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| Time-lag Calculation and Enlightenment of Multi-source Science and Technology Literature Fusion for the Detection of Emerging Research Topic: A Case Study in the Field of Agriculture |
| Yang Jinqing1,2, Lu Wei1,2, Wu Leyan1,2 |
1.School of Information Management, Wuhan University, Wuhan 430072
2.Institute for Information Retrieval and Knowledge Mining, Wuhan University, Wuhan 430072 |
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Abstract To explore the time lag in the emerging topic detection of multi-source data fusion, this paper designs a scheme to calculate time lag. First, research topics are extracted from four kinds of scientific and technological literature datasets, then a similarity matrix is constructed by calculating the similarity between those research topics. Second, optimal combination under the condition of minimum similarity loss is found based on the Hungarian optimal matching algorithm. Finally, the linear equation model is constructed and time lag is calculated by fitting the model. Using the experimental data of 337,790 abstract texts in agricultural disciplines from 2009 to 2016, the number of the research topics extracted from fund projects, patents, journal articles, and conference papers is 250, 260, 260, and 240 respectively. Using the above-mentioned time-lag calculation method of scientific and technological literature, we find the following results: journal articles lag behind fund project text and conference papers for one year and patent documents lag behind journal articles for one year. Combining with the previous research results in different disciplines, the feasibility and effectiveness of the time-lag calculation method for multi-source scientific and technological literature are verified, and a new idea for the formulation of a multi-source data fusion strategy is also provided.
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Received: 26 September 2019
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