H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 35 Citations 6,132 177 World Ranking 5947 National Ranking 280

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Machine learning

His primary areas of study are Linked data, Information retrieval, Data mining, RDF and World Wide Web. His study explores the link between Linked data and topics such as Rdf graph that cross with problems in Word. His research in Information retrieval intersects with topics in Metadata, Knowledge extraction and Benchmark.

He has included themes like Estimator, Web mining and Cluster analysis in his Data mining study. His work in RDF addresses issues such as Theoretical computer science, which are connected to fields such as Recommender system. His World Wide Web research is multidisciplinary, incorporating elements of Word-sense disambiguation and Key.

His most cited work include:

  • Knowledge graph refinement: A survey of approaches and evaluation methods (431 citations)
  • Adoption of the Linked Data Best Practices in Different Topical Domains (247 citations)
  • RDF2Vec: RDF Graph Embeddings for Data Mining (220 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Information retrieval, Linked data, World Wide Web, Artificial intelligence and Knowledge graph. His study in Information retrieval is interdisciplinary in nature, drawing from both Task and Set. His Linked data research is multidisciplinary, relying on both Recommender system, Data mining and Data science.

His study focuses on the intersection of World Wide Web and fields such as Human–computer interaction with connections in the field of Semantic computing. His Artificial intelligence research incorporates elements of Machine learning, Pattern recognition and Natural language processing. The various areas that Heiko Paulheim examines in his Knowledge graph study include Graph and Theoretical computer science.

He most often published in these fields:

  • Information retrieval (30.04%)
  • Linked data (26.61%)
  • World Wide Web (21.03%)

What were the highlights of his more recent work (between 2019-2021)?

  • Knowledge graph (17.17%)
  • Information retrieval (30.04%)
  • Theoretical computer science (8.15%)

In recent papers he was focusing on the following fields of study:

Heiko Paulheim spends much of his time researching Knowledge graph, Information retrieval, Theoretical computer science, Matching and Ontology alignment. His Knowledge graph research integrates issues from Graph, Knowledge representation and reasoning, Benchmark, Empirical research and Subject. While working on this project, he studies both Information retrieval and Popularity.

His studies in Matching integrate themes in fields like Ontology, Artificial intelligence, Extension, Supervised learning and Machine learning. His Ontology alignment study incorporates themes from Data mining and Presentation. His Linked data study in the realm of Semantic Web connects with subjects such as Common sense.

Between 2019 and 2021, his most popular works were:

  • On cognitive preferences and the plausibility of rule-based models (19 citations)
  • The knowledge graph track at OAEI : Gold standards, baselines, and the golden hammer bias (11 citations)
  • Knowledge Graphs on the Web -- an Overview (6 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Programming language
  • Machine learning

Knowledge graph, Information retrieval, Graph, Theoretical computer science and Matching are his primary areas of study. His research integrates issues of Business domain, World Wide Web and Knowledge representation and reasoning in his study of Knowledge graph. He merges many fields, such as Information retrieval and Group evaluation, in his writings.

His Graph study spans across into fields like Graph, Web API, Embedding, Current and Focus. Heiko Paulheim has researched Matching in several fields, including Ontology, Artificial intelligence, Ontology alignment, Extension and Supervised learning. His Ontology alignment research is multidisciplinary, incorporating perspectives in User interface, Task and Confidence threshold.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Knowledge graph refinement: A survey of approaches and evaluation methods

Heiko Paulheim.
Social Work (2016)

849 Citations

Adoption of the Linked Data Best Practices in Different Topical Domains

Max Schmachtenberg;Christian Bizer;Heiko Paulheim.
international semantic web conference (2014)

474 Citations

RDF2Vec: RDF Graph Embeddings for Data Mining

Petar Ristoski;Heiko Paulheim.
international semantic web conference (2016)

359 Citations

Semantic Web in data mining and knowledge discovery

Petar Ristoski;Heiko Paulheim.
Journal of Web Semantics (2016)

270 Citations

Unsupervised generation of data mining features from linked open data

Heiko Paulheim;Johannes Fümkranz.
web intelligence, mining and semantics (2012)

200 Citations

Type Inference on Noisy RDF Data

Heiko Paulheim;Christian Bizer.
international semantic web conference (2013)

197 Citations

Improving the Quality of Linked Data Using Statistical Distributions

Heiko Paulheim;Christian Bizer.
International Journal on Semantic Web and Information Systems (2014)

174 Citations

A Multi-Indicator Approach for Geolocalization of Tweets

Axel Schulz;Aristotelis Hadjakos;Heiko Paulheim;Johannes Nachtwey.
international conference on weblogs and social media (2013)

168 Citations

I See a Car Crash: Real-Time Detection of Small Scale Incidents in Microblogs

Axel Schulz;Petar Ristoski;Heiko Paulheim.
extended semantic web conference (2013)

158 Citations

RDF2Vec: RDF graph embeddings and their applications

Petar Ristoski;Jessica Rosati;Jessica Rosati;Tommaso Di Noia;Renato De Leone.
Social Work (2019)

115 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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