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Publikationstyp: Konferenz: Paper
Art der Begutachtung: Peer review (Publikation)
Titel: Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data
Autor/-in: Nadig, Stefanie
Braschler, Martin
Stockinger, Kurt
et. al: No
DOI: 10.21256/zhaw-20042
Tagungsband: Proceedings of the 12th LREC
Angaben zur Konferenz: 12th Language Resources and Evaluation Conference (LREC) 2020
Erscheinungsdatum: Mai-2020
Verlag / Hrsg. Institution: European Language Resources Association
Sprache: Englisch
Schlagwörter: Database search; Information retrieval; Benchmark data set; Query evaluation; Relevance assessment
Fachgebiet (DDC): 005: Computerprogrammierung, Programme und Daten
020: Bibliotheks- und Informationswissenschaft
Zusammenfassung: 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
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: School of Engineering
Organisationseinheit: Institut für Informatik (InIT)
Enthalten in den Sammlungen:Publikationen School of Engineering

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Nadig, S., Braschler, M., & Stockinger, K. (2020, May). Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data. Proceedings of the 12th LREC. https://doi.org/10.21256/zhaw-20042
Nadig, S., Braschler, M. and Stockinger, K. (2020) ‘Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data’, in Proceedings of the 12th LREC. European Language Resources Association. Available at: https://doi.org/10.21256/zhaw-20042.
S. Nadig, M. Braschler, and K. Stockinger, “Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data,” in Proceedings of the 12th LREC, May 2020. doi: 10.21256/zhaw-20042.
NADIG, Stefanie, Martin BRASCHLER und Kurt STOCKINGER, 2020. Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data. In: Proceedings of the 12th LREC. Conference paper. European Language Resources Association. Mai 2020
Nadig, Stefanie, Martin Braschler, and Kurt Stockinger. 2020. “Database Search vs. Information Retrieval : A Novel Method for Studying Natural Language Querying of Semi-Structured Data.” Conference paper. In Proceedings of the 12th LREC. European Language Resources Association. https://doi.org/10.21256/zhaw-20042.
Nadig, Stefanie, et al. “Database Search vs. Information Retrieval : A Novel Method for Studying Natural Language Querying of Semi-Structured Data.” Proceedings of the 12th LREC, European Language Resources Association, 2020, https://doi.org/10.21256/zhaw-20042.


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