A user evaluation of hierarchical phrase browsing

Phrase browsing interfaces based on hierarchies of phrases extracted automatically from document collections offer a useful compromise between automatic full-text searching and manually-created subject indexes. The literature contains descriptions of such systems that many find compelling and persuasive. However, evaluation studies have either been anecdotal, or focused on objective measures of the quality of automatically-extracted index terms, or restricted to questions of computational efficiency and feasibility. This paper reports on an empirical, controlled user study that compares hierarchical phrase browsing with full-text searching over a range of information seeking tasks. Users found the results located via phrase browsing to be relevant and useful but preferred keyword searching for certain types of queries. Users experiences were marred by interface details, including inconsistencies between the phrase browser and the surrounding digital library interface

Automatically organising images using concept hierarchies

In this paper we discuss the use of concept hierarchies, an approach to automatically organize a set of documents based upon a set of concepts derived from the documents themselves for image retrieval. Co-occurrence between terms associated with image captions and a statistical relation called subsumption are used to generate term clusters which are organized hierarchically. Previously, the approach has been studied for document retrieval and results have shown that automatically generating hierarchies can help users with their search task. In this paper we present an implementation of concept hierarchies for image retrieval, together with preliminary ad-hoc evaluation. Although our approach requires more investigation, initial results from a prototype system are promising and would appear to provide a useful summary of the search results

Evaluating hierarchical organisation structures for exploring digital libraries

Search boxes providing simple keyword-based search are insufficient when users have complex information needs or are unfamiliar with a collection, for example in large digital libraries. Browsing hierarchies can support these richer interactions, but many collections do not have a suitable hierarchy available. In this paper we present a number of approaches for automatically creating hierarchies and mapping items into them, including a novel technique which automatically adapts a Wikipedia-based taxonomy to the target collection. These approaches are applied to a large collection of cultural heritage items which is formed through the aggregation of other collections and for which no unified hierarchy is available. We investigate a number of novel user-evaluated metrics to quantify the hierarchies’ quality and performance, showing that the proposed technique is preferred by users. From this we draw a number of conclusions as to what makes a hierarchy useful to the user

Analysis of equivalence mapping for terminology services

This paper assesses the range of equivalence or mapping types required to facilitate interoperability in the context of a distributed terminology server. A detailed set of mapping types were examined, with a view to determining their validity for characterizing relationships between mappings from selected terminologies (AAT, LCSH, MeSH, and UNESCO) to the Dewey Decimal Classification (DDC) scheme. It was hypothesized that the detailed set of 19 match types proposed by Chaplan in 1995 is unnecessary in this context and that they could be reduced to a less detailed conceptually-based set. Results from an extensive mapping exercise support the main hypothesis and a generic suite of match types are proposed, although doubt remains over the current adequacy of the developing Simple Knowledge Organization System (SKOS) Core Mapping Vocabulary Specification (MVS) for inter-terminology mapping

Concept-based Interactive Query Expansion Support Tool (CIQUEST)

This report describes a three-year project (2000-03) undertaken in the Information Studies Department at The University of Sheffield and funded by Resource, The Council for Museums, Archives and Libraries. The overall aim of the research was to provide user support for query formulation and reformulation in searching large-scale textual resources including those of the World Wide Web. More specifically the objectives were: to investigate and evaluate methods for the automatic generation and organisation of concepts derived from retrieved document sets, based on statistical methods for term weighting; and to conduct user-based evaluations on the understanding, presentation and retrieval effectiveness of concept structures in selecting candidate terms for interactive query expansion. The TREC test collection formed the basis for the seven evaluative experiments conducted in the course of the project. These formed four distinct phases in the project plan. In the first phase, a series of experiments was conducted to investigate further techniques for concept derivation and hierarchical organisation and structure. The second phase was concerned with user-based validation of the concept structures. Results of phases 1 and 2 informed on the design of the test system and the user interface was developed in phase 3. The final phase entailed a user-based summative evaluation of the CiQuest system. The main findings demonstrate that concept hierarchies can effectively be generated from sets of retrieved documents and displayed to searchers in a meaningful way. The approach provides the searcher with an overview of the contents of the retrieved documents, which in turn facilitates the viewing of documents and selection of the most relevant ones. Concept hierarchies are a good source of terms for query expansion and can improve precision. The extraction of descriptive phrases as an alternative source of terms was also effective. With respect to presentation, cascading menus were easy to browse for selecting terms and for viewing documents. In conclusion the project dissemination programme and future work are outlined

Adaptive text mining: Inferring structure from sequences

Text mining is about inferring structure from sequences representing natural language text, and may be defined as the process of analyzing text to extract information that is useful for particular purposes. Although hand-crafted heuristics are a common practical approach for extracting information from text, a general, and generalizable, approach requires adaptive techniques. This paper studies the way in which the adaptive techniques used in text compression can be applied to text mining. It develops several examples: extraction of hierarchical phrase structures from text, identification of keyphrases in documents, locating proper names and quantities of interest in a piece of text, text categorization, word segmentation, acronym extraction, and structure recognition. We conclude that compression forms a sound unifying principle that allows many text mining problems to be tacked adaptively

A Document Browsing Tool Based on Book Indexes

This research project is a contribution to the global field of information retrieval, specifically, to develop tools to enable information access in digital documents. We recognize the need to provide the user with flexible access to the contents of large, potentially complex digital documents, with means other than a search function or a handful of metadata elements. The goal is to produce a text browsing tool offering a maximum of information based on a fairly superficial linguistic analysis. We are concerned with a type of extensive single-document indexing, and not indexing by a set of keywords (see Klement, 2002, for a clear distinction between the two). The desired browsing tool would not only give at a glance the main topics discussed in the document, but would also present relationships between these topics. It would also give direct access to the text (via hypertext links to specific passages). The present paper, after reviewing previous research on this and similar topics, discusses the methodology and the main characteristics of a prototype we have devised. Experimental results are presented, as well as an analysis of remaining hurdles and potential applications.CRSN

Supporting Multiple Paths to Objects in Information Hierarchies: Faceted Classification, Faceted Search, and Symbolic Links

We present three fundamental, interrelated approaches to support multiple access paths to each terminal object in information hierarchies: faceted classification, faceted search, and web directories with embedded symbolic links. This survey aims to demonstrate how each approach supports users who seek information from multiple perspectives. We achieve this by exploring each approach, the relationships between these approaches, including tradeoffs, and how they can be used in concert, while focusing on a core set of hypermedia elements common to all. This approach provides a foundation from which to study, understand, and synthesize applications which employ these techniques. This survey does not aim to be comprehensive, but rather focuses on thematic issues

The PATHS System for Exploring Digital Cultural Heritage

Over the past years large digital cultural heritage collections have become available, however access paradigms have not kept pace with this development and are still primarily constructed around simple keyword search. This works well for users familiar with the collections, but for new users who are unfamiliar with the collection they present a significant hurdle. The PATHS (Personalised Access To cultural Heritage Spaces) project addresses these issues by providing a novel framework for exploring large digital cultural heritage collections, built around the metaphor of a path through the collection. In this paper we present the initial user requirements analysis that was used to determine what a path is in the cultural heritage domain. From this we developed a conceptual model of path interaction, which was turned into a system design and implementation. Finally we present the evaluation of the resulting system and draw a number of conclusions as to what systems supporting exploration in digital cultural heritage collections must support to enable the users to satisfy their information needs

Enriching and designing metaschemas for the UMLS semantic network

The disparate terminologies used by various biomedical applications or professionals make the communication between them more difficult. The Unified Medical Language System (UMLS) of the National Library of Medicine (NLM) is an attempt to integrate different medical terminologies into a unified representation framework to improve decision making and the quality of patient care as well as research in the health-care field. Metathesaurus (META) and Semantic Network (SN) are two main components of the UMLS system, where the SN provides a high-level abstract of the concepts in the META. This dissertation addresses three problems of the SN. First, the SN\u27s two-tree structure is restrictive because it does not allow a semantic type to be a specialization of several other semantic types. This restriction leads to the omission of some subsumption knowledge in the SN. Secondly, the SN is large and complex for comprehension purposes and it does not come with a pictorial representation for users. As a partial solution for this problem, several metaschemas were previously built as higher-level abstractions for the SN to help users\u27 orientation. Third, there is no efficient method to evaluate each metaschema. There is no technique to obtain a consolidated metaschema acceptable for a majority of the UMLS\u27s users. In this dissertation work the author attacked the described problems by using the following approaches. (1) The SN was expanded into the Enriched Semantic Network (ESN), a multiple subsumption structure with a directed acyclic graph (DAG) IS-A hierarchy, allowing a semantic type to have multiple parents. New viable IS-A links were added as warranted. Two methodologies were presented to identify and add new viable IS-A links. The ESN serves as an extended high-level abstract of the META. (2) The ESN\u27s semantic relationship distribution and concept configuration were studied. Rules were defined to derive the ESN\u27s semantic relationship distribution from the current SN\u27s semantic relationship distribution. A mapping function was defined to map the SN\u27s concept configuration to the ESN\u27s concept configuration, avoiding redundant classifications in the ESN\u27s concept configuration. (3) Several new metaschemas for the SN and the ESN were built and evaluated based on several different partitioning techniques. Each of these metaschema can serve as a higher-level abstraction of the SN (or the ESN)