From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Wikipedia as an encyclopaedia of life

In his 2003 essay E O Wilson outlined his vision for an “encyclopaedia of life” comprising “an electronic page for each species of organism on Earth”, each page containing “the scientific name of the species, a pictorial or genomic presentation of the primary type specimen on which its name is based, and a summary of its diagnostic traits.” Although the “quiet revolution” in biodiversity informatics has generated numerous online resources, including some directly inspired by Wilson's essay (e.g., "http://ispecies.org":http://ispecies.org, "http://www.eol.org":http://www.eol.org), we are still some way from the goal of having available online all relevant information about a species, such as its taxonomy, evolutionary history, genomics, morphology, ecology, and behaviour. While the biodiversity community has been developing a plethora of databases, some with overlapping goals and duplicated content, Wikipedia has been slowly growing to the point where it now has over 100,000 pages on biological taxa. My goal in this essay is to explore the idea that, largely independent of the efforts of biodiversity informatics and well-funded international efforts, Wikipedia ("http://en.wikipedia.org/wiki/Main_Page":http://en.wikipedia.org/wiki/Main_Page) has emerged as potentially the best platform for fulfilling E O Wilson’s vision

BlogForever D2.6: Data Extraction Methodology

This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform

Combining link and content-based information in a Bayesian inference model for entity search

An architectural model of a Bayesian inference network to support entity search in semantic knowledge bases is presented. The model supports the explicit combination of primitive data type and object-level semantics under a single computational framework. A flexible query model is supported capable to reason with the availability of simple semantics in querie

The Online Bioinformatics Resources Collection at the University of Pittsburgh Health Sciences Library System—a one-stop gateway to online bioinformatics databases and software tools

To bridge the gap between the rising information needs of biological and medical researchers and the rapidly growing number of online bioinformatics resources, we have created the Online Bioinformatics Resources Collection (OBRC) at the Health Sciences Library System (HSLS) at the University of Pittsburgh. The OBRC, containing 1542 major online bioinformatics databases and software tools, was constructed using the HSLS content management system built on the Zope(®) Web application server. To enhance the output of search results, we further implemented the Vivísimo Clustering Engine(®), which automatically organizes the search results into categories created dynamically based on the textual information of the retrieved records. As the largest online collection of its kind and the only one with advanced search results clustering, OBRC is aimed at becoming a one-stop guided information gateway to the major bioinformatics databases and software tools on the Web. OBRC is available at the University of Pittsburgh's HSLS Web site ()

VAS (Visual Analysis System): An information visualization engine to interpret World Wide Web structure

People increasingly encounter problems of interpreting and filtering mass quantities of information. The enormous growth of information systems on the World Wide Web has demonstrated that we need systems to filter, interpret, organize and present information in ways that allow users to use these large quantities of information. People need to be able to extract knowledge from this sometimes meaningful but sometimes useless mass of data in order to make informed decisions. Web users need to have some kind of information about the sort of page they might visit, such as, is it a rarely referenced or often-referenced page? This master\u27s thesis presents a method to address these problems using data mining and information visualization techniques