{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mining-user-queries-with-information","title":"Mining User Queries with Information Extraction Methods and Linked Data","arxiv_id":"1709.07782","date":"2017-09-22","proceeding":null,"authors":["Chardonnens Anne","Rizza Ettore","Coeckelbergs Mathias","van Hooland Seth"],"abstract":"Purpose: Advanced usage of Web Analytics tools allows to capture the content\nof user queries. Despite their relevant nature, the manual analysis of large\nvolumes of user queries is problematic. This paper demonstrates the potential\nof using information extraction techniques and Linked Data to gather a better\nunderstanding of the nature of user queries in an automated manner.\n  Design/methodology/approach: The paper presents a large-scale case-study\nconducted at the Royal Library of Belgium consisting of a data set of 83 854\nqueries resulting from 29 812 visits over a 12 month period of the historical\nnewspapers platform BelgicaPress. By making use of information extraction\nmethods, knowledge bases and various authority files, this paper presents the\npossibilities and limits to identify what percentage of end users are looking\nfor person and place names.\n  Findings: Based on a quantitative assessment, our method can successfully\nidentify the majority of person and place names from user queries. Due to the\nspecific character of user queries and the nature of the knowledge bases used,\na limited amount of queries remained too ambiguous to be treated in an\nautomated manner.\n  Originality/value: This paper demonstrates in an empirical manner both the\npossibilities and limits of gaining more insights from user queries extracted\nfrom a Web Analytics tool and analysed with the help of information extraction\ntools and knowledge bases. Methods and tools used are generalisable and can be\nreused by other collection holders.","url_abs":"http://arxiv.org/abs/1709.07782v1","url_pdf":"http://arxiv.org/pdf/1709.07782v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mining-user-queries-with-information","repo_url":"https://github.com/ulbstic/BelgicaPress","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}