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  • × year_i:[2010 TO 2020}
  • × author_ss:"Liu, Y."
  1. Liu, Y.; Shi, J.; Chen, Y.: Patient-centered and experience-aware mining for effective adverse drug reaction discovery in online health forums (2018) 0.00 
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    Abstract
    Adverse Drug Reactions (ADRs) have become a serious health problem and even a leading cause of death in the United States. Pre-marketing clinical trials and traditional post-marketing surveillance using voluntary and spontaneous report systems are insufficient for ADR detection. On the other hand, online health forums provide valuable evidences in a large scale and in a timely fashion through the active participation of patients, caregivers, and doctors. In this article, we present patient-centered and experience-aware mining framework for effective ADR discovery using online health forum data. Our experimental evaluation with both an official ADR knowledge base and human-annotated ground truth verifies the effectiveness of the proposed method for ADR discovery.
  2. Liu, Y.; Rousseau, R.: Citation analysis and the development of science : a case study using articles by some Nobel prize winners (2014) 0.00 
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    Date
    29. 1.2014 16:31:35
  3. Liu, Y.; Li, W.; Huang, Z.; Fang, Q.: ¬A fast method based on multiple clustering for name disambiguation in bibliographic citations (2015) 0.00 
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    Abstract
    Name ambiguity in the context of bibliographic citation affects the quality of services in digital libraries. Previous methods are not widely applied in practice because of their high computational complexity and their strong dependency on excessive attributes, such as institutional affiliation, research area, address, etc., which are difficult to obtain in practice. To solve this problem, we propose a novel coarse-to-fine framework for name disambiguation which sequentially employs 3 common and easily accessible attributes (i.e., coauthor name, article title, and publication venue). Our proposed framework is based on multiple clustering and consists of 3 steps: (a) clustering articles by coauthorship and obtaining rough clusters, that is fragments; (b) clustering fragments obtained in step 1 by title information and getting bigger fragments; (c) and clustering fragments obtained in step 2 by the latent relations among venues. Experimental results on a Digital Bibliography and Library Project (DBLP) data set show that our method outperforms the existing state-of-the-art methods by 2.4% to 22.7% on the average pairwise F1 score and is 10 to 100 times faster in terms of execution time.
  4. Lim, S.C.J.; Liu, Y.; Lee, W.B.: Multi-facet product information search and retrieval using semantically annotated product family ontology (2010) 0.00 
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    Abstract
    With the advent of various services and applications of Semantic Web, semantic annotation has emerged as an important research topic. The application of semantically annotated ontology had been evident in numerous information processing and retrieval tasks. One of such tasks is utilizing the semantically annotated ontology in product design which is able to suggest many important applications that are critical to aid various design related tasks. However, ontology development in design engineering remains a time consuming and tedious task that demands considerable human efforts. In the context of product family design, management of different product information that features efficient indexing, update, navigation, search and retrieval across product families is both desirable and challenging. For instance, an efficient way of retrieving timely information on product family can be useful for tasks such as product family redesign and new product variant derivation when requirements change. However, the current research and application of information search and navigation in product family is mostly limited to its structural aspect which is insufficient to handle advanced information search especially when the query targets at multiple aspects of a product. This paper attempts to address this problem by proposing an information search and retrieval framework based on the semantically annotated multi-facet product family ontology. Particularly, we propose a document profile (DP) model to suggest semantic tags for annotation purpose. Using a case study of digital camera families, we illustrate how the faceted search and retrieval of product information can be accomplished. We also exemplify how we can derive new product variants based on the designer's query of requirements via the faceted search and retrieval of product family information. Lastly, in order to highlight the value of our current work, we briefly discuss some further research and applications in design decision support, e.g. commonality analysis and variety comparison, based on the semantically annotated multi-facet product family ontology.
  5. Lim, S.C.J.; Liu, Y.; Lee, W.B.: ¬A methodology for building a semantically annotated multi-faceted ontology for product family modelling (2011) 0.00 
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    Abstract
    Product family design is one of the prevailing approaches in realizing mass customization. With the increasing number of product offerings targeted at different market segments, the issue of information management in product family design, that is related to an efficient and effective storage, sharing and timely retrieval of design information, has become more complicated and challenging. Product family modelling schema reported in the literature generally stress the component aspects of a product family and its analysis, with a limited capability to model complex inter-relations between physical components and other required information in different semantic orientations, such as manufacturing, material and marketing wise. To tackle this problem, ontology-based representation has been identified as a promising solution to redesign product platforms especially in a semantically rich environment. However, ontology development in design engineering demands a great deal of time commitment and human effort to process complex information. When a large variety of products are available, particularly in the consumer market, a more efficient method for building a product family ontology with the incorporation of multi-faceted semantic information is therefore highly desirable. In this study, we propose a methodology for building a semantically annotated multi-faceted ontology for product family modelling that is able to automatically suggest semantically-related annotations based on the design and manufacturing repository. The six steps of building such ontology: formation of product family taxonomy; extraction of entities; faceted unit generation and concept identification; facet modelling and semantic annotation; formation of a semantically annotated multi-faceted product family ontology (MFPFO); and ontology validation and evaluation are discussed in detail. Using a family of laptop computers as an illustrative example, we demonstrate how our methodology can be deployed step by step to create a semantically annotated MFPFO. Finally, we briefly discuss future research issues as well as interesting applications that can be further pursued based on the MFPFO developed.
  6. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.00 
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    Date
    20. 1.2015 18:30:22

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