What is she best known for?
The fields of study she is best known for:
- Programming language
- Database
- Artificial intelligence
Susan B. Davidson spends much of her time researching XML, Workflow, Database, Theoretical computer science and Data science.
Susan B. Davidson interconnects WordNet, Information retrieval and Relational database management system in the investigation of issues within XML.
The study incorporates disciplines such as High availability, Technical report, Correctness and Software engineering in addition to Database.
Her Theoretical computer science research is multidisciplinary, relying on both Ground truth, Path expression and Data model.
Her Data science research incorporates themes from View integration, Point and Dimensional modeling.
Her biological study spans a wide range of topics, including XML Signature and XML schema.
Her most cited work include:
- A query language and optimization techniques for unstructured data (542 citations)
- Consistency in a partitioned network: a survey (532 citations)
- Adding Structure to Unstructured Data (420 citations)
What are the main themes of her work throughout her whole career to date?
Workflow, Information retrieval, Database, Theoretical computer science and XML are her primary areas of study.
Her research integrates issues of World Wide Web and Data science in her study of Workflow.
Her Information retrieval study frequently draws connections to adjacent fields such as Data citation.
Susan B. Davidson combines subjects such as Time complexity, Path expression, Set and Data mining with her study of Theoretical computer science.
Her research related to XML validation, XML database, XML framework and XML schema might be considered part of XML.
Her studies in XML validation integrate themes in fields like XML Signature and XML Schema Editor.
She most often published in these fields:
- Workflow (22.45%)
- Information retrieval (22.45%)
- Database (19.39%)
What were the highlights of her more recent work (between 2012-2021)?
- Information retrieval (22.45%)
- Data science (13.27%)
- Workflow (22.45%)
In recent papers she was focusing on the following fields of study:
Her main research concerns Information retrieval, Data science, Workflow, Data citation and Provenance.
A large part of her Information retrieval studies is devoted to Query language.
Her work deals with themes such as Ontology, Key, Data management and World Wide Web, which intersect with Data science.
Her study on Workflow management system is often connected to Reuse as part of broader study in Workflow.
Her Data citation research integrates issues from Conjunctive query, Open research and Database theory.
Her Theoretical computer science study incorporates themes from Contrast, Oracle and Query optimization.
Between 2012 and 2021, her most popular works were:
- Using the crowd for top-k and group-by queries (108 citations)
- Realizing the potential of data science (34 citations)
- Why data citation is a computational problem (33 citations)
In her most recent research, the most cited papers focused on:
- Programming language
- Database
- Artificial intelligence
Her scientific interests lie mostly in Information retrieval, Data citation, Data science, Data mining and Theoretical computer science.
The Data citation study combines topics in areas such as Raising, Open research and Database theory.
She has researched Data science in several fields, including Query language, World Wide Web, Key, Synthetic data and Computational problem.
Her Data mining research includes themes of Workflow technology, Workflow engine, Workflow and Dataflow.
Her Workflow technology research incorporates elements of Workflow management system, Similarity measure and Distributed computing.
Her Theoretical computer science study integrates concerns from other disciplines, such as Value, XML and Cluster analysis.
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