Toward Effective Automated Weighted Subject Indexing: A Comparison of Different Approaches in Different Environments.
Subject indexing plays an important role in supporting subject access to information resources. Current subject indexing systems do not make adequate distinctions on the importance of assigned subject descriptors. Assigning numeric weights to subject descriptors to distinguish their importance to th...
| Published in: | Journal of the Association for Information Science & Technology Vol. 69; no. 1; pp. 121 - 134 |
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| Main Authors: | , , |
| Format: | equations & formulas research tables/charts Journal Article |
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Wiley-Blackwell
Jan2018
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=126974705&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 126974705 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23301635 H6JN jtl: Journal of the Association for Information Science & Technology issn: 23301635 maglogo: N pubinfo: dt: Jan2018 vid: 69 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 126974705 126974705 126974705 10.1002/asi.23912 126974705 ppf: 121 ppct: 13 formats: tig: atl: Toward Effective Automated Weighted Subject Indexing: A Comparison of Different Approaches in Different Environments. aug: au: Kun Lu Jin Mao Gang Li affil: School of Library and Information Studies, University of Oklahoma, 401 West Brooks, Norman, OK 73019, USA sug: subj: Abstracting and Indexing Methods Subject Headings Automation Human Medline Semantics Wilcoxon Rank Sum Test Funding Source ab: Subject indexing plays an important role in supporting subject access to information resources. Current subject indexing systems do not make adequate distinctions on the importance of assigned subject descriptors. Assigning numeric weights to subject descriptors to distinguish their importance to the documents can strengthen the role of subject metadata. Automated methods are more cost-effective. This study compares different automated weighting methods in different environments. Two evaluation methods were used to assess the performance. Experiments on three datasets in the biomedical domain suggest the performance of different weighting methods depends on whether it is an abstract or full text environment. Mutual information with bag-of-words representation shows the best average performance in the full text environment, while cosine with bag-of-words representation is the best in an abstract environment. The cosine measure has relatively consistent and robust performance. A direct weighting method, IDF (Inverse Document Frequency), can produce quick and reasonable estimates of the weights. Bag-of-words representation generally outperforms the concept-based representation. Further improvement in performance can be obtained by using the learning-to-rank method to integrate different weighting methods. This study follows up Lu and Mao (Journal of the Association for Information Science and Technology, 66, 1776-1784, 2015), in which an automated weighted subject indexing method was proposed and validated. The findings from this study contribute to more effective weighted subject indexing. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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