probabilistic model and the most promising profile, that is a "view" over the application domain, is dynamically assigned to the user, using a discrete probability density function. XML data-centric orientation makes it possible to elegantly describe application domain, data access and dynamic data composition functions, allowing the use of pre-existing multimedia basic data.

Run-time Management Policies for Data Intensive Web sites
Christos Bouras, Agisilaos Konidaris

Web developers have been concerned with the issues of Web latency and Web data consistency for many years. These issues have become more important in our days since the accurate and imminent dissemination of information is vital to businesses and individuals that rely on the Web. In this paper, we evaluate different run-time management policies against real Web sites. We first define the meaning of data intensive Web sites and categorize them according to their hit patterns. Our research relies on real world Web data collected from various popular Web sites and proxy log files. We propose a Web site run-time management policy that may apply to various real Web site hit patterns and data update frequencies