Any-k Algorithms for Exploratory Analysis with Conjunctive Queries
Author(s) -
Xiaofeng Yang,
Mirek Riedewald,
Rundong Li,
Wolfgang Gatterbauer
Publication year - 2018
Publication title -
pubmed central
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-5847-7
DOI - 10.1145/3214708.3214711
Subject(s) - conjunctive query , computer science , exploratory analysis , tree (set theory) , algorithm , value (mathematics) , exploratory search , theoretical computer science , combinatorics , data mining , information retrieval , mathematics , relational database , machine learning , data science
We recently proposed the notion of any-k queries , together with the KARPET algorithm, for tree-pattern search in labeled graphs. Any- k extends top- k by not requiring a pre-specified value of k . Instead, an any- k algorithm returns as many of the top-ranked results as possible, for a given time budget. Given additional time, it produces the next-highest ranked results quickly as well. It can be stopped anytime, but may have to continue until all results are returned. In the latter case, any-k takes times similar to an algorithm that first produces all results and then sorts them. We summarize KARPET and argue that it can be extended to support any- k exploratory search for arbitrary conjunctive queries.
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