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Ashish Gupta 0008

dblp:27/4744-8 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data stream processing · 67% Query processing and optimization · 33%
Theoretical computer science
1 paper
Automata and formal languages · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data stream processing › streaming data retrieval
stream indexing
0.012004
Processing XML streams with deterministic automata and stream indexes · ACM Trans. Database Syst. 2004
Data stream processing
XML stream processing
0.012004
Processing XML streams with deterministic automata and stream indexes · ACM Trans. Database Syst. 2004
Query processing and optimization › XML query processing
XPath query evaluation
0.012004
Processing XML streams with deterministic automata and stream indexes · ACM Trans. Database Syst. 2004
Automata and formal languages › finite automata
deterministic finite automata
0.012004
Processing XML streams with deterministic automata and stream indexes · ACM Trans. Database Syst. 2004
Automata and formal languages
finite automata
0.012004
Processing XML streams with deterministic automata and stream indexes · ACM Trans. Database Syst. 2004
YearPublicationVenuePosition
2004 Processing XML streams with deterministic automata and stream indexes
abstract
We consider the problem of evaluating a large number of XPath expressions on a stream of XML packets. We contribute two novel techniques. The first is to use a single Deterministic Finite Automaton (DFA). The contribution here is to show that the DFA can be used effectively for this problem: in our experiments we achieve a constant throughput, independently of the number of XPath expressions. The major issue is the size of the DFA, which, in theory, can be exponential in the number of XPath expressions. We provide a series of theoretical results and experimental evaluations that show that the lazy DFA has a small number of states, for all practical purposes. These results are of general interest in XPath processing, beyond stream processing. The second technique is the Streaming IndeX (SIX), which consists of adding a small amount of binary data to each XML packet that allows the query processor to achieve significant speedups. As an application of these techniques we describe the XML Toolkit (XMLTK), a collection of command-line tools providing highly scalable XML data processing.
Todd J. Green, Ashish Gupta 0008, Gerome Miklau, Makoto Onizuka, Dan Suciu
ACM Trans. Database Syst.2