Gumshoe quality toolkit: administering programmable search

Authors:
Zhuowei Bao;Benny Kimelfeld;Yunyao Li;Sriram Raghavan;Huahai Yang
Affiliations:
University of Pennsylvania, Philadelphia, PA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM Research - Almaden, San Jose, CA, USA;IBM India Research Lab, Bangalore, India;IBM Research - Almaden, San Jose, CA, USA
Venue:
Proceedings of the 21st ACM international conference on Information and knowledge management
Year:
2012

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Abstract

Enterprise search is challenging due to various reasons, notably the dynamic terminology and domain structure that are specific to the enterprise, combined with the fact that search deployments are typically managed by domain experts who are not necessarily search experts. To address that, it has been proposed to design search architectures that feature two principles: comprehensibility of the ranking mechanism and customizability of the search engine by means of intuitive runtime rules. The proposed demonstration operates on top of an engine implementation based on this search philosophy, and provides an administrator toolkit to realize the two principles. In particular, the toolkit provides a complete visualization of the provenance (hence ranking) of search results, embeds an editor for programming runtime rules, facilitates the investigation of (the cause of) missing or low-ranked desired results, and provides suggestions of rewrite rules to handle such results.