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A functionality taxonomy for document search engines

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arxiv 2105.12989 v1 pith:T5FMPVK2 submitted 2021-05-27 cs.IR

classification cs.IR
keywords searchenginesfunctionalitytaxonomyareasdocumentengineused
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In this paper a functionality taxonomy for document search engines is proposed. It can be used to assess the features of a search engine, to position search engines relative to each other, or to select which search engine 'fits' a certain situation. One is able to identify areas for improvement. During development, we were guided by the viewpoint of the user. We use the word `search engine' in the broadest sense possible, including library and web based (meta) search engines. The taxonomy distinguishes seven functionality areas: an indexing service, user profiling, query composition, query execution, result presentation, result refinement, and history keeping. Each of these relates and provides services to other functionality areas. It can be extended whenever necessary. To illustrate the validity of our taxonomy, it has been used for comparing various document search engines existing today (ACM Digital Library, PiCarta, Copernic, AltaVista, Google, and GuideBeam). It appears that the functionality aspects covered by our taxonomy can be used for describing these search engines.

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  1. Rank, Chunk and Expand: Lineage-Oriented Reasoning for Taxonomy Expansion

    cs.CL 2025-05 conditional novelty 6.0 of 10

    LORex combines a trained candidate ranker with batched LLM reasoning to insert new concepts into taxonomies, outperforming twelve baselines on most benchmarks while overstating the average gain.

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