Ponceleon,D.: Hierarchical segmentation: finding changes in a text signal,In

This paper describes a signal processing algorithm which discovers the hierarchical organization of a document or media presentation. We use latent semantic indexing to describe the semantic content of the signal, and scalespace segmentation to describe its features at many different scales. We represent the semantic content of the document as a signal that varies through the document. We lowpass filter this signal to compute the document’s semantic path at many different time scales and then look for changes. The changes are sorted by their strength to form a hierarchical segmentation. We present results from a text document and a video transcript. 1. THE PROBLEM As prices decline and storage and computational horsepower increase, we will soon be swamped in multimedia data. Unfortunately, given an audio or a video signal there is little information readily available that can help us find our way around such a time-based signal. Technical papers are structured into major and minor headings, imposing a hierarchical structure. Often professional or high-quality audio–visual (AV) presentations are also structured. However, this information is hidden in the signal. Our goal is to use the semantic information in the AV signal to create a hierarchical table of contents that describes the associated signal. Towards this end we combine two powerful concepts: scale space (SS) filtering and Latent Semantic Indexing (LSI). We use LSI to provide a continuously valued feature that describes the semantic content of an AV signal. By doing this we reduce the dimensionality of the problem and, more importantly, we address synonymy and poly

Hierarchical segmentation using latent semantic indexing in scale space

This paper describes a new algorithm which discovers the hierarchical organization of a document or media presentation. We use latent semantic indexing to describe the semantic content of the signal, and scale-space segmentation to describe its features at many different scales. We present results from a text document and a video transcript. 1. THE PROBLEM As prices decline and storage and computational horsepower increase, we will soon be swamped in multimedia data. Unfortunately, given an audio or a video signal there is little information readily available that can help us find our way around such a time-based signal. Technical papers are structured into major and minor headings, imposing a hierarchical structure. Often professional or high-quality AV presentations are also structured. However

Supporting Narrative Flow in Presentation Software

Commercial presentation software focuses on authoring, rather than on supporting the presentation process itself. Typical slide navigation tools are disruptive to the preWk"+}"ffff flow and coulddisclose slide eide We pre se nt a navigation tool forslide prev+}Wk'ff base d on de+T' principle such as"ne"k hide the curre ntslide" We kev the tool simple and ed+ to use to decrease the presenter's stress during a presentatio

WISDNA: An Information Visualization Paradigm for XML

With ever-increasing amounts of data in repositories, finding the information a user needs becomes increasingly challenging. When users approach an information access system they often do not have a clear understanding of how to access the precise information they need. Additionally, it is not rare that users have only a vague notion of what they are looking for, hence the need for an exploratory navigation tool beyond a static list of search results. A model used in practice is an iterative search-and-browse cycle to retrieve relevant information. The role of the user interface in understanding search results and providing relevant metadata in a compact manner is a key component of this iterative process. In this context we present WISDNA as an information visualization paradigm for XML data from web information services. According to the Department of Commerce U.S. online retail sales topped $32 billion in 2002, a 19 percent increase over the previous year. In 2002, c