Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-20042
Publication type: Conference paper
Type of review: Peer review (publication)
Title: Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data
Authors: Nadig, Stefanie
Braschler, Martin
Stockinger, Kurt
et. al: No
DOI: 10.21256/zhaw-20042
Proceedings: Proceedings of the 12th LREC
Conference details: 12th Language Resources and Evaluation Conference (LREC) 2020
Issue Date: May-2020
Publisher / Ed. Institution: European Language Resources Association
Language: English
Subjects: Database search; Information retrieval; Benchmark data set; Query evaluation; Relevance assessment
Subject (DDC): 005: Computer programming, programs and data
020: Library and information sciences
Abstract: The traditional approach of querying a relational database is via a formal language, namely SQL. Recent developments in the design of natural language interfaces to databases show promising results for querying either with keywords or with full natural language queries and thus render relational databases more accessible to non-tech savvy users. Such enhanced relational databases basically use a search paradigm which is commonly used in the field of information retrieval. However, the way systems are evaluated in the database and the information retrieval communities often differs due to a lack of common benchmarks. In this paper, we provide an adapted benchmark data set that is based on a test collection originally used to evaluate information retrieval systems. The data set contains 45 information needs developed on the Internet Movie Database (IMDb), including corresponding relevance assessments. By mapping this benchmark data set to a relational database schema, we enable a novel way of directly comparing database search techniques with information retrieval. To demonstrate the feasibility of our approach, we present an experimental evaluation that compares SODA, a keyword-enabled relational database system, against the Terrier information retrieval system and thus lays the foundation for a future discussion of evaluating database systems that support natural language interfaces.
URI: https://digitalcollection.zhaw.ch/handle/11475/20042
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in Collections:Publikationen School of Engineering

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