A Wikipedia powered state-based approach to automatic search query enhancement. Issue 4 (July 2018)

• Record Type: Journal Article
• Authors: Goslin, Kyle; Hofmann, Markus
• Is Part Of: Information processing & management. Volume 54:Issue 4(2018:Jul.)
• Page Start: 726
• Page End: 739
• Publication Date: 2018-07
• Subjects: Automatic Search Query Enhancement -- Query drift -- Information retrieval -- Wikipedia; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2017.10.001
• Languages: English
• ISSNs: 0306-4573

Abstract

Abstract: This paper describes the development and testing of a novel Automatic Search Query Enhancement (ASQE) algorithm, the Wikipedia N Sub-state Algorithm (WNSSA), which utilises Wikipedia as the sole data source for prior knowledge. This algorithm is built upon the concept of iterative states and sub-states, harnessing the power of Wikipedia's data set and link information to identify and utilise reoccurring terms to aid term selection and weighting during enhancement. This algorithm is designed to prevent query drift by making callbacks to the user's original search intent by persisting the original query between internal states with additional selected enhancement terms. The developed algorithm has shown to improve both short and long queries by providing a better understanding of the query and available data. The proposed algorithm was compared against five existing ASQE algorithms that utilise Wikipedia as the sole data source, showing an average Mean Average Precision (MAP) improvement of 0.273 over the tested existing ASQE algorithms.