Search (4 results, page 1 of 1)

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Abstract

Purpose The purpose of this paper is to utilize document expansion techniques for improving image representation and retrieval. This paper proposes a concise framework for tag-based image retrieval (TBIR). Design/methodology/approach The proposed approach includes three core components: a strategy of selecting expansion (similar) images from the whole corpus (e.g. cluster-based or nearest neighbor-based); a technique for assessing image similarity, which is adopted for selecting expansion images (text, image, or mixed); and a model for matching the expanded image representation with the search query (merging or separate). Findings The results show that applying the proposed method yields significant improvements in effectiveness, and the method obtains better performance on the top of the rank and makes a great improvement on some topics with zero score in baseline. Moreover, nearest neighbor-based expansion strategy outperforms the cluster-based expansion strategy, and using image features for selecting expansion images is better than using text features in most cases, and the separate method for calculating the augmented probability P(q|RD) is able to erase the negative influences of error images in RD. Research limitations/implications Despite these methods only outperform on the top of the rank instead of the entire rank list, TBIR on mobile platforms still can benefit from this approach. Originality/value Unlike former studies addressing the sparsity, vocabulary mismatch, and tag relatedness in TBIR individually, the approach proposed by this paper addresses all these issues with a single document expansion framework. It is a comprehensive investigation of document expansion techniques in TBIR.

Date

20. 1.2015 18:30:22

Type

a

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Abstract

Information behavior may enhance hypertension self-management in African Americans. The goal of this substudy was to examine the relationships between measures of self-reported health information behavior and neural measures of health information processing in a sample of 19 prehypertensive African Americans (mean age = 52.5, 52.6% women). We measured (a) health information seeking, sharing, and use (surveys) and (b) neural activity using functional magnetic resonance imaging (fMRI) to assess response to health information videos. We hypothesized that differential activation (comparison of analytic vs. empathic brain activity when watching a specific type of video) would indicate better function in three, distinct cognitive domains: (a) Analytic Network, (b) Default Mode Network (DMN), and (c) ventromedial prefrontal cortex (vmPFC). Scores on the information sharing measure (but not seeking or use) were positively associated with differential activation in the vmPFC (rs = .53, p = .02) and the DMN (rs = .43, p = .06). Our findings correspond with previous work indicating that activation of the DMN and vmPFC is associated with sharing information to persuade others and with behavior change. Although health information is commonly conveyed as detached and analytic in nature, our findings suggest that neural processing of socially and emotionally salient health information is more closely associated with health information sharing.

Type

a

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Type

a

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Abstract

Author-selected keywords have been widely utilized for indexing, information retrieval, bibliometrics and knowledge organization in previous studies. However, few studies exist con-cerning how author-selected keywords function semantically in scientific manuscripts. In this paper, we investigated this problem from the perspective of term function (TF) by devising indica-tors of the diversity and symmetry of keyword term functions in papers, as well as the intensity of individual term functions in papers. The data obtained from the whole Journal of Informetrics(JOI) were manually processed by an annotation scheme of key-word term functions, including "research topic," "research method," "research object," "research area," "data" and "others," based on empirical work in content analysis. The results show, quantitatively, that the diversity of keyword term function de-creases, and the irregularity increases with the number of author-selected keywords in a paper. Moreover, the distribution of the intensity of individual keyword term function indicated that no significant difference exists between the ranking of the five term functions with the increase of the number of author-selected keywords (i.e., "research topic" > "research method" > "research object" > "research area" > "data"). The findings indicate that precise keyword related research must take into account the dis-tinct types of author-selected keywords.

Type

a