Search (4 results, page 1 of 1)

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Abstract

Both structured and unstructured data, as well as structured data representing several different types of tuples, may be integrated into a single list for browsing or retrieval. Data may be arranged in the Gray code order of the features and metadata, producing optimal ordering for browsing. We provide several metrics for evaluating the performance of systems supporting browsing, given some constraints. Metadata and indexing terms are used for sorting keys and attributes for structured data, as well as for semi-structured or unstructured documents, images, media, etc. Economic and information theoretic models are suggested that enable the ordering to adapt to user preferences. Different relational structures and unstructured data may be integrated into a single, optimal ordering for browsing or for displaying tables in digital libraries, database management systems, or information retrieval systems. Adaptive displays of data are discussed.

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Abstract

When do information retrieval systems using two document clusters provide better retrieval performance than systems using no clustering? We answer this question for one set of assumptions and suggest how this may be studied with other assumptions. The "Cluster Hypothesis" asks an empirical question about the relationships between documents and user-supplied relevance judgments, while the "Cluster Performance Question" proposed here focuses an the when and why of information retrieval or digital library performance for clustered and unclustered text databases. This may be generalized to study the relative performance of m versus n clusters.

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Abstract

The variety of performance measures available for information retrieval systems, search engines, and network filtering agents can be confusing to both practitioners and scholars. Most discussions about these measures address their theoretical foundations and the characteristics of a measure that make it desirable for a particular application. In this work, we consider how measures of performance at a point in a search may be formally compared. Criteria are developed that allow one to determine the percent of time or conditions under which 2 different performance measures suggest that one document ordering is superior to another ordering, or when the 2 measures disagree about the relative value of document orderings. As an example, graphs provide illustrations of the relationships between precision and F

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Abstract

A thesaurus and an ontology provide a set of structured terms, phrases, and metadata, often in a hierarchical arrangement, that may be used to index, search, and mine documents. We describe the decisions that should be made when including a term, deciding whether a term should be subdivided into its subclasses, or determining which of more than one set of possible subclasses should be used. Based on retrospective measurements or estimates of future performance when using thesaurus terms in document ordering, decisions are made so as to maximize performance. These decisions may be used in the automatic construction of a thesaurus. The evaluation of an existing thesaurus is described, consistent with the decision criteria developed here. These kinds of user-focused decision-theoretic techniques may be applied to other hierarchical applications, such as faceted classification systems used in information architecture or the use of hierarchical terms in "breadcrumb navigation".