Search (7 results, page 1 of 1)

  • × author_ss:"Lee, J."
  1. Cheung, D.W.; Kao, B.; Lee, J.: Discovering user access patterns on the World Wide Web (1998) 0.07 
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    Footnote
    Contribution to a special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
    Theme
    Web-Agenten
  2. Neilson, I.; Lee, J.: Conversations with graphics : implications for the design of natural language/graphics interfaces (1994) 0.01 
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    Abstract
    Details the results of an empirical enquiry into how people use two communicational codes - natural language and drawing - to achieve a shared understanding of communicational codes as well as task structures etc. Research in human computer interaction has, however, tended to neglect the former in favour of the latter. Redresses this imbalance by reporting the results of an empirical enquiry into how people use two communication codes - natural language and drawing - to achieve a shared understanding of a problem and its solution. Indicates the complex interdependency of these forms of communication when used in combination. Discusses the implications of these results for the design of natural language/graphics interfaces
    Source
    International journal of human-computer studies. 40(1994) no.3, S.509-541
  3. Lee, J.: Design rationale systems : understanding the issues (1997) 0.01 
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    Abstract
    Most current computer assisted design rationale systems fail to consider practical concerns, such as cost effective use and smooth integration. Identifies 7 technical and business issues: what services to provide; what parts of the rationale to represent explicitly; how to represent, produce, and access rationales and manage them cost effectively; and how to integrate the design rationale system. Describes their implications
  4. Son, J.; Lee, J.; Larsen, I.; Nissenbaum, K.R.; Woo, J.: Understanding the uncertainty of disaster tweets and its effect on retweeting : the perspectives of uncertainty reduction theory and information entropy (2020) 0.01 
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    Abstract
    The rapid and wide dissemination of up-to-date, localized information is a central issue during disasters. Being attributed to the original 140-character length, Twitter provides its users with quick-posting and easy-forwarding features that facilitate the timely dissemination of warnings and alerts. However, a concern arises with respect to the terseness of tweets that restricts the amount of information conveyed in a tweet and thus increases a tweet's uncertainty. We tackle such concerns by proposing entropy as a measure for a tweet's uncertainty. Based on the perspectives of Uncertainty Reduction Theory (URT), we theorize that the more uncertain information of a disaster tweet, the higher the entropy, which will lead to a lower retweet count. By leveraging the statistical and predictive analyses, we provide evidence supporting that entropy validly and reliably assesses the uncertainty of a tweet. This study contributes to improving our understanding of information propagation on Twitter during disasters. Academically, we offer a new variable of entropy to measure a tweet's uncertainty, an important factor influencing disaster tweets' retweeting. Entropy plays a critical role to better comprehend URLs and emoticons as a means to convey information. Practically, this research suggests a set of guidelines for effectively crafting disaster messages on Twitter.
  5. Lee, J.; Min, J.-K.; Oh, A.; Chung, C.-W.: Effective ranking and search techniques for Web resources considering semantic relationships (2014) 0.01 
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    Abstract
    On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved. In this paper, we present effective ranking and search techniques considering the semantic relationships in an ontology. Our technique retrieves top-k resources which are the most relevant to query keywords through the semantic relationships. To do this, we propose a weighting measure for the semantic relationship. Based on this measure, we propose a novel ranking method which considers the number of meaningful semantic relationships between a resource and keywords as well as the coverage and discriminating power of keywords. In order to improve the efficiency of the search, we prune the unnecessary search space using the length and weight thresholds of the semantic relationship path. In addition, we exploit Threshold Algorithm based on an extended inverted index to answer top-k results efficiently. The experimental results using real data sets demonstrate that our retrieval method using the semantic information generates accurate results efficiently compared to the traditional methods.
  6. Lee, J.; Boling, E.: Information-conveying approaches and cognitive styles of mental modeling in a hypermedia-based learning environment (2008) 0.01 
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    Theme
    Computer Based Training
  7. Mischo, W.H.; Lee, J.: End-user searching in bibliographic databases (1987) 0.00 
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    Source
    Annual review of information science and technology. 22(1987), S.227-263

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