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Martin Gavrilov

dblp:14/5417 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2004
—ORCID · none

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

Theory of computation · 2 · 2 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author

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 mining · 75% Information retrieval · 25%
Theoretical computer science
1 paper
Algorithms and data structures · 62% Computational geometry · 38%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data mining
clustering		 0.012000
Mining the stock market (extended abstract): which measure is best? · KDD 2000
Information retrieval
similarity measure		 0.012000
Mining the stock market (extended abstract): which measure is best? · KDD 2000
Data mining › clustering
time series clustering		 0.012000
Mining the stock market (extended abstract): which measure is best? · KDD 2000
Data mining › temporal data mining
time series mining		 0.012000
Mining the stock market (extended abstract): which measure is best? · KDD 2000
Algorithms and data structures › sequence algorithms › string algorithms › string matching
approximate string matching		 0.011999
Geometric Pattern Matching: A Performance Study · SCG 1999
Computational geometry › geometric matching
geometric pattern matching		 0.011999
Geometric Pattern Matching: A Performance Study · SCG 1999
Algorithms and data structures › sequence algorithms
string algorithms		 0.011999
Geometric Pattern Matching: A Performance Study · SCG 1999
Algorithms and data structures › sequence algorithms › string algorithms
string matching		 0.011999
Geometric Pattern Matching: A Performance Study · SCG 1999

Methods — techniques the papers use, named apart from their topics

similarity measure · 0.0clustering · 0.0random sampling · 0.0locality-sensitive hashing · 0.0
YearPublicationVenuePosition
2004 Combinatorial and Experimental Methods for Approximate Point Pattern Matching
Martin Gavrilov, Piotr Indyk, Rajeev Motwani 0001, Suresh Venkatasubramanian
 Algorithmica1
2000 Mining the stock market (extended abstract): which measure is best?
abstract
In recent years, there has been a lot of interest in the database community in mining time series data.Surprisingly, little work has been done on verifying which measures are most suitable for mining of a given class of data sets.Such work is of crucial importance, since it enables us to identify similarity measures which are useful in a given context and therefore for which efficient algorithms should be further investigated.Moreover, an accurate evaluation of the performance of even existing algorithms is not possible without a good understanding of the data sets occurring in practice.In this work we attempt to fill this gap by studying similarity measures for clustering of similar stocks (which, of course, is an interesting problem on its own).Our approach is to cluster the stocks according to various measures (including several novel ones) and compare the results to the "groundtruth" clustering based on the Standard and Poor 500 Index.Our experiments reveal several interesting facts about the similarity measures used for stock-market data.
Martin Gavrilov, Dragomir Anguelov, Piotr Indyk, Rajeev Motwani 0001
 KDD1
1999 Geometric Pattern Matching: A Performance Study
abstract
Article Free Access Share on Geometric pattern matching: a performance study Authors: Martin Gavrilov Department of Computer Science, Stanford University Department of Computer Science, Stanford UniversityView Profile , Piotr Indyk Department of Computer Science, Stanford University Department of Computer Science, Stanford UniversityView Profile , Rajeev Motwani Department of Computer Science, Stanford University Department of Computer Science, Stanford UniversityView Profile , Suresh Venkatasubramanian Department of Computer Science, Stanford University Department of Computer Science, Stanford UniversityView Profile Authors Info & Claims SCG '99: Proceedings of the fifteenth annual symposium on Computational geometryJune 1999 Pages 79–85https://doi.org/10.1145/304893.304916Published:13 June 1999Publication History 17citation669DownloadsMetricsTotal Citations17Total Downloads669Last 12 Months17Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Martin Gavrilov, Piotr Indyk, Rajeev Motwani 0001, Suresh Venkatasubramanian
 SCG1