2016 - ACM Distinguished Member
Laks V. S. Lakshmanan mainly focuses on Data mining, Set, Theoretical computer science, Maximization and Mathematical optimization. His work in the fields of Data mining, such as Query language, intersects with other areas such as Mobile telephony. His studies deal with areas such as Apriori algorithm and Database theory as well as Set.
His Theoretical computer science research incorporates themes from Data integrity, Cube and Quotient. Laks V. S. Lakshmanan interconnects Approximation algorithm, Greedy algorithm, Expected value, Heuristics and Approximation theory in the investigation of issues within Maximization. His studies examine the connections between Relational database and genetics, as well as such issues in Interoperability, with regards to Database.
His primary areas of study are Data mining, Database, Information retrieval, Theoretical computer science and Maximization. His Data mining research includes themes of Set and Constraint. His Database research integrates issues from XML validation, XML framework, Efficient XML Interchange and XML database.
His study focuses on the intersection of Information retrieval and fields such as XML with connections in the field of Programming language. His work deals with themes such as Data modeling, Aggregate, Tree, Online analytical processing and Data integrity, which intersect with Theoretical computer science. In his work, Scalability is strongly intertwined with Social network, which is a subfield of Maximization.
Laks V. S. Lakshmanan mainly investigates Maximization, Approximation algorithm, Viral marketing, Graph and Data science. His Maximization study is related to the wider topic of Mathematical optimization. His studies in Approximation algorithm integrate themes in fields like Overhead, Computation and Minification.
His Viral marketing study necessitates a more in-depth grasp of Social network. As part of his studies on Cohesion, Laks V. S. Lakshmanan frequently links adjacent subjects like Data mining. His study in the fields of Multidimensional data under the domain of Data mining overlaps with other disciplines such as Lossless compression.
Laks V. S. Lakshmanan focuses on Graph, Community search, Maximization, Theoretical computer science and Approximation algorithm. His study in Community search is interdisciplinary in nature, drawing from both Telecommunications network, Cohesion and Data science. He combines subjects such as Social media and Viral marketing with his study of Data science.
His work carried out in the field of Maximization brings together such families of science as Social network and Product. His Theoretical computer science research is multidisciplinary, relying on both Aggregate, Recommender system, Group and Heuristic. Laks V. S. Lakshmanan has included themes like Analytics, Cluster analysis and Computation in his Approximation algorithm study.
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Learning influence probabilities in social networks
Amit Goyal;Francesco Bonchi;Laks V.S. Lakshmanan.
web search and data mining (2010)
Exploratory mining and pruning optimizations of constrained associations rules
Raymond T. Ng;Laks V. S. Lakshmanan;Jiawei Han;Alex Pang.
international conference on management of data (1998)
CELF++: optimizing the greedy algorithm for influence maximization in social networks
Amit Goyal;Wei Lu;Laks V.S. Lakshmanan.
the web conference (2011)
TIMBER: A native XML database
H. V. Jagadish;S. Al-Khalifa;A. Chapman;L. V. S. Lakshmanan.
very large data bases (2002)
A Foundation for Multi-dimensional Databases
Marc Gyssens;Laks V. S. Lakshmanan.
very large data bases (1997)
SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model
Amit Goyal;Wei Lu;Laks V.S. Lakshmanan.
international conference on data mining (2011)
ProbView: a flexible probabilistic database system
Laks V. S. Lakshmanan;Nicola Leone;Robert Ross;V. S. Subrahmanian.
ACM Transactions on Database Systems (1997)
Mining frequent itemsets with convertible constraints
Jian Pei;Jiawei Han;L.V.S. Lakshmanan;L.V.S. Lakshmanan.
international conference on data engineering (2001)
Information and Influence Propagation in Social Networks
Wei Chen;Laks V. S. Lakshmanan;Carlos Castillo.
TAX: A Tree Algebra for XML
H. V. Jagadish;Laks V. S. Lakshmanan;Divesh Srivastava;Keith Thompson.
database programming languages (2001)
Profile was last updated on December 6th, 2021.
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