Search (10 results, page 1 of 1)

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Abstract

Purpose - The purpose of this paper is to introduce a new similarity method to gauge the differences between two subject hierarchical structures. Design/methodology/approach - In the proposed similarity measure, nodes on two hierarchical structures are projected onto a two-dimensional space, respectively, and both structural similarity and subject similarity of nodes are considered in the similarity between the two hierarchical structures. The extent to which the structural similarity impacts on the similarity can be controlled by adjusting a parameter. An experiment was conducted to evaluate soundness of the measure. Eight experts whose research interests were information retrieval and information organization participated in the study. Results from the new measure were compared with results from the experts. Findings - The evaluation shows strong correlations between the results from the new method and the results from the experts. It suggests that the similarity method achieved satisfactory results. Practical implications - Hierarchical structures that are found in subject directories, taxonomies, classification systems, and other classificatory structures play an extremely important role in information organization and information representation. Measuring the similarity between two subject hierarchical structures allows an accurate overarching understanding of the degree to which the two hierarchical structures are similar. Originality/value - Both structural similarity and subject similarity of nodes were considered in the proposed similarity method, and the extent to which the structural similarity impacts on the similarity can be adjusted. In addition, a new evaluation method for a hierarchical structure similarity was presented.

Date

8. 4.2015 16:22:13

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Content

We investigate the influence of culture and identity (geographic location) on the constitution of a specific research field. Using as case study the Sloan Digital Sky Survey (SDSS) project in the Astronomy field, we analyzed texts from bibliographic records of publications along three cultural and geographic axes: US only publications, non-US publications and international collaboration. Using three text mining systems (CiteSpace, TermWatch and PEx), we were able to automatically identify the topics specific to each cultural and geographic region as well as isolate the core research topics common to all geographic zones. The results tended to show that US-only and non-US research in this field shared more commonalities with international collaboration than with one another, thus indicating that the former two (US-only and non-US) research focused on rather distinct topics.

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Abstract

We investigated a topic-based navigation guidance system in the World Health Organization portal, compared the link connection network and the semantic connection network derived from the guidance system, analyzed the characteristics of the 2 networks from the perspective of the node centrality (in_closeness, out_closeness, betweenness, in_degree, and out_degree), and provided the suggestions to optimize and enhance the topic-based navigation guidance system. A mixed research method that combines the social network analysis method, clustering analysis method, and inferential analysis methods was used. The clustering analysis results of the link connection network were quite different from those of the semantic connection network. There were significant differences between the link connection network and the semantic network in terms of density and centrality. Inferential analysis results show that there were no strong correlations between the centrality of a node and its topic information characteristics. Suggestions for enhancing the navigation guidance system are discussed in detail. Future research directions, such as application of the same research method presented in this study to other similar public health portals, are also included.

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Abstract

Bibliometric analysis based on literature in the Web of Science (WOS) has become an increasingly popular method for visualizing the structure of scientific fields. Keywords Plus and Author Keywords are commonly selected as units of analysis, despite the limited research evidence demonstrating the effectiveness of Keywords Plus. This study was conceived to evaluate the efficacy of Keywords Plus as a parameter for capturing the content and scientific concepts presented in articles. Using scientific papers about patient adherence that were retrieved from WOS, a comparative assessment of Keywords Plus and Author Keywords was performed at the scientific field level and the document level, respectively. Our search yielded more Keywords Plus terms than Author Keywords, and the Keywords Plus terms were more broadly descriptive. Keywords Plus is as effective as Author Keywords in terms of bibliometric analysis investigating the knowledge structure of scientific fields, but it is less comprehensive in representing an article's content.

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Abstract

This article presents a distance and angle similarity measure. The integrated similarity measure takes the strenghts of both the distance and direction of measured documents into account. This article analyzes the features of the similarity measure by comparing it with the traditional distance-based similarity measure and the cosine measure, providing the iso-similarity contour, investigating the impacts of the parameters and variables on the new similarity measure. It also gives the further research issues on the topic

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Abstract

Comparative study of knowledge management (KM) promises to lead to more effective knowledge use in all cultural environments. This pilot study compares KM priorities, needs, tools, and administrative structure components in large Chinese and American universities. General KM theory and literature related to KM in higher education are analyzed to develop the four components of the study. Comparative differences in KM practice at large Chinese and American universities are analyzed for each component. A correlation matrix reveals statistically significant co-variation among all but one of the study components. Four conclusions related to comparative KM and suggestions for future research are presented.

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Abstract

This entry describes two important classes of systems that facilitate the sharing of recommendations and expertise. Recommender systems suggest items of potential interest to individuals who do not have personal experience with the items. Expert locator systems, an important subset of recommender systems, help find people with the appropriate skills, knowledge, or expertise to meet a particular need. Research related to each of these systems is relatively new and extremely active. The use of these systems is likely to continue increasing as more and more activity is implicitly captured online, making it possible to automatically identify experts, and capture preferences that can be used to recommend items.

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Abstract

The authors introduce an information visualization model, WebStar, for hyperlink-based information systems. Hyperlinks within a hyperlink-based document can be visualized in a two-dimensional visual space. All links are projected within a display sphere in the visual space. The relationship between a specified central document and its hyperlinked documents is visually presented in the visual space. In addition, users are able to define a group of subjects and to observe relevance between each subject and all hyperlinked documents via movement of that subject around the display sphere center. WebStar allows users to dynamically change an interest center during navigation. A retrieval mechanism is developed to control retrieved results in the visual space. Impact of movement of a subject on the visual document distribution is analyzed. An ambiguity problem caused by projection is discussed. Potential applications of this visualization model in information retrieval are included. Future research directions on the topic are addressed.

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Abstract

The authors of this paper investigate terms of consumers' diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers' perspective, and reveal users' diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included.

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Abstract

We investigated a subject directory in the US Agriculture Department-Economic Research Service portal. Parent-child relationships, related connections among the categories, and related connections among the subcategories in the subject directory were optimized using social network analysis. The optimization results were assessed by both density analysis and edge strength analysis methods. In addition, the results were evaluated by domain experts. From this study, it is recommended that four subcategories be switched from their original four categories into two different categories as a result of the parent-child relationship optimization.?It is also recommended that 132 subcategories be moved to 40 subcategories and that eight categories be moved to two categories as a result of the related connection optimization. The findings show that optimization boosted the densities of the optimized categories, and the recommended connections of both the related categories and subcategories were stronger than the existing connections of the related categories and subcategories. This paper provides visual displays of the optimization analysis as well as suggestions to enhance the subject directory of this portal.