Abstract not found

In this paper we show that in advanced information retrieval (IR) applications capa- bilities for data aggregation, transitive computation and NF 2 (non-first normal form) relational computation are often necessary at the same time. We demonstrate that complex objects are naturally modeled as NF 2 relations whereas structures like hi- erarchical thesauri must be modeled for transitive computation. Transitive process- ing cannot be supported by stmcturally static structures like NF 2 relations. We pres- ent a truly declarative query interface, which integrates data aggregation, transitive computation and NF 2 relational computation. Thus the interface supports the re- trieval and structural manipulation of complex objects (e.g., documents, and biblio- graphic references), their retrieval through transitive relationships (e.g., thesauri, citations) and data aggregation based on their components (e.g., citation counts, author productivity). Most importantly, users can formulate queries on a high ab- straction level without mastering actual programming or database techniques.

This paper describes the generic principles of Decomate-II's Concept Browser. It discusses the three main problems in using a thesaurus or conceptual network to help users formulate database queries: the network maintenance problem, the network navigation problem, and the network-to-database mapping problem. Possible solutions to all these problems are proposed, based on previous experiences with concept network systems. Care is taken to keep the resulting system suitable for production use in an existing library environment based on Boolean keyword retrieval from a large collection with uncontrolled vocabulary. Keywords: Semantic network, thesaurus, conceptual network, knowledge navigation, lexicon, conceptual modeling, topic browsing, document retrieval, Decomate-II. URL: http://infolab.kub.nl/prj/decomate 1 Introduction Much work in the area of indexing and retrieval concentrates on constructing effective and efficient algorithms to find a set of `interesting' documents in a larg...

Thesauri are used to provide controlled vocabularies for resource classification. Their use can greatly assist document discovery because thesauri man date a consistent shared terminology for describing documents. A particular thesaurus classifies documents according to an information community's needs. As a result, there are many different thesaural schemas. This has led to a proliferation of schema-specific thesaural systems. In our research, we exploit schematic regularities to design a generic thesaural ontology and specify it as a markup language. The language provides a common representational framework in which to encode the idiosyncrasies of specific thesauri. This approach has several advantages: it offers consistent syntax and semantics in which to express thesauri; it allows general purpose thesaural applications to leverage many thesauri; and it supports a single thesaural user interface by which information communities can consistently organise, store and retrieve electronic documents. Keywords: Electronic Documents, Metadata, Ontology, Thesaurus, XML 2

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

At the moment, there is a need for new knowledge representation using Thesaurus or Ontologies because of the need to reuse knowledge. In this paper, a Software Architecture knowledge representation is created, for that purpose a manual and automatic methodology for creating it is used. A new manual methodology is provided in the paper. CAKE (Computer Aided Knowledge Environment) is the automatic process used as automatic methodology. The result is the first thesaurus in English for the Software Architecture Domain using the new manual methodology presented in the paper and the first ontology in Spanish for the Software Architecture Domain using the automatic methodology.

Abstract. Searching specialized collections, such as biomedical literature, typically requires intimate knowledge of a specialized terminology. Hence, it can be a disappointing experience: not knowing the right terms to use and being unaware of synonyms or variations in terminology might result in low recall scores. We study the role of a thesaurus in the biomedical information retrieval process. We start by giving a description of vocabulary mismatch problems between natural language queries and relevant documents in biomedical literature search; we provide a detailed case study and observe the impact of vocabulary mismatch problems on retrieval effectiveness. Additionally, we analyze the associated MeSH thesaurus terms used to index the documents in the collection. Based on our observations, we propose a method for exploiting the MeSH thesaurus to improve retrieval effectiveness and, more specifically, to increase recall. We carry out a series of thesaurus-based retrieval experiments that show substantial performance improvements. We conclude with a detailed analysis of the retrieval results. 1

This is a reformatted version of the original dissertation, and

This paper discusses evaluation methods based on the use of non-dichotomous relevance judgements in information retrieval (IR) experiments. It is argued that evaluation methods should credit IR methods for their ability to retrieve highly relevant documents. This is deskable from the user's point of view in modem large IR environments. The proposed methods are (1) a novel application of P-R curves and average precision computations based on separate recall bases for documents of different degrees of relevance, and (2) two novel measures computing the cumulated gain the user obtains by examining the retrieval result up to a given ranked position. We then demonstrate the use of these evaluation methods in a case study on the effectiveness of query types, based on combinations of query structures and expansion, in retrieving documents of various degrees of relevance. Query expansion is based on concepts, which are selected from a conceptual model, and then expanded by semantic relationships given in the model. The test is run with a best match retrieval system (inQuery) in a text database consisting of newspaper articles.

This document describes the various modules that provide the Advanced Access facilities to the Decomate-II system. It contains the argumentation for the design and the implementation intentions as far as currently can be decided.