What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Database
- The Internet
Alberto H. F. Laender mainly focuses on Information retrieval, Data mining, Web page, Quality and Web mapping.
His studies in Information retrieval integrate themes in fields like Hierarchical clustering, Context and Categorization.
His biological study spans a wide range of topics, including Data modeling and Spatial analysis.
His work on Web modeling as part of general Web page study is frequently linked to Metric, therefore connecting diverse disciplines of science.
Data Web covers Alberto H. F. Laender research in Web mapping.
The concepts of his Data Web study are interwoven with issues in Information extraction and Web mining.
His most cited work include:
- A brief survey of web data extraction tools (647 citations)
- Automatic web news extraction using tree edit distance (328 citations)
- A brief survey of automatic methods for author name disambiguation (205 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Information retrieval, World Wide Web, Data mining, Quality and Database.
His Information retrieval course of study focuses on Context and Machine learning.
The Web page and The Internet research Alberto H. F. Laender does as part of his general World Wide Web study is frequently linked to other disciplines of science, such as Data extraction, therefore creating a link between diverse domains of science.
Alberto H. F. Laender combines subjects such as Data deduplication, Data integrity, Genetic programming and Set with his study of Data mining.
As a member of one scientific family, Alberto H. F. Laender mostly works in the field of Quality, focusing on Task and, on occasion, Data science, Artificial intelligence and Key.
His Data Web research includes themes of Static web page and Web mining.
He most often published in these fields:
- Information retrieval (36.27%)
- World Wide Web (23.04%)
- Data mining (15.69%)
What were the highlights of his more recent work (between 2013-2021)?
- Information retrieval (36.27%)
- Task (8.82%)
- Quality (11.76%)
In recent papers he was focusing on the following fields of study:
Alberto H. F. Laender mostly deals with Information retrieval, Task, Quality, Context and Data science.
The study incorporates disciplines such as XML, Data mining, Ambiguity and Citation in addition to Information retrieval.
His Task research incorporates elements of Resource and Categorization.
Alberto H. F. Laender has researched Quality in several fields, including Noise and Social network.
His Context research includes elements of Consistency, Machine learning, Distributed computing and Artificial intelligence.
His Data science study combines topics in areas such as Database and Interpersonal ties.
Between 2013 and 2021, his most popular works were:
- Self-training author name disambiguation for information scarce scenarios (29 citations)
- On the combination of domain-specific heuristics for author name disambiguation: the nearest cluster method (24 citations)
- Incremental author name disambiguation by exploiting domain-specific heuristics (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Database
- The Internet
His scientific interests lie mostly in Information retrieval, Heuristics, Author name, Citation and Domain.
His specific area of interest is Information retrieval, where Alberto H. F. Laender studies Learning to rank.
The study of Citation is intertwined with the study of Data science in a number of ways.
His studies examine the connections between Domain and genetics, as well as such issues in Resource, with regards to Knowledge management.
His Set research is multidisciplinary, relying on both Training set, Transduction and Bootstrapping.
Alberto H. F. Laender has included themes like Crowdsourcing, Cataloging, World Wide Web and Context in his Task study.
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