Abstract
This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.
Highlights
Retrieval tools have proven to be indispensable for searching and locating relevant information in large repositories
The existence of large slide presentation repositories in education and scholarly settings has necessitated the development of effective search and retrieval tools
This paper has examined the unique characteristics of slide presentations, as compared to traditional text and multimedia documents, and has proposed a retrieval tool geared toward such repositories
Summary
Retrieval tools have proven to be indispensable for searching and locating relevant information in large repositories. A plethora of solutions has been proposed and successfully applied to document, image, video, and audio collections Despite this success, bridging the so-called semantic gap still remains a key challenge in developing retrieval techniques. The relative positioning of text in this structure can provide hints about the degree of relevance of each term as perceived by the author Such information can be used in combination with traditional keyword matching to improve retrieval performance [3, 4]. The proposed system uses structural and text formatting attributes, such as indentation level, font size, and typeface, to calculate a relevance score for occurrences of the query term on each slide. The proposed score combination scheme provides a flexible framework to model the subjective nature of the concept of term relevance in varying slide authoring styles.
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