Search (26 results, page 1 of 2)

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Abstract

This article examines searcher behavior and affective response to a hypertext-based bibliographic information retrieval system called HyperLynx for searchers with different search skills and backgrounds. Search times and number of nodes visited were recorded for five specified search queries, and views of the system were recorded for each searcher. No significant differences were found in search times or user satisfaction with the system, indicating that a hypertext-based approach to bibliographic retrieval could be appropriate for a variety of searcher experience levels

Source

Journal of the American Society for Information Science. 46(1995) no.1, S.22-29

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Abstract

The domain of knowledge organization (KO) represents a foundational area of information science. One way to better understand the intellectual structure of the KO domain is to apply bibliometric methods to key contributors to the literature. This study analyzes the most prolific contributing authors to the journal Knowledge Organization, the sources they cite and the citations they receive for the period 1993 to 2016. The analyses were conducted using visualization outcomes of citation, co-citation and author bibliographic coupling analysis to reveal theoretical points of reference among authors and the most prominent research themes that constitute this scientific community. Birger Hjørland was the most cited author, and was situated at or near the middle of each of the maps based on different citation relationships. The proximities between authors resulting from the different citation relationships demonstrate how authors situate themselves intellectually through the citations they give and how other authors situate them through the citations received. There is a consistent core of theoretical references as well among the most productive authors. We observed a close network of scholarly communication between the authors cited in this core, which indicates the actual role of the journal Knowledge Organization as a space for knowledge construction in the area of knowledge organization.

Source

Knowledge organization. 45(2018) no.1, S.13-22

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Abstract

Author research impact was examined based on citer analysis (the number of citers as opposed to the number of citations) for 90 highly cited authors grouped into three broad subject areas. Citer-based outcome measures were also compared with more traditional citation-based measures for levels of association. The authors found that there are significant differences in citer-based outcomes among the three broad subject areas examined and that there is a high degree of correlation between citer and citation-based measures for all measures compared, except for two outcomes calculated for the social sciences. Citer-based measures do produce slightly different rankings of authors based on citer counts when compared to more traditional citation counts. Examples are provided. Citation measures may not adequately address the influence, or reach, of an author because citations usually do not address the origin of the citation beyond self-citations.

Date

28. 9.2010 12:54:22

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Abstract

Describes a study which investigated the affective response of 83 subjects to 2 versions of a hypertext-based bibliographic retrieval system. The objective of the study was to determine if subjects preferred searching a hypertext information retrieval (IR) system via traditional bibliographic links or via an enhanced set of linkages between structured records. The study also examined the utility of using factor analysis to explore subjects' affective responses to searching the 2 hypertext-based IR systems; explored the effect of experience on search outcome; and compared the effect of different types of linkages within the hypertext system. Findings reveal a complex relationship between system and user that is sometimes contradictory. Searchers found the systems to be usable or unusable in different ways indicating that further researchg is needed to isolate to specific features that searchers find frustrating or not in searching structured records via a hypertext-based IR system

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Abstract

In this issue Xie and Wolfram study the Wisconsin state digital library BadgerLink to determine the organizational factors that lead to different use requirements and the degree to which these are met, as well as impact on physical libraries. To this end, usage data from EBSCOhost and ProQuest logs for BadgerLink were analyzed, 313 Wisconsin libraries of all types were surveyed (76% response rate), and analyzed along with 81 responses to a voluntary web survey of end users. Heaviest users were K-12 schools and institutions of higher education. Heaviest use sites were the two largest state universities and the state's largest public library. Small libraries were infrequent users. Web survey respondents were mature working professionals. Sixty percent searched for specific information, but 46% reported browsing in subject areas. Libraries with dedicated Internet access reported more frequent usage than those with dial-up connection. Those who accessed from libraries reported more frequent use than those at work or at home. Libraries that trained end users reported more use, but the majority of the web survey respondents reported themselves as self-taught. Logs confirm reported subject interests. Three surrogates were requested for every full text document but full text availability is reported as the reason for use by 30% of users. Availability has led to the cancellation of subscriptions in many libraries that are important promoters of the service. A model will need to include interactions based upon the influence of each involved participant on the others. It will also need to include the extension of the activities of one participant to other participant organizations and the communication among these organizations.

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Abstract

The authors investigate the frequency distribution of the use of image tags in Web pages. Using data sampled from top level Web pages across five top level domains and from sample pages within individual websites, the authors model observed patterns in the frequency of image tag usage by fitting collected data distributions to different theoretical models used in informetrics. Models tested include the modified power law (MPL), Mandelbrot (MDB), generalized waring (GW), generalized inverse Gaussian-Poisson (GIGP), and generalized negative binomial (GNB) distributions. The GIGP provided the best fit for data sets for top level pages across the top level domains tested. The poor fits of the models to the observed data distributions from specific websites were due to the multimodal nature of the observed data sets. Mixtures of the tested models for the data sets provided better fits. The ability to effectively model Web page attributes, such as the distribution of the number of image tags used per page, is needed for accurate simulation models of Web page content, and makes it possible to estimate the number of requests needed to display the complete content of Web pages.

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Abstract

Session characteristics taken from large transaction logs of three Web search environments (academic Web site, public search engine, consumer health information portal) were modeled using cluster analysis to determine if coherent session groups emerged for each environment and whether the types of session groups are similar across the three environments. The analysis revealed three distinct clusters of session behaviors common to each environment: hit and run sessions on focused topics, relatively brief sessions on popular topics, and sustained sessions using obscure terms with greater query modification. The findings also revealed shifts in session characteristics over time for one of the datasets, away from hit and run sessions toward more popular search topics. A better understanding of session characteristics can help system designers to develop more responsive systems to support search features that cater to identifiable groups of searchers based on their search behaviors. For example, the system may identify struggling searchers based on session behaviors that match those identified in the current study to provide context sensitive help.

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Abstract

Zang and Wolfram compute the discrimination value for terms as the difference between the centroid value of all terms in the corpus and that value without the term in question, and suggest selection be made by comparing density changes with a visualization tool. The Distance Angle Retrieval Environment (DARE) visually projects a document or term space by presenting distance similarity on the X axis and angular similarity on the Y axis. Thus a document icon appearing close to the X axis would be relevant to reference points in terms of a distance similarity measure, while those close to the Y axis are relevant to reference points in terms of an angle based measure. Using 450 Associated Press news reports indexed by 44 distinct terms, the removal of the term ``Yeltsin'' causes the cluster to fall on the Y axis indicating a good discriminator. For an angular measure, cosine say, movement along the X axis to the left will signal good discrimination, as movement to the right will signal poor discrimination. A term density space could also be used. Most terms are shown to be indifferent discriminators. Different measures result in different choices as good and poor discriminators, as does the use of a term space rather than a document space. The visualization approach is clearly feasible, and provides some additional insights not found in the computation of a discrimination value.

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Abstract

Purpose - The purpose of this article is to examine interindexer consistency on a larger scale than other studies have done to determine if group consensus is reached by larger numbers of indexers and what, if any, relationships emerge between assigned terms. Design/methodology/approach - In total, 64 MLIS students were recruited to assign up to five terms to a document. The authors applied basic data modeling and the exploratory statistical techniques of multi-dimensional scaling (MDS) and hierarchical cluster analysis to determine whether relationships exist in indexing consistency and the coocurrence of assigned terms. Findings - Consistency in the assignment of indexing terms to a document follows an inverse shape, although it is not strictly power law-based unlike many other social phenomena. The exploratory techniques revealed that groups of terms clustered together. The resulting term cooccurrence relationships were largely syntagmatic. Research limitations/implications - The results are based on the indexing of one article by non-expert indexers and are, thus, not generalizable. Based on the study findings, along with the growing popularity of folksonomies and the apparent authority of communally developed information resources, communally developed indexes based on group consensus may have merit. Originality/value - Consistency in the assignment of indexing terms has been studied primarily on a small scale. Few studies have examined indexing on a larger scale with more than a handful of indexers. Recognition of the differences in indexing assignment has implications for the development of public information systems, especially those that do not use a controlled vocabulary and those tagged by end-users. In such cases, multiple access points that accommodate the different ways that users interpret content are needed so that searchers may be guided to relevant content despite using different terminology.

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Abstract

Transaction logs from four different Web-based information retrieval environments (bibliographic databank, OPAC, search engine, specialized search system) were analyzed for empirical regularities in search characteristics to determine whether users engage in different behaviors in different Web-based search environments. Descriptive statistics and relative frequency distributions related to term usage, query formulation, and session duration were tabulated. The analysis revealed that there are differences in these characteristics. Users were more likely to engage in extensive searching using the OPAC and specialized search system. Surprisingly, the bibliographic databank search environment resulted in the most parsimonious searching, more similar to a general search engine. Although on the surface Web-based search facilities may appear similar, users do engage in different search behaviors.

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Abstract

This study compares the range of disciplines of citing journal articles to determine how closely related journals assigned to the same Web of Science research area are. The frequency distribution of disciplines by citing articles provides a signature for a cited journal that permits it to be compared with other journals using similarity comparison techniques. As an initial exploration, citing discipline data for 40 high-impact-factor journals assigned to the "information science and library science" category of the Web of Science were compared across 5 time periods. Similarity relationships were determined using multidimensional scaling and hierarchical cluster analysis to compare the outcomes produced by the proposed citing discipline and established cocitation methods. The maps and clustering outcomes reveal that a number of journals in allied areas of the information science and library science category may not be very closely related to each other or may not be appropriately situated in the category studied. The citing discipline similarity data resulted in similar outcomes with the cocitation data but with some notable differences. Because the citing discipline method relies on a citing perspective different from cocitations, it may provide a complementary way to compare journal similarity that is less labor intensive than cocitation analysis.

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Abstract

In previous articles, we reported the state of Web searching in 1997 (Jansen, Spink, & Saracevic, 2000) and in 1999 (Spink, Wolfram, Jansen, & Saracevic, 2001). Such snapshot studies and statistics on Web use appear regularly (OCLC, 1999), but provide little information about Web searching trends. In this article, we compare and contrast results from our two previous studies of Excite queries' data sets, each containing over 1 million queries submitted by over 200,000 Excite users collected on 16 September 1997 and 20 December 1999. We examine how public Web searching changing during that 2-year time period. As Table 1 shows, the overall structure of Web queries in some areas did not change, while in others we see change from 1997 to 1999. Our comparison shows how Web searching changed incrementally and also dramatically. We see some moves toward greater simplicity, including shorter queries (i.e., fewer terms) and shorter sessions (i.e., fewer queries per user), with little modification (addition or deletion) of terms in subsequent queries. The trend toward shorter queries suggests that Web information content should target specific terms in order to reach Web users. Another trend was to view fewer pages of results per query. Most Excite users examined only one page of results per query, since an Excite results page contains ten ranked Web sites. Were users satisfied with the results and did not need to view more pages? It appears that the public continues to have a low tolerance of wading through retrieved sites. This decline in interactivity levels is a disturbing finding for the future of Web searching. Queries that included Boolean operators were in the minority, but the percentage increased between the two time periods. Most Boolean use involved the AND operator with many mistakes. The use of relevance feedback almost doubled from 1997 to 1999, but overall use was still small. An unusually large number of terms were used with low frequency, such as personal names, spelling errors, non-English words, and Web-specific terms, such as URLs. Web query vocabulary contains more words than found in large English texts in general. The public language of Web queries has its own and unique characteristics. How did Web searching topics change from 1997 to 1999? We classified a random sample of 2,414 queries from 1997 and 2,539 queries from 1999 into 11 categories (Table 2). From 1997 to 1999, Web searching shifted from entertainment, recreation and sex, and pornography, preferences to e-commerce-related topics under commerce, travel, employment, and economy. This shift coincided with changes in information distribution on the publicly indexed Web.

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Abstract

Reports results of a survey of US library schools to investigate the adoption, impact, and role of networking concepts and resources, such as the Internet, in the library and information science curriculum. Findings indicate that, to a large degree, educators have kept up with recent trends and tools in networking in a variety of courses. There was overwhelming consensus on the importance of networked information resources and access tools but less agreement on their places in the library and information science curriculum

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Abstract

This paper examines the influence of the works of Hope A. Olson by conducting an ego-centric informetric analysis of her published works. Publication and citation data were collected from Google Scholar and the Thomson Reuters Web of Science. Classic informetrics techniques were applied to the datasets including co-authorship analysis, citer analysis, citation and co-citation analysis and text-based analysis. Co-citation and text-based data were analyzed and visualized using VOSviewer and CiteSpace, respectively. The analysis of her citation identity reveals how Dr. Olson situates her own research within the knowledge landscape while the analysis of her citation image reveals how others have situated her work in relation to the authors with whom she has been co-cited. This reflection of Dr. Olson's research contributions reveals the influence of her scholarship not only on knowledge organization but other areas of library and information science and allied disciplines.

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Abstract

A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed.

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Abstract

Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more directly on the text of their published works. In this study we present static and dynamic word-based approaches using vector space modeling, as well as a topic-based approach based on latent Dirichlet allocation for mapping author research relatedness. Vector space modeling is used to define an author space consisting of works by a given author. Outcomes for the two word-based approaches and a topic-based approach for 50 prolific authors in library and information science are compared with more traditional author cocitation analysis using multidimensional scaling and hierarchical cluster analysis. The two word-based approaches produced similar outcomes except where two authors were frequent co-authors for the majority of their articles. The topic-based approach produced the most distinctive map.

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Abstract

Investigates how linkage environments in a hypertext based bibliographic retrieval system affect retrieval performance for novice and experienced searchers, 2 systems, 1 with inter record linkages to authors and descriptors and 1 that also included title and abstract keywords, were tested. No significant differences in retrieval performance and system usage were found for most search tests. The enhanced system did provide better performance where title and abstract keywords provided the most direct access to relevant records. The findings have implications for the design of bilbiographic information retrieval systems using hypertext linkages

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Abstract

The emergence of general audience digital libraries (GADLs) defines a context that represents a hybrid of both "traditional" IR, using primarily bibliographic resources provided by database vendors, and "popular" IR, exemplified by public search systems available on the World Wide Web. Findings of a study investigating end-user searching and response to a GADL are reported. Data collected from a Web-based end-user survey and data logs of resource usage for a Web-based GADL were analyzed for user characteristics, patterns of access and use, and user feedback. Cross-tabulations using respondent demographics revealed several key differences in how the system was used and valued by users of different age groups. Older users valued the service more than younger users and engaged in different searching and viewing behaviors. The GADL more closely resembles traditional retrieval systems in terms of content and purpose of use, but is more similar to popular IR systems in terms of user behavior and accessibility. A model that defines the dual context of the GADL environment is derived from the data analysis and existing IR models in general and other specific contexts. The authors demonstrate the distinguishing characteristics of this IR context, and discuss implications for the development and evaluation of future GADLs to accommodate a variety of user needs and expectations.

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Abstract

The authors investigated 11 sports-related query keywords extracted from a public search engine query log to better understand sports-related information seeking on the Internet. After the query log contents were cleaned and query data were parsed, popular sports-related keywords were identified, along with frequently co-occurring query terms associated with the identified keywords. Relationships among each sports-related focus keyword and its related keywords were characterized and grouped using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two approaches were synthesized in a visual context by highlighting the results of the hierarchical clustering analysis in the visual MDS configuration. Important events, people, subjects, merchandise, and so on related to a sport were illustrated, and relationships among the sports were analyzed. A small-scale comparative study of sports searches with and without term assistance was conducted. Searches that used search term assistance by relying on previous query term relationships outperformed the searches without the search term assistance. The findings of this study provide insights into sports information seeking behavior on the Internet. The developed method also may be applied to other query log subject areas.

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Abstract

Queries submitted to the Excite search engine were analyzed for subject content based on the cooccurrence of terms within multiterm queries. More than 1000 of the most frequently cooccurring term pairs were categorized into one or more of 30 developed subject areas. Subject area frequencies and their cooccurrences with one another were tallied and analyzed using hierarchical cluster analysis and multidimensional scaling. The cluster analyses revealed several anticipated and a few unanticipated groupings of subjects, resulting in several well-defined high-level clusters of broad subject areas. Multidimensional scaling of subject cooccurrences revealed similar relationships among the different subject categories. Applications that arise from a better understanding of the topics users search and their relationships are discussed