Carsten Stolz

Relevance and Impact of Tabbed Browsing Behavior on Web Usage Mining

The rapid growth of the Internet has pushed the research and development of Web usage mining ever more into focus. Web usage mining and its applications have become critical to the business world. These analyses rest in turn on the ability to develop a clear understanding of the actions a user has taken. So far, the temporal order of clicks has been taken to be equal to the structural order of a session. With the advent of the newest browser generation where the use of multiple tabs has become a common feature, the above assumption does not necessarily hold any more. It is crucial to understand how the use of multiple tabs impacts on Web usage mining, especially on the understanding of a session and its reconstruction. In order to analyze this new browsing behavior, we introduce a generic browsing model extending the traditional serial or single window model to cover the use of multiple tabs. Based on this model, we present and analyze an approach to detect use of multiple tabs within sessions. The existence and increasing prominence of the use of multiple tabs is shown by this approach to be of relevance to business analysis as well as research results

Guidance Performance Indicator " Web Metrics for Information Driven Web Sites

For the evaluation of Web sites, a multitude of metrics are available. Apart from general statistical measures, success metrics reflect the degree to which a Web site achieves its defined objectives. Particularly metrics for e-commerce sites based on transaction analysis are commonly available and well understood. In contrast to transaction based sites, the success of Web sites geared toward information delivery is harder to quantify since there is no direct feedback of user intent. User feedback is only directly available on transactional Web sites. We introduce a metric to measure the success of an information driven Web site in meeting its objective to deliver the desired information in a timely and usable fashion. We propose to assign a value to each click based on the type of transition, duration and semantic distance. These values are then combined into a scoring model describing the success of a Web site in meeting its objectives. The resulting metric is introduced as the GPI and its applicability shown on a large corporate Web site.

Matching web site structure and content

To keep an overview of a complex corporate web sites, it is crucial to understand the relationship of contents, structure and the users behavior. In this paper, we describe an approach which is allowing us to compare web page content with the information implictly defined by the structure of the web site. We start by describing each web page with a set of key words. We combine this information with the link structure in an algorithm generating a context based description. By comparing both descriptions, we draw conclusions about the semantic relationship of a web page and its neighbourhood. In this way, we indicate whether a page fits in the content of its neighbourhood. Doing this, we implicitly identify topics which span over several connected web pages. With our approach we support redesign processes by assessing the actual structure and content of a web site with designers concepts.

Web performance indicator by implicit user feedback – application and formal approach

With growing importance of the internet, web sites have to be continously improved. Web metrics help to identify improvement potentials. Particularly success metrics for e-commerce sites based on transaction analysis are commonly available and well understood. In contrast to transaction based sites, the success of web sites geared toward information delivery is harder to quantify since there is no direct feedback of the user. We propose a generic success measure for information driven web sites. The idea of the measure is based on the observation of user behaviour in context of the web site semantics. In particular we observe users on their way through the web site and assign positive and negative scores to their actions. The value of the score depends on the transitions between page types and their contribution to the web site’s objectives. To derive a generic view on the metric construction, we introduce a formal meta environment deriving success measures upon the relations and dependencies of usage, content and structure of a web site.

Searchstrings revealing user intent: a better understanding of user perception

The evaluation of information driven websites by analysis of serverside available data is the objective of our approach. In our former work we developed techniques for evaluation of non-transactional websites by regarding the authors intentions and using only based on implicit user feedback. In several case studies we got aware that in single cases unsatisfied users had been evaluated positively. This divergence could be explained by not having considered the users intentions. We propose in this approach to integrate search queries within referrer informaiton as freely available information about the users intentions. By integrating this new source of information into our meta model of website structure, content and author intention, we enhance the formerly developed web success metric GPI. We apply well understood techniques such as PLSA for text categorization. Based on the latent semantic we construct a new indicator evaluating the website with respect to the user intention. By ranking all webpages with respect to the user intention manifested in the search query, we acchieve an individualized measure to evaluate a session by the users initial intention. In contrast to manual assignments of weights by the website author, our proposed measure is purely calculated allowing a generic assessment of websites without manual intervention.In a case study we can show, that this indicator evaluates the quality and usability of a website more accurately by taking the users goals under consideration. We can also show, that the initially mentioned diverging user sessions, can now be assessed according to the users perception.Due to limited information on the host side, without direct access to the client side, still some assumptions remain to be made.

Improving semantic consistency of web sites by quantifying user intent

The design and organization of a website reflects the authors intent. Since user perception and understanding of websites may differ from the authors, we propose a means to identify and quantify this difference in perception. In our approach we extract perceived semantic focus by analyzing user behavior in conjunction with keyword similarity. By combining usage and content data we identify user groups with regard to the subject of the pages they visited. Our real world data shows that these user groups are nicely distinguishable by their content focus. By introducing a distance measure of keyword coincidence between web pages and user groups, we can identify pages of similar perceived interest. A discrepancy between perceived distance and link distance in the web graph indicates an inconsistency in the web sites design. Determining usage similarity allows the web site author to optimize the content to the users needs.

Measuring Semantic Relations of Web Sites by Clustering of Local Context

Our contribution in this paper is an approach to measure semantical relations within a web site. We start with a web page description by key words. The implementation of structural and content information reduces the variety of key words. Thereby, the document-key-word-matrix is smoothend and similarities between web pages are emphasized. This increases the possibility of cluster key words and identif topics successfully. To do so, we implement a probabilistic clustering algorithm. To assess semantic relations, we introduce a number of measures and interpret them.

Web Site Performance Analysis Success Assessment of Information Driven Web Site on User Traces

Web metrics help to identify improvement potentials for web sites. In contrast to transaction based sites, the success of web sites geared toward information delivery is harder to quantify without direct feedback out of a transaction. We propose a generic success measure for information driven web sites by observing the users in context of the web site semantics. Thus we identify target pages, analyze the web page content and evaluate effectiveness and efficiency of the user actions with respect to the web site’s objectives. The user’s perspective has to be incorporated for a comprehensive success measure. We propose to integrate search queries from referrer information carrying the user’s intentions. Out of an integrated web site meta model we derive formally a new success measure. This approach uses common data mining techniques and text mining algorithms like PLSA and shows its applicability in two case studies and an independent user enquiry.