Computer Evaluation of Indexing and Text Processing

By Gerard A. Salton, Michael E. Lesk. 1968

Subfields: Information Retrieval & Search

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Citations in the corpus

Understanding and improving automated collaborative filtering systems (2000, background): “Indexing is the process of examining content collections and creating software-searchable data structures that contain descriptions of the items available[13,14,24,25,41,45,52,57,71].”
Corpus-based and Knowledge-based Measures of Text Semantic Similarity (2006, background): “One of the earliest applications of text similarity is perhaps the vectorial model in information retrieval, where the document most relevant to an input query is determined by ranking documents in a collection in reversed order of their similarity to the given query (Salton & Lesk 1971).”
Document expansion for speech retrieval (1999, background): “Experimentation has shown that automaticallyderived uncontrolled index terms are competitive with carefully crafted manual index terms [23].”
Relevance assessments and retrieval system evaluation (1968, methodology): “The output produced by the SMART system consists of superimposed recall-precision graphs exhibiting averages over a complete query set for several processing methods {3].”
A statistical interpretation of term specificity and its application in retrieval (2021, background): “All three collections have been used for a whole range of experiments with different index languages, search techniques, and so on: see Cleverdon et al. (1966), Salton (1968), Salton and Lesk (1968), Spärck Jones (1971), Aitchison et al. (1970) and Keen (forthcoming).”
Semantic text similarity using corpus-based word similarity and string similarity (2008, methodology): “…methods are commonly used in Information Retrieval (IR) systems [Meadow et al. 2000], where the document most relevant to an input query is determined by representing a document as a word vector, and then queries are matched to similar documents in the document database via a similarity metric…”
Test Collection Based Evaluation of Information Retrieval Systems (2010, unknown): “[164] M. E. Lesk and G. Salton, “Relevance assessments and retrieval system evaluation*1,” Information Storage and Retrieval, vol. 4, no. 4, pp. 343–359, doi:10.1016/0020-0271(68)90029-6, 1968.”
Towards Meaningful Statements in IR Evaluation: Mapping Evaluation Measures to Interval Scales (2021, methodology): “Statistical significance testing has a long story of adoption and investigation in IR, from the early uses of t-test reported by Salton and Lesk [77], to the discussion on the compliance with the distribution assumptions of significance tests by van Rijsbergen [93], to advocating for a more wide-spr”