Search (52 results, page 1 of 3)

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Abstract

The SAC Subcommittee on Subject Relationships/Reference Structures was authorized at the 1995 Midwinter Meeting and appointed shortly before Annual Conference. Its creation was one result of a discussion of how (and why) to promote the display and use of broader-term subject heading references, and its charge reads as follows: To investigate: (1) the kinds of relationships that exist between subjects, the display of which are likely to be useful to catalog users; (2) how these relationships are or could be recorded in authorities and classification formats; (3) options for how these relationships should be presented to users of online and print catalogs, indexes, lists, etc. By the summer 1996 Annual Conference, make some recommendations to SAC about how to disseminate the information and/or implement changes. At that time assess the need for additional time to investigate these issues. The Subcommittee's work on each of the imperatives in the charge was summarized in a report issued at the 1996 Annual Conference (Appendix A). Highlights of this work included the development of a taxonomy of 165 subject relationships; a demonstration that, using existing MARC coding, catalog systems could be programmed to generate references they do not currently support; and an examination of reference displays in several CD-ROM database products. Since that time, work has continued on identifying term relationships and display options; on tracking research, discussion, and implementation of subject relationships in information systems; and on compiling a list of further research needs.

Content

Enthält: Appendix A: Subcommittee on Subject Relationships/Reference Structures - REPORT TO THE ALCTS/CCS SUBJECT ANALYSIS COMMITTEE - July 1996 Appendix B (part 1): Taxonomy of Subject Relationships. Compiled by Dee Michel with the assistance of Pat Kuhr - June 1996 draft (alphabetical display) (Separat in: http://web2.ala.org/ala/alctscontent/CCS/committees/subjectanalysis/subjectrelations/msrscu2.pdf) Appendix B (part 2): Taxonomy of Subject Relationships. Compiled by Dee Michel with the assistance of Pat Kuhr - June 1996 draft (hierarchical display) Appendix C: Checklist of Candidate Subject Relationships for Information Retrieval. Compiled by Dee Michel, Pat Kuhr, and Jane Greenberg; edited by Greg Wool - June 1997 Appendix D: Review of Reference Displays in Selected CD-ROM Abstracts and Indexes by Harriette Hemmasi and Steven Riel Appendix E: Analysis of Relationships in Six LC Subject Authority Records by Harriette Hemmasi and Gary Strawn Appendix F: Report of a Preliminary Survey of Subject Referencing in OPACs by Gregory Wool Appendix G: LC Subject Referencing in OPACs--Why Bother? by Gregory Wool Appendix H: Research Needs on Subject Relationships and Reference Structures in Information Access compiled by Jane Greenberg and Steven Riel with contributions from Dee Michel and others edited by Gregory Wool Appendix I: Bibliography on Subject Relationships compiled mostly by Dee Michel with additional contributions from Jane Greenberg, Steven Riel, and Gregory Wool

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Abstract

We present a deductive data model for concept-based query expansion. It is based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matching models at the occurrence level. Each model specifies the matching of the expression in database indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for environments providing heterogeneous IR systems. Expansion is controlled by adjustable matching reliability.

Source

Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al

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Abstract

The study reported here investigated the query expansion behavior of end-users interacting with a thesaurus-enhanced search system on the Web. Two groups, namely academic staff and postgraduate students, were recruited into this study. Data were collected from 90 searches performed by 30 users using the OVID interface to the CAB abstracts database. Data-gathering techniques included questionnaires, screen capturing software, and interviews. The results presented here relate to issues of search-topic and search-term characteristics, number and types of expanded queries, usefulness of thesaurus terms, and behavioral differences between academic staff and postgraduate students in their interaction. The key conclusions drawn were that (a) academic staff chose more narrow and synonymous terms than did postgraduate students, who generally selected broader and related terms; (b) topic complexity affected users' interaction with the thesaurus in that complex topics required more query expansion and search term selection; (c) users' prior topic-search experience appeared to have a significant effect on their selection and evaluation of thesaurus terms; (d) in 50% of the searches where additional terms were suggested from the thesaurus, users stated that they had not been aware of the terms at the beginning of the search; this observation was particularly noticeable in the case of postgraduate students.

Date

22. 7.2006 16:32:43

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Abstract

The authors present a model of information searching in thesaurus-enhanced search systems, intended as a reference model for system developers. The model focuses on user-system interaction and charts the specific stages of searching an indexed collection with a thesaurus. It was developed based on literature, findings from empirical studies, and analysis of existing systems. The model describes in detail the entities, processes, and decisions when interacting with a search system augmented with a thesaurus. A basic search scenario illustrates this process through the model. Graphical and textual depictions of the model are complemented by a concise matrix representation for evaluation purposes. Potential problems at different stages of the search process are discussed, together with possibilities for system developers. The aim is to set out a framework of processes, decisions, and risks involved in thesaurus-based search, within which system developers can consider potential avenues for support.

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Abstract

This paper addresses the problem of information discovery in large collections of text. For users, one of the key problems in working with such collections is determining where to focus their attention. In selecting documents for examination, users must be able to formulate reasonably precise queries. Queries that are too broad will greatly reduce the efficiency of information discovery efforts by overwhelming the users with peripheral information. In order to formulate efficient queries, a mechanism is needed to automatically alert users regarding potentially interesting information contained within the collection. This paper presents the results of an experiment designed to test one approach to generation of such alerts. The technique of latent semantic indexing (LSI) is used to identify relationships among entities of interest. Entity extraction software is used to pre-process the text of the collection so that the LSI space contains representation vectors for named entities in addition to those for individual terms. In the LSI space, the cosine of the angle between the representation vectors for two entities captures important information regarding the degree of association of those two entities. For appropriate choices of entities, determining the entity pairs with the highest mutual cosine values yields valuable information regarding the contents of the text collection. The test database used for the experiment consists of 150,000 news articles. The proposed approach for alert generation is tested using a counterterrorism analysis example. The approach is shown to have significant potential for aiding users in rapidly focusing on information of potential importance in large text collections. The approach also has value in identifying possible use of aliases.

Source

Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]

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Abstract

Describes the OKAPI projects and OKAPI's development as an experimental online catalogue system over 10 years, first at the University of Westminster (formerly the Polytechnique of Central London) and subsequently at City University, London. The 1st OKAPI project in 1984 introduced 'best match' retrieval and focused on the user interface design. The 2nd investigated word stemming, spelling correction and cross reference tables as retrieval aids. A comparative study of 2 library catalogues was undertaken in 1987, while in 1988 query expansion and relevance feedback were introduced and evaluated by laboratory tests. In 1990 live evaluation of automatic query expansion was carried out and in 1993 subject enhancement of bibliographic records was investigated. The latest project has examined the design of a graphical user interface to support interactive query expansion. Discusses the research and evaluation of each project

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Date

22. 2.2003 17:25:39
22. 2.2003 18:17:40

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Date

30. 3.2001 13:32:22

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Abstract

The growing availability of data in electronic form, the expansion of the World Wide Web and the accessibility of computational methods for large-scale data processing have allowed researchers in Information Retrieval (IR) to design systems which can effectively and efficiently constrain search within the boundaries given by context, thus transforming classical search into contextual search. Contextual Search: A Computational Framework introduces contextual search within a computational framework based on contextual variables, contextual factors and statistical models. It describes how statistical models can process contextual variables to infer the contextual factors underlying the current search context. It also provides background to the subject by: placing it among other surveys on relevance, interaction, context, and behaviour; providing a description of the contextual variables used for implementing the statistical models which represent and predict relevance and contextual factors; and providing an overview of the evaluation methodologies and findings relevant to this subject. Contextual Search: A Computational Framework is a highly recommended read, both for beginners who are embarking on research in this area and as a useful reference for established IR researchers.

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Abstract

Discusses the ways in which systems and/or users formulate and reformulate searches in documents retrieval systems (DRS), database management systems (DBMS) and expert systems (ES). Concludes that query formulation and reformulation has been neglected in these fields

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Abstract

This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.

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Abstract

Evaluates the retrieval effectiveness of query expansion strategies on a test collection of the medical database MEDLINE using Cornell University's SMART retrieval system. Tests 3 expansion strategies for their ability to identify appropriate MeSH terms for user queries. Compares retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a collection of 75 queries and 2.334 Medline citations. Recommends query expansions using retrieval feedback for adding MeSH search terms to a user's initial query

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Date

1. 2.2016 18:25:22

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Date

1. 2.2016 18:25:22

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou

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Date

22. 7.2006 17:56:22

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Abstract

One of the major causes of search failures in information retrieval systems is vocabulary mismatch. Presents a solution to the vocabulary problem through 2 strategies known as term suggestion (TS) and term relevance feedback (TRF). In TS, collection specific terms are extracted from the text collection. These terms and their frequencies constitute the keyword database for suggesting terms in response to users' queries. One effect of this term suggestion is that it functions as a dynamic directory if the query is a general term that contains broad meaning. In term relevance feedback, terms extracted from the top ranked documents retrieved from the previous query are shown to users for relevance feedback. In the experiment, interactive TS provides very high precision rates while achieving similar recall rates as n-gram matching. Local TRF achieves improvement in both precision and recall rate in a full text news database and degrades slightly in recall rate in bibliographic databases due to the very limited source of information for feedback. In terms of Rijsbergen's combined measure of recall and precision, both TS and TRF achieve better performance than n-gram matching, which implies that the greater improvement in precision rate compensates the slight degradation in recall rate for TS and TRF

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Abstract

In the field of electronic publishing, encyclopedias represent a unique sort of text for investigating advanced methods of navigation. The user of an electronic excyclopedia normally expects special methods for accessing the entries in an encyclopedia database. Navigation through printed encyclopedias in the traditional sense focuses on the alphabetic order of the entries. In electronic encyclopedias, however, thematic structuring of lemmas and, of course, extensive (hyper-) linking mechanisms have been added. This paper will focus on showing developments, which go beyond these navigational strucutres. We will concentrate on the semantic space formed by lemmas to build a network of semantic distances and thematic trails through the encyclopedia

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Abstract

There are many advantages for Digital Libraries in indexing with classifications or thesauri, but some current disincentive in the lack of flexible retrieval tools that deal with compound descriptors. This demonstration of a research prototype illustrates a matching function for compound descriptors, or multi-concept subject headings, that does not rely on exact matching but incorporates term expansion via thesaurus semantic relationships to produce ranked results that take account of missing and partially matching terms. The matching function is based on a measure of semantic closeness between terms.The work is part of the EPSRC funded FACET project in collaboration with the UK National Museum of Science and Industry (NMSI) which includes the National Railway Museum. An export of NMSI's Collections Database is used as the dataset for the research. The J. Paul Getty Trust's Art and Architecture Thesaurus (AAT) is the main thesaurus in the project. The AAT is a widely used thesaurus (over 120,000 terms). Descriptors are organised in 7 facets representing separate conceptual classes of terms.The FACET application is a multi tiered architecture accessing a SQL Server database, with an OLE DB connection. The thesauri are stored as relational tables in the Server's database. However, a key component of the system is a parallel representation of the underlying semantic network as an in-memory structure of thesaurus concepts (corresponding to preferred terms). The structure models the hierarchical and associative interrelationships of thesaurus concepts via weighted poly-hierarchical links. Its primary purpose is real-time semantic expansion of query terms, achieved by a spreading activation semantic closeness algorithm. Queries with associated results are stored persistently using XML format data. A Visual Basic interface combines a thesaurus browser and an initial term search facility that takes into account equivalence relationships. Terms are dragged to a direct manipulation Query Builder which maintains the facet structure.