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Tenopir, C.; King, D.W.; Edwards, S.; Wu, L.: Electronic journals and changes in scholarly article seeking and reading patterns : the paradox of control (2009)
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- Abstract
- Purpose - By tracking the information-seeking and reading patterns of science, technology, medical and social science faculty members from 1977 to the present, this paper seeks to examine how faculty members locate, obtain, read, and use scholarly articles and how this has changed with the widespread availability of electronic journals and journal alternatives. Design/methodology/approach - Data were gathered using questionnaire surveys of university faculty and other researchers periodically since 1977. Many questions used the critical incident of the last article reading to allow analysis of the characteristics of readings in addition to characteristics of readers. Findings - The paper finds that the average number of readings per year per science faculty member continues to increase, while the average time spent per reading is decreasing. Electronic articles now account for the majority of readings, though most readings are still printed on paper for final reading. Scientists report reading a higher proportion of older articles from a wider range of journal titles and more articles from library e-collections. Articles are read for many purposes and readings are valuable to those purposes. Originality/value - The paper draws on data collected in a consistent way over 30 years. It provides a unique look at how electronic journals and other developments have influenced changes in reading behavior over three decades. The use of critical incidence provides evidence of the value of reading in addition to reading patterns.
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Fang, L.; Tuan, L.A.; Hui, S.C.; Wu, L.: Syntactic based approach for grammar question retrieval (2018)
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- Abstract
- With the popularity of online educational platforms, English learners can learn and practice no matter where they are and what they do. English grammar is one of the important components in learning English. To learn English grammar effectively, it requires students to practice questions containing focused grammar knowledge. In this paper, we study a novel problem of retrieving English grammar questions with similar grammatical focus. Since the grammatical focus similarity is different from textual similarity or sentence syntactic similarity, existing approaches cannot be applied directly to our problem. To address this problem, we propose a syntactic based approach for English grammar question retrieval which can retrieve related grammar questions with similar grammatical focus effectively. In the proposed syntactic based approach, we first propose a new syntactic tree, namely parse-key tree, to capture English grammar questions' grammatical focus. Next, we propose two kernel functions, namely relaxed tree kernel and part-of-speech order kernel, to compute the similarity between two parse-key trees of the query and grammar questions in the collection. Then, the retrieved grammar questions are ranked according to the similarity between the parse-key trees. In addition, if a query is submitted together with answer choices, conceptual similarity and textual similarity are also incorporated to further improve the retrieval accuracy. The performance results have shown that our proposed approach outperforms the state-of-the-art methods based on statistical analysis and syntactic analysis.
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Zhao, L.; Wu, L.; Huang, X.: Using query expansion in graph-based approach for query-focused multi-document summarization (2009)
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- Abstract
- This paper presents a novel query expansion method, which is combined in the graph-based algorithm for query-focused multi-document summarization, so as to resolve the problem of information limit in the original query. Our approach makes use of both the sentence-to-sentence relations and the sentence-to-word relations to select the query biased informative words from the document set and use them as query expansions to improve the sentence ranking result. Compared to previous query expansion approaches, our approach can capture more relevant information with less noise. We performed experiments on the data of document understanding conference (DUC) 2005 and DUC 2006, and the evaluation results show that the proposed query expansion method can significantly improve the system performance and make our system comparable to the state-of-the-art systems.
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