MenuMiner

Keller, Matthias; Nussbaumer, Martin

doi:10.1145/2187980.2188237

Cited by 8 publications

References 21 publications

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Mining Taxonomies from Web Menus: Rule-Based Concepts and Algorithms

Keller

Hartenstein

2013

Lecture Notes in Computer Science

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The logical hierarchies of Web sites (i.e. Web site taxonomies) are obvious to humans, because humans can distinguish different menu levels and their relationships. But such accurate information about the logical structure is not yet available to machines. Many applications would benefit if Web site taxonomies could be mined from menus, but it was an almost unsolvable problem in the past. While a tag newly introduced in HTML5 and novel mining methods allow to distinguish menus from other contents today, it has not yet been researched, how the underlying taxonomies can be extracted, given the menus. In this paper we present the first detailed analysis of the problem and introduce rule-based concepts for addressing each identified sub problem. We report on a large-scale study on mining hierarchical menus of 350 randomly selected domains. Our methods allow extracting Web site taxonomy information that was not available before with high precision and high recall.

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Mining Taxonomies from Web Menus: Rule-Based Concepts and Algorithms

Keller

Hartenstein

2013

Lecture Notes in Computer Science

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Closed sequential pattern mining for sitemap generation

Ceci

Lanotte

2020

World Wide Web

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A sitemap represents an explicit specification of the design concept and knowledge organization of a website and is therefore considered as the website’s basic ontology. It not only presents the main usage flows for users, but also hierarchically organizes concepts of the website. Typically, sitemaps are defined by webmasters in the very early stages of the website design. However, during their life websites significantly change their structure, their content and their possible navigation paths. Even if this is not the case, webmasters can fail to either define sitemaps that reflect the actual website content or, vice versa, to define the actual organization of pages and links which do not reflect the intended organization of the content coded in the sitemaps. In this paper we propose an approach which automatically generates sitemaps. Contrary to other approaches proposed in the literature, which mainly generate sitemaps from the textual content of the pages, in this work sitemaps are generated by analyzing the Web graph of a website. This allows us to: i) automatically generate a sitemap on the basis of possible navigation paths, ii) compare the generated sitemaps with either the sitemap provided by the Web designer or with the intended sitemap of the website and, consequently, iii) plan possible website re-organization. The solution we propose is based on closed frequent sequence extraction and only concentrates on hyperlinks organized in “Web lists”, which are logical lists embedded in the pages. These “Web lists” are typically used for supporting users in Web site navigation and they include menus, navbars and content tables. Experiments performed on three real datasets show that the extracted sitemaps are much more similar to those defined by website curators than those obtained by competitor algorithms.

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Enhancing decision-making in user-centered web development: a methodology for card-sorting analysis

Macías

Culén

2021

World Wide Web

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The World Wide Web has become a common platform for interactive software development. Most web applications feature custom user interfaces used by millions of people every day. Information architecture addresses the structural design of information to build quality web applications with improved usability of content, navigation, and findability. One of the most frequently utilized information architecture methods is card sorting—an affordable, user-centered approach for eliciting and evaluating categories and navigable items. Card sorting facilitates decision-making during the development process based on users’ mental models of a given application domain. However, although the qualitative analysis of card sorts has become common practice in information architecture, the quantitative analysis of card sorting is less widely applied. The reason for this gap is that quantitative analysis often requires the use of customized techniques to extract meaningful information for decision-making. To facilitate this process and support the structuring of information, we propose a methodology for the quantitative analysis of card-sorting results in this paper. The suggested approach can be systematically applied to provide clues and support for decisions. These might significantly impact the design and, thus, the final quality of the web application. Therefore, the approach includes proper goodness values that enable comparisons among the results of the methods and techniques used and ensure the suitability of the analyses performed. Two publicly available datasets were used to demonstrate the key issues related to the interpretation of card sorting results and the overall suitability and validity of the proposed methodology.

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MenuMiner

Cited by 8 publications

References 21 publications

Mining Taxonomies from Web Menus: Rule-Based Concepts and Algorithms

Mining Taxonomies from Web Menus: Rule-Based Concepts and Algorithms

Closed sequential pattern mining for sitemap generation

Enhancing decision-making in user-centered web development: a methodology for card-sorting analysis

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