1School of Economics & Management, Nanjing Institute of Technology, Nanjing 211167, China 2School of Information Management, Nanjing University, Nanjing 210023, China 3School of Economics & Management, Nanjing University of Science and Technology, Nanjing 210094, China 4 College of Information Science & Technology, Nanjing Agricultural University, Nanjing 210095, China
[Objective] This paper proposes a new system to extract methodological entities from the full texts of academic literature, aiming to identify their indexing features and usages. [Methods] Firstly, we extracted feature sentences and methodological entities based on dictionaries, rules, and manual annotations. Then, we implemented a methodology knowledge extraction module with the help of Microsoft Visual Studio 2012 and SQL Server 2012. [Results] The precision of extracting methodological features was 76%, while the recall rate was greater than 42%. Each feature sentence had 1.42 method entities on average. The formal indexing ratio for methodological entities was less than 27%, while the ratio for feature sentences was less than 35%. We also found low formal indexing rate for subject-specific methodological entities. [Limitations] This system’s recall and precision rates were not very satisfactory. The manual workload was intensive for entity extraction and did not include the semantic features. [Conclusions] The proposed method has inter-disciplinary versatility and helps us explore the dissemination routes of interdisciplinary knowledge.
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