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  • × author_ss:"Huffman, G.D."
  1. Huffman, G.D.: Semi-automatic determination of citation relevancy : user evaluation (1990) 0.03 
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    Abstract
    Online bibiographic, database searches typically produce hundreds of retrieved citations with only about 20-40% relevant to the search topic and/or problem statement. Significant amounts of time are required to categorize and select the relevant citations. A software system-SORT-AIDS/SABRE-has been developes which ranks the citations in terms of relevance. This paper presents the results of a comprehensive user evaluation of the relevance ranking procedures. Test results show that the software generated distributions approach the ideal distribution-all relevant citations at the beginning of the collection-in 22% of the cases, are 23% better than the random distribution-relevant citations distributed uniformly throughout the dcollection-on average and are poorer than the random distribution in 4% of the cae.
    Source
    Information processing and management. 26(1990) no.2, S.295-302
    Type
    a
  2. Huffman, G.D.; Vital, D.A.; Bivins, R.G.: Generating indices with lexical association methods : term uniqueness (1990) 0.00 
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    Abstract
    A software system has been developed which orders citations retrieved from an online database in terms of relevancy. The system resulted from an effort generated by NASA's Technology Utilization Program to create new advanced software tools to largely automate the process of determining relevancy of database citations retrieved to support large technology transfer studies. The ranking is based on the generation of an enriched vocabulary using lexical association methods, a user assessment of the vocabulary and a combination of the user assessment and the lexical metric. One of the key elements in relevancy ranking is the enriched vocabulary -the terms mst be both unique and descriptive. This paper examines term uniqueness. Six lexical association methods were employed to generate characteristic word indices. A limited subset of the terms - the highest 20,40,60 and 7,5% of the uniquess words - we compared and uniquess factors developed. Computational times were also measured. It was found that methods based on occurrences and signal produced virtually the same terms. The limited subset of terms producedby the exact and centroid discrimination value were also nearly identical. Unique terms sets were produced by teh occurrence, variance and discrimination value (centroid), An end-user evaluation showed that the generated terms were largely distinct and had values of word precision which were consistent with values of the search precision.
    Source
    Information processing and management. 26(1990) no.4, S.549-558
    Type
    a

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