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  • × author_ss:"Lu, W."
  1. Lu, W.; Ding, H.; Jiang, J.: ¬A document expansion framework for tag-based image retrieval (2018) 0.03 
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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
  2. Jones, L.M.; Wright, K.D.; Jack, A.I.; Friedman, J.P.; Fresco, D.M.; Veinot, T.; Lu, W.; Moore, S.M.: ¬The relationships between health information behavior and neural processing in african americans with prehypertension : color or text (2019) 0.01 
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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.
  3. Zhang, L.; Lu, W.; Yang, J.: LAGOS-AND : a large gold standard dataset for scholarly author name disambiguation (2023) 0.01 
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    Date
    22. 1.2023 18:40:36
  4. Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023) 0.01 
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    Date
    22. 6.2023 14:55:20

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