What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Programming language
Paolo Boldi mainly focuses on Graph, Theoretical computer science, Discrete mathematics, Combinatorics and PageRank.
He interconnects Query expansion, Web query classification and Query optimization in the investigation of issues within Graph.
His Theoretical computer science study integrates concerns from other disciplines, such as Path, Webgraph and Complex network.
His Webgraph research focuses on Cluster analysis and how it connects with Modular decomposition and Graph product.
His Directed graph and Undirected graph study in the realm of Discrete mathematics connects with subjects such as Symmetry breaking and Structure.
The study incorporates disciplines such as Ranking, Graph, Mathematical optimization and Applied mathematics in addition to PageRank.
His most cited work include:
- The webgraph framework I: compression techniques (917 citations)
- UbiCrawler: a scalable fully distributed web crawler (477 citations)
- Layered label propagation: a multiresolution coordinate-free ordering for compressing social networks (422 citations)
What are the main themes of his work throughout his whole career to date?
Paolo Boldi spends much of his time researching Theoretical computer science, Combinatorics, Discrete mathematics, Graph and World Wide Web.
He specializes in Theoretical computer science, namely PageRank.
His studies in PageRank integrate themes in fields like Graph and Rank.
His work in the fields of Degree, Cayley graph and Graph theory overlaps with other areas such as Sense of direction.
His work in Discrete mathematics covers topics such as Perfect hash function which are related to areas like Dynamic perfect hashing.
His work deals with themes such as Hyperlink and Information retrieval, which intersect with Graph.
He most often published in these fields:
- Theoretical computer science (27.74%)
- Combinatorics (20.00%)
- Discrete mathematics (20.00%)
What were the highlights of his more recent work (between 2014-2020)?
- Theoretical computer science (27.74%)
- Information retrieval (10.32%)
- Graph (17.42%)
In recent papers he was focusing on the following fields of study:
Paolo Boldi mainly investigates Theoretical computer science, Information retrieval, Graph, Software and Graph.
Paolo Boldi has included themes like Algorithm, Social graph and Complex network in his Theoretical computer science study.
The Folksonomy research he does as part of his general Information retrieval study is frequently linked to other disciplines of science, such as Noise, therefore creating a link between diverse domains of science.
His Graph research includes elements of Hyperlink, Data mining, Time complexity, Named entity and Knowledge base.
Paolo Boldi works mostly in the field of Graph, limiting it down to concerns involving Web page and, occasionally, Rank correlation, Ranking, Search engine and Approximation algorithm.
His research investigates the connection between PageRank and topics such as Monotone polygon that intersect with problems in Discrete mathematics.
Between 2014 and 2020, his most popular works were:
- Cleansing Wikipedia Categories using Centrality (14 citations)
- BUbiNG: Massive Crawling for the Masses (12 citations)
- Rank monotonicity in centrality measures (10 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Artificial intelligence
- Programming language
Theoretical computer science, Host, Web crawler, Throughput and Crawling are his primary areas of study.
Paolo Boldi carries out multidisciplinary research, doing studies in Theoretical computer science and Compression.
His Host study combines topics from a wide range of disciplines, such as Java and Distributed computing.
His Java study deals with Software intersecting with Graph compression, Computer engineering, Random access and Source code.
His Complex network research incorporates themes from Independence and Context.
Paolo Boldi focuses mostly in the field of Context, narrowing it down to topics relating to Feature and, in certain cases, Statistical assumption and Selection.
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