Abstract not found

Traditional information retrieval systems present search results as a ranked list of documents, ordered by their estimated relevance to the query. Visualization of search results is emerging as a powerful tool for presenting more information to the user in a way that is both intuitive and easy to interpret. This paper describes the various visualization techniques, and presents a novel classification of these methods. Next it discusses several of the important issues concerning these techniques: how they are evaluated, how they scale to large document sets, can they be combined, and will we see them in practice on the Web anytime soon. 1

Current user interfaces of full text retrieval systems do not help in the process of filtering the result of a query, usually very large. We address this problem and we propose a visual interface to handle the result of a query, based on a hybrid model for text. This graphical user interface provides several visual representations of the answer and its elements (queries, documents, and text), easing the analysis and the filtering process. Keywords: visual browsing, visual text databases, visual tools, visual representations, visual query languages, set visualization, visual analysis. 1 Introduction Full text retrieval systems are a popular way of providing support for on-line text. Their advantage is that they avoid the complicated and expensive process of semantic indexing. From the end-user point of view, full text searching of on-line documents is appealing because a valid query is just any word or sentence of the document. However, there is no standard query language despite the ...

Dynamic Fisheye Views: Combining Dynamic Queries and Mapping with Database View Definition Doctor of Philosophy, 1996 Department of Computer Science University of Toronto Information (or data) visualization refers to the graphical presentation of information with the aim of providing the viewer with a qualitative understanding of the information contents. Two common graphical methods for depicting multidimensional data are scatterplots (that show relationships among data dimensions) and node-andlink diagrams or graphs (that show relationships among individual data points). One strategy to aid understanding of multidimensional data is to map data dimensions or attributes (e.g., temperature, population, location) to graphic properties (e.g., colour, size, position). Dynamic mapping (DM) is an interactive technique that permits mappings to be adjusted dynamically. The dynamic query (DQ) is a related interactive technique that applies the principles of direct manipulation to the sea...

The idea of Information Visualization is to get insights into great amounts of abstract data. Especially document sets found by searching the World Wide Web are a special challenge. The paper gives a short overview on the variety of possible visualizations for this application area. Crucial factors for the success of visualizations are discussed. A combined approach is presented to use alternative simple visualizations, grouped around the traditional result-list, for usage with a local meta web search engine.

Query languages of full text retrieval systems are based on several assumptions about the input text. Many systems assume that the input has some basic structure (say, documents and words) which restricts the application domain. Others only allow to retrieve documents and not text positions. We address these problems and we propose an extended model for text, and a query language based on it. The query language is powerful enough to be used as an intermediate language to customized and/or intelligent retrieval applications based on visual interfaces. We also discuss several implementation issues giving preliminary experimental results. Keywords: Text databases, query languages. 1 Introduction Full text retrieval systems are becoming a popular way of providing support for on-line text. Their advantage is that they avoid the complicated and expensive process of semantic indexing. From the end-user point of view, full text searching of on-line documents is appealing because a valid quer...

With the increase in information on the World Wide Web it has become difficult to find desired information quickly without using multiple queries or using a topic-specific search engine. One way to help in the search is by grouping HTML pages together that appear in some way to be related. In order to better understand this task, we performed an initial study of human clustering of web pages, in the hope that it would provide some insight into the difficulty of automating this task. Our results show that subjects did not cluster identically; in fact, on average, any two subjects had little similarity in their web-page clusters. We also found that subjects generally created rather small clusters, and those with access only to URLs created fewer clusters than those with access to the full text of each web page. Generally the overlap of documents between clusters for any given subject increased when given the full text, as did the percentage of documents clustered. When analyzing individual subjects, we found that each had different behavior across queries, both in terms of overlap, size of clusters, and number of clusters. These results provide a sobering note on any quest for a single clearly correct clustering method for web pages. 1 1

We address some issues relating to retrieval from unfamiliar text collections consisting of full-length documents. We claim that displaying query results in terms of inter-document similarity is inappropriate with long texts, and suggest instead that the results of simple initial queries should be contextualized according to category sets that correspond to the main topics of the texts. We argue that main topics of long texts should be represented by multiple categories, since in most cases one category cannot adequately classify a text. We describe a new automatic categorization algorithm that does not require pre-labeled texts and a prototype browsing interface that presents a simple mechanism for displaying multi-dimensional information. 1

The Document Explorer provides head-coupled stereoscpopic viewing of 3-d visual representations for document collections, associative term thesauri, and individual documents. This style of interface has been called "fish tank VR" and shown to be relatively effective for 3-d viewing and interaction tasks. The system also provides mechanisms to integrate query formulation across the visual representations. Supplying interaction techniques to access the system's several visual representations is one of the system's goals. The demonstration allows users to experiment with 3-d interaction in the highly interactive, iterative process of information retrieval.

visual retrieval model