Bettina Berendt

Towards Semantic Web Mining

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. The idea is to improve, on the one hand, the results of Web Mining by exploiting the new semantic structures in the Web; and to make use of Web Mining, on the other hand, for building up the Semantic Web. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.

Analysis of navigation behaviour in web sites integrating multiple information systems

Abstract. The analysis of web usage has mostly focused on sites composed of conventional static pages. However, huge amounts of information available in the web come from databases or other data collections and are presented to the users in the form of dynamically generated pages. The query interfaces of such sites allow the specification of many search criteria. Their generated results support navigation to pages of results combining cross-linked data from many sources. For the analysis of visitor navigation behaviour in such web sites, we propose the web usage miner (WUM), which discovers navigation patterns subject to advanced statistical and structural constraints. Since our objective is the discovery of interesting navigation patterns, we do not focus on accesses to individual pages. Instead, we construct conceptual hierarchies that reflect the query capabilities used in the production of those pages. Our experiments with a real web site that integrates data from multiple databases, the German SchulWeb, demonstrate the appropriateness of WUM in discovering navigation patterns and show how those discoveries can help in assessing and improving the quality of the site.

Semantic Web Mining: State of the art and future directions

Abstract Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: More and more researchers are working on improving the results of Web Mining by exploiting semantic structures in the Web, and they make use of Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.

Investigating Distance Knowledge Using Virtual Environments

Computer-simulated three-dimensional environments have become a popular tool in spatial cognition research. One way of demonstrating their usefulness is to replicate experimental results obtained in physical spaces. Two experiments investigated the role of environmental features in distance cognition, following Sadalla and Magel. Their participants explored routes marked with tape on the floor through active walking. Results showed that a higher number of turns along a route increased the estimated length of that route. In the authors’experiments, participants had to explore the routes in a desktop virtual environment. Experiment 1 employed ratio estimation and drawing methods and replicated Sadalla and Magel’s findings. Experiment 2 employed a reproduction method, and extends the results by showing that relative to physical distance, the route with fewer turns was underestimated, while the route with more turns was overestimated. The results show that desktop virtual environments are a valid and economic research tool.

Web Mining: From Web to Semantic Web

In this paper we look at the deployment of web usage mining results within two key application areas of web measurement and knowledge generation for personalisation. We take a fresh look at the model of interaction between business and visitors to their web sites and the sources of data generated during these interactions. We then look at previous attempts at measuring the effectiveness of the web as a channel to customers and describe our approach, based on scenario development and measurement to gain insights into customer behaviour. We then present Concerto, a platform for deploying knowledge on customer behaviour with the aim of providing a more personalized service. We also look at approaches to measuring the effectiveness of the personalization. Various standards that are emerging in the market that can ease the integration effort of personalization and similar knowledge deployment engines within the existing IT infrastructure of an organization are also presented. Finally, current challenges in the deployment of web usage mining are presented.

Spatial Representation with Aspect Maps

This paper describes the aspect map approach to model the processing of geographic maps. Geographic maps are described as spatial representation media which play an important role in many processes of human spatial cognition. We focus on the aspectuality of representation and therefore deal with aspect maps: spatial organization structures in which one or more aspects of geographic entities are represented. The aspect map architecture is presented, an AI model of processing geographic maps. Two processes contained in this model are investigated in more detail. The first is the transformation of one aspect map into another aspect map which only retains selected entities and aspects (extraction). The second process is the combination of two aspect maps, in order to obtain a third aspect map. The results of an empirical study show that the formal approach can describe and distinguish the ways in which people solve this task.

A user-centric approach to identifying best deployment strategies for language tools: the impact of content and access language on Web user behaviour and attitudes

The number of Web users whose first language is not English continues to grow, as does the amount of content provided in languages other than English. This poses new challenges for actors on the Web, such as in which language(s) content should be offered, how search tools should deal with mono- and multilingual content, and how users can make the best use of navigation and search options, suited to their individual linguistic skills. How should these challenges be dealt with? Technological approaches to non-English (or in general, cross-language) Web search have made large progress; however, translation remains a hard problem. This precludes a low-cost but high-quality blanket all-language coverage of the whole Web. In this paper, we propose a user-centric approach to answering questions of where to best concentrate efforts and investments. Drawing on linguistic research, we describe data on the availability of content and access to it in first and second languages across the Web. We then present three studies that investigated the impact of the availability (or not) of first-language content and access forms on user behaviour and attitudes. The results indicate that non-English languages are under-represented on the Web and that this is partly due to content-creation, link-setting and link-following behaviour. They also show that user satisfaction is influenced both by the cognitive effort of searching and the availability of alternative information in that language. These findings suggest that more cross-language tools are desirable. However, they also indicate that context (such as user groups’ domain expertise or site type) should be considered when tradeoffs between information quality and multilinguality need to be taken into account.

A Roadmap for Web Mining: From Web to Semantic Web

The purpose of Web mining is to develop methods and systems for discovering models of objects and processes on the World Wide Web and for web-based systems that show adaptive performance. Web Mining integrates three parent areas: Data Mining (we use this term here also for the closely related areas of Machine Learning and Knowledge Discovery), Internet technology and World Wide Web, and for the more recent Semantic Web. The World Wide Web has made an enormous amount of information electronically accessible. The use of email, news and markup languages like HTML allow users to publish and read documents at a world-wide scale and to communicate via chat connections, including information in the form of images and voice records. The HTTP protocol that enables access to documents over the network via Web browsers created an immense improvement in communication and access to information. For some years these possibilities were used mostly in the scientific world but recent years have seen an immense growth in popularity, supported by the wide availability of computers and broadband communication. The use of the internet for other tasks than finding information and direct communication is increasing, as can be seen from the interest in “e-activities” such as e-commerce, e-learning, e-government, e-science.

Semantics, Web and Mining

EWMF Papers.- A Website Mining Model Centered on User Queries.- WordNet-Based Word Sense Disambiguation for Learning User Profiles.- Visibility Analysis on the Web Using Co-visibilities and Semantic Networks.- Link-Local Features for Hypertext Classification.- Information Retrieval in Trust-Enhanced Document Networks.- Semi-automatic Creation and Maintenance of Web Resources with webTopic.- KDO Papers on KDD for Ontology.- Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis.- Semi-automatic Construction of Topic Ontologies.- Evaluation of Ontology Enhancement Tools.- KDO Papers on Ontology for KDD.- Introducing Semantics in Web Personalization: The Role of Ontologies.- Ontology-Enhanced Association Mining.- Ontology-Based Rummaging Mechanisms for the Interpretation of Web Usage Patterns.

Language-sensitive search behaviour and the role of domain knowledge

While many websites aim at a large and linguistically diversified audience, they present their information mostly in the languages of larger speakers groups. Little is known about the effect on accessibility. We investigated the influence of a sites language offer on website access and search behaviour with two studies, and studied the interaction of language offers and domain knowledge. To achieve high ecological validity, we analysed data from a multilingual sites web-server logfile and from a questionnaire posted on it, and compared the behaviour of users who accessed the site in a non-native language to that of users who accessed it in their native language. Results from 277,809 user sessions and 165 international survey participants indicate that a websites languages may strongly reduce website access by users not supplied with information in their native language. Once inside a site, non-native speakers with high domain knowledge behave similarly to native speakers. However, non-native speakers’ behaviour becomes language-sensitive when they have low domain knowledge.