Search (10 results, page 1 of 1)

  • × author_ss:"Song, M."
  • × year_i:[2010 TO 2020}
  1. Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.00 
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    Date
    22. 8.2014 16:52:04
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833
  2. Song, M.; Kang, K.; An, J.Y.: Investigating drug-disease interactions in drug-symptom-disease triples via citation relations (2018) 0.00 
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    Abstract
    With the growth in biomedical literature, the necessity of extracting useful information from the literature has increased. One approach to extracting biomedical knowledge involves using citation relations to discover entity relations. The assumption is that citation relations between any two articles connect knowledge entities across the articles, enabling the detection of implicit relationships among biomedical entities. The goal of this article is to examine the characteristics of biomedical entities connected via intermediate entities using citation relations aided by text mining. Based on the importance of symptoms as biomedical entities, we created triples connected via citation relations to identify drug-disease pairs with shared symptoms as intermediate entities. Drug-disease interactions built via citation relations were compared with co-occurrence-based interactions. Several types of analyses were adopted to examine the properties of the extracted entity pairs by comparing them with drug-disease interaction databases. We attempted to identify the characteristics of drug-disease pairs through citation relations in association with biomedical entities. The results showed that the citation relation-based approach resulted in diverse types of biomedical entities and preserved topical consistency. In addition, drug-disease pairs identified only via citation relations are interesting for clinical trials when they are examined using BITOLA.
    Date
    1.11.2018 18:19:22
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.11, S.1355-1368
  3. Ho, S.M.; Bieber, M.; Song, M.; Zhang, X.: Seeking beyond with IntegraL : a user study of sense-making enabled by anchor-based virtual integration of library systems (2013) 0.00 
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    Abstract
    This article presents a user study showing the effectiveness of a linked-based, virtual integration infrastructure that gives users access to relevant online resources, empowering them to design an information-seeking path that is specifically relevant to their context. IntegraL provides a lightweight approach to improve and augment search functionality by dynamically generating context-focused "anchors" for recognized elements of interest generated by library services. This article includes a description of how IntegraL's design supports users' information-seeking behavior. A full user study with both objective and subjective measures of IntegraL and hypothesis testing regarding IntegraL's effectiveness of the user's information-seeking experience are described along with data analysis, implications arising from this kind of virtual integration, and possible future directions.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1927-1945
  4. Tang, X.; Yang, C.C.; Song, M.: Understanding the evolution of multiple scientific research domains using a content and network approach (2013) 0.00 
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    Abstract
    Interdisciplinary research has been attracting more attention in recent decades. In this article, we compare the similarity between scientific research domains and quantifying the temporal similarities of domains. We narrowed our study to three research domains: information retrieval (IR), database (DB), and World Wide Web (W3), because the rapid development of the W3 domain substantially attracted research efforts from both IR and DB domains and introduced new research questions to these two areas. Most existing approaches either employed a content-based technique or a cocitation or coauthorship network-based technique to study the development trend of a research area. In this work, we proposed an effective way to quantify the similarities among different research domains by incorporating content similarity and coauthorship network similarity. Experimental results on DBLP (DataBase systems and Logic Programming) data related to IR, DB, and W3 domains showed that the W3 domain was getting closer to both IR and DB whereas the distance between IR and DB remained relatively constant. In addition, comparing to IR and W3 with the DB domain, the DB domain was more conservative and evolved relatively slower.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1065-1075
  5. Song, M.; Kim, S.Y.; Zhang, G.; Ding, Y.; Chambers, T.: Productivity and influence in bioinformatics : a bibliometric analysis using PubMed central (2014) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.2, S.352-371
  6. An, J.; Kim, N.; Kan, M.-Y.; Kumar Chandrasekaran, M.; Song, M.: Exploring characteristics of highly cited authors according to citation location and content (2017) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.8, S.1975-1988
  7. Kim, M.; Baek, I.; Song, M.: Topic diffusion analysis of a weighted citation network in biomedical literature (2018) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.2, S.329-342
  8. Song, M.; Jeong, Y.K.; Kim, H.J.: Identifying the topology of the K-pop video community on YouTube : a combined co-comment analysis approach (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2580-2595
  9. Lee, K.; Kim, S.Y.; Kim, E.H.-J.; Song, M.: Comparative evaluation of bibliometric content networks by tomographic content analysis : an application to Parkinson's disease (2017) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1295-1307
  10. Song, M.; Kim, S.Y.; Lee, K.: Ensemble analysis of topical journal ranking in bioinformatics (2017) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.6, S.1564-1583

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