We make the suggestion that instead of implementing custom index structures and query evaluation algorithms, IR researchers should simply store document representations in a column-oriented relational database and write ranking models using SQL. For rapid prototyping, this is particularly advantageous since researchers can explore new ranking functions and features by simply issuing SQL queries, without needing to write imperative code. We demonstrate the feasibility of this approach by an implementation of conjunctive BM25 using MonetDB on a part of the ClueWeb12 collection. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Mühleisen, H., Samar, T., Lin, J., & De Vries, A. P. (2014). Column stores as an IR prototyping tool. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8416 LNCS, pp. 789–792). Springer Verlag. https://doi.org/10.1007/978-3-319-06028-6_97
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