@article{davoust_processing_2016,

title = {Processing regular path queries on arbitrarily distributed data},

author = {A. Davoust and B. Esfandiari},

editor = {Oa'Sullivan D. Debruyne C. Dillon T.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995931482&doi=10.1007%2f978-3-319-48472-3_53&partnerID=40&md5=58ab4d499f8422130fc98507ba48e9b9},

doi = {10.1007/978-3-319-48472-3_53},

issn = {03029743},

year  = {2016},

date = {2016-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {10033 LNCS},

pages = {844–861},

abstract = {Regular Path Queries (RPQs) are a type of graph query where answers are pairs of nodes connected by a sequence of edges matching a regular expression. We study the techniques to process such queries on a distributed graph of data. While many techniques assume the location of each data element (node or edge) is known, when the components of the distributed system are autonomous, the data will be arbitrarily distributed, or non-localized. We compare query processing strategies for this setting analytically and empirically, using biomedical data and meaningful queries. We isolate query-dependent cost factors and present a method to choose between strategies, using new query cost estimation techniques. © Springer International Publishing AG 2016.},

note = {ISBN: 9783319484716 

Publisher: Springer Verlag},

keywords = {Arbitrarily distributed datum, Biomedical data, Cost estimating, Distributed systems, Graph queries, Processing strategies, Query cost estimation, Query languages, Regular expressions, Regular path queries},

pubstate = {published},

tppubtype = {article}

}