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Lu, K.; Mao, J.: ¬An automatic approach to weighted subject indexing : an empirical study in the biomedical domain (2015)
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- Abstract
- Subject indexing is an intellectually intensive process that has many inherent uncertainties. Existing manual subject indexing systems generally produce binary outcomes for whether or not to assign an indexing term. This does not sufficiently reflect the extent to which the indexing terms are associated with the documents. On the other hand, the idea of probabilistic or weighted indexing was proposed a long time ago and has seen success in capturing uncertainties in the automatic indexing process. One hurdle to overcome in implementing weighted indexing in manual subject indexing systems is the practical burden that could be added to the already intensive indexing process. This study proposes a method to infer automatically the associations between subject terms and documents through text mining. By uncovering the connections between MeSH descriptors and document text, we are able to derive the weights of MeSH descriptors manually assigned to documents. Our initial results suggest that the inference method is feasible and promising. The study has practical implications for improving subject indexing practice and providing better support for information retrieval.
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Lu, K.; Mao, J.; Li, G.: Toward effective automated weighted subject indexing : a comparison of different approaches in different environments (2018)
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- Abstract
- 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.
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Braam, R.R.; Bruil, J.: Quality of indexing information : authors' views on indexing of their articles in chemical abstracts online CA-file (1992)
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- Abstract
- Studies the quality of subject indexing by Chemical Abstracts Indexing Service by confronting authors with the particular indexing terms attributed to their computer, for 270 articles published in 54 journals, 5 articles out of each journal. Responses (80%) indicate the superior quality of keywords, both as content descriptors and as retrieval tools. Author judgements on these 2 different aspects do not always converge, however. CAS's indexing policy to cover only 'new' aspects is reflected in author's judgements that index lists are somewhat incomplete, in particular in the case of thesaurus terms (index headings). The large effort expanded by CAS in maintaining and using a subject thesuaurs, in order to select valid index headings, as compared to quick and cheap keyword postings, does not lead to clear superior quality of thesaurus terms for document description nor in retrieval. Some 20% of papers were not placed in 'proper' CA main section, according to authors. As concerns the use of indexing data by third parties, in bibliometrics, users should be aware of the indexing policies behind the data, in order to prevent invalid interpretations
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Hudon, M.: Conceptual compatibility in controlled language tools used to index and access the content of moving image collections (2004)
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- Abstract
- Five controlled vocabularies currently used for content representation in collections of non art moving images were examined to determine their level of conceptual compatibility. Methods borrowed from previous research in the area of indexing language compatibility were used. Quantitative data and qualitative observations allowed us to estimate more precisely and realistically the actual degree of conceptual redundancy in these indexing languages. It was found that the conceptual overlap is high enough to justify the pursuit of research and development work an a common basic indexing and access language that could be used to name objects, events, categories of persons, and relations most frequently depicted in non art moving image collections.
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Chan, L.M.: Alphabetical arrangement and subject collocation in Library of Congress Subject Headings (1977)
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Iivonen, M.: ¬The impact of the indexing environment on interindexer consistency (1990)
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Prasher, R.G.: Evaluation of indexing system (1989)
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Ladewig, C.; Rieger, M.: Ähnlichkeitsmessung mit und ohne aspektische Indexierung (1998)
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Gretz, M.; Thomas, M.: Indexierungen in biomedizinischen Literaturdatenbanken : eine vergleichende Analyse (1991)
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Iivonen, M.; Kivimäki, K.: Common entities and missing properties : similarities and differences in the indexing of concepts (1998)
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