@inproceedings{b8ea5c8fe02f493db48b844b8da08bf7,
title = "A comparison of automatic search qery enhancement algorithms that utilise Wikipedia as a source of a priori knowledge",
abstract = "This paper describes the benchmarking and analysis of fve Automatic Search Query Enhancement (ASQE) algorithms that utilise Wikipedia as the sole source for a priori knowledge. The contributions of this paper include: 1) A comprehensive review into current ASQE algorithms that utilise Wikipedia as the sole source for a priori knowledge; 2) benchmarking of fve existing ASQE algorithms using the TREC-9 Web Topics on the ClueWeb12 data set and 3) analysis of the results from the benchmarking process to identify the strengths and weaknesses each algorithm. During the benchmarking process, 2,500 relevance assessments were performed. Results of these tests are analysed using the Average Precision @10 per query and Mean Average Precision @10 per algorithm. From this analysis we show that the scope of a priori knowledge utilised during enhancement and the available term weighting methods available from Wikipedia can further aid the ASQE process. Although approaches taken by the algorithms are still relevant, an over dependence on weighting schemes and data sources used can easily impact results of an ASQE algorithm.",
keywords = "Information retrieval, Search Query Enhancement, Wikipedia",
author = "Kyle Goslin and Markus Hofmann",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 9th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2017 ; Conference date: 08-12-2017 Through 10-12-2017",
year = "2017",
month = dec,
day = "8",
doi = "10.1145/3158354.3158356",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "6--13",
editor = "Mandar Mitra and Jainisha Sankhavara and Prasenjit Majumder and Parth Mehta",
booktitle = "FIRE 2017 - Proceedings of the 9th Annual Meeting of the Forum for Information Retrieval Evaluation",
address = "United States",
}