Michael Huggett

Cognitive Principles for Information Management: The Principles of Mnemonic Associative Knowledge (P-MAK)

Information management systems improve the retention of information in large collections. As such they act as memory prostheses, implying an ideal basis in human memory models. Since humans process information by association, and situate it in the context of space and time, systems should maximize their effectiveness by mimicking these functions. Since human attentional capacity is limited, systems should scaffold cognitive efforts in a comprehensible manner. We propose the Principles of Mnemonic Associative Knowledge (P-MAK), which describes a framework for semantically identifying, organizing, and retrieving information, and for encoding episodic events by time and stimuli. Inspired by prominent human memory models, we propose associative networks as a preferred representation. Networks are ideal for their parsimony, flexibility, and ease of inspection. Networks also possess topological properties—such as clusters, hubs, and the small world—that aid analysis and navigation in an information space. Our cognitive perspective addresses fundamental problems faced by information management systems, in particular the retrieval of related items and the representation of context. We present evidence from neuroscience and memory research in support of this approach, and discuss the implications of systems design within the constraints of P-MAK’s principles, using text documents as an illustrative semantic domain.

Dynamic online views of meta-indexes

For a collection of digitized monographs in a subject domain, a domain meta-index provides a summary of domain concepts, and a structured vocabulary to support a scholars navigation and search. We present a prototype of a Meta-index User Interface (MUI) that provides views of a domain at three levels: summarizing and comparing domains, exposing the regularities of a domains vocabulary, and displaying book information and page content related both to objectively-representative books, and to specific user searches.

Integrative online research-data management

In support of our research projects in information retrieval, we have developed an integrated multi-process software system that shepherds research data from induction through aggregation, analysis, and presentation. We combine public-domain code libraries with our own software to provide a flexible, easily- configured modular system that exposes data online for easier collaboration. The goal is to create a single online infrastructure that allows colleagues to submit, process, analyze and visualize data, and discuss and prioritize issues through a single integrated interface. We demonstrate our system within the context of the large data set provided by the Indexers Legacy project [1].

Static reformulation: a user study of static hypertext for query-based reformulation

Hypertext allows users to navigate between related materials in digital libraries. The most fundamental automated hypertexts are those constructed on the basis of semantic similarity. Such hypertexts have been evaluated by a variety of means, but seldom by real users given simulated real-world tasks. We claim that while other methods exist, one of the best ways to prove the usefulness of hypertext is to show the benefits for users performing realistic tasks. We compare the reformulation of queries that users perform in keyword searching, to the query reformulation implicit in browsing between documents linked by similarity of content. We find that a static automatically-constructed similarity hypertext provides useful linking between related items, improving the retrieval of targets when used to augment standard keyword search.

Using digital book metrics for navigation and browsing

As the scholar’s work migrates from print to the digital realm, new ways of browsing, navigating and searching collections of digital books are needed. The Back-of Book Index is a carefully crafted source of information on a book’s vocabulary and concepts, and if aggregated across multiple books, for a subject domain as a whole. Using a test collection of digital books in a variety of domains, we explore the use of index vocabulary to derive a series of metrics to indicate the relationships between index vocabulary and the digital collection, and the relationships between the books within a digital domain. We are investigating ways in which these metrics can be used to facilitate navigation and browsing at the domain level, to identify the most appropriate works within a digital collection for a particular subject or topic.

The Meta-Dex Suite: generating and analyzing indexes and meta-indexes

Our Meta-dex software suite extracts content and index text from a corpus of PDF files, and generates a meta-index that references entries across an entire domain. We provide tools to analyze the individual and integrated indexes, and visualize entries and books within the meta-index. The suite is scalable to very large data sets.

Creating meta-indexes for digital domains

The back-of-book indexes for test collections of digital books in the domains of Economics and Geology have been deconstructed and analyzed, and the entries aggregated to create domain-level meta-indexes. Metrics comparing the two domains are presented.

Domain Search and Exploration with Meta-Indexes

In order to facilitate navigation and search of large collections of digital books, we have developed a new knowledge structure, the meta-index, which aggregates the back-of-book indexes within a subject domain. Using a test collection of digital books, we demonstrate the use of the meta-index and associated metrics that characterize the books within a digital domain, and explore some of the challenges presented by the meta-index structure.

User interface evaluation of meta-indexes for search

In the Indexers Legacy Project, we have created meta-indexes for domain-oriented collections of digital books in order to promote searching, navigation and browsing in digital collections. Because the meta-index is a new knowledge structure, we have used focus groups and sample tasks to collect information on users perception and use of meta-indexes. Users responses were positive and their suggestions led to improvements in our online Meta-Dex User Interface (MUI) tool, which will be tested in subsequent user studies.

Meta-index views on digital domains

Domain meta-indexes provide a summary of domain concepts, and a structured vocabulary from which to form queries and organize research. We present a prototype of a Meta-index User Interface (MUI) that provides views of a domain at 3 levels: summarizing and comparing domains, exposing the regularities of a domains vocabulary, and displaying book information and page content related both to objectively representative books, and to specific user searches.