John P. McCrae
- Artificial Intelligence top 1%
- Information Systems top 5%
- Language and Linguistics top 2%
- Molecular Biology
- Communication top 5%
- Co-authors
- Bharathi Raja ChakravarthiPhilipp CimianoPaul BuitelaarMihael ArčanRuba PriyadharshiniElena Montiel-PonsodaShardul SuryawanshiElizabeth Sherly
- Topics
- Natural Language Processing Techniques (100 papers)Semantic Web and Ontologies (52 papers)Topic Modeling (50 papers)
In The Last Decade
John P. McCrae
118 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 1.3k
- Information Systems 211
- Language and Linguistics 190
- Molecular Biology 183
- Communication 82
Countries citing papers authored by John P. McCrae
This map shows the geographic impact of John P. McCrae's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John P. McCrae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John P. McCrae more than expected).
Fields of papers citing papers by John P. McCrae
This network shows the impact of papers produced by John P. McCrae. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John P. McCrae. The network helps show where John P. McCrae may publish in the future.
Co-authorship network of co-authors of John P. McCrae
This figure shows the co-authorship network connecting the top 25 collaborators of John P. McCrae. A scholar is included among the top collaborators of John P. McCrae based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John P. McCrae. John P. McCrae is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 11 | |
| 4 | 0 | |
| 5 | 48 | |
| 6 | Overview of the track on HASOC-Offensive Language Identification-DravidianCodeMix | 30 |
| 7 | 8 | |
| 8 | A Comparative Study of SVM and LSTM Deep Learning Algorithms for Stock Market Prediction. | 26 |
| 9 | 18 | |
| 10 | 2 | |
| 11 | 29 | |
| 12 | LIXR: Quick, succinct conversion of XML to RDF. | 1 |
| 13 | Representing Multilingual Data as Linked Data: the Case of BabelNet 2.0 | 42 |
| 14 | 7 | |
| 15 | A lemon lexicon for DBpedia | 18 |
| 16 | 2 | |
| 17 | Collaborative semantic editing of linked data lexica | 11 |
| 18 | Combining statistical and semantic approaches to the translation of ontologies and taxonomies | 11 |
| 19 | 8 | |
| 20 | 1 |
About John P. McCrae
John P. McCrae is a scholar working on Artificial Intelligence, Language and Linguistics and Information Systems, having authored 135 papers that have together received 1.5k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (100 papers), Semantic Web and Ontologies (52 papers) and Topic Modeling (50 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Language and Linguistics (190 citations) and Communication (82 citations). John P. McCrae has collaborated with scholars based in Ireland, Germany and Spain. Frequent co-authors include Bharathi Raja Chakravarthi, Philipp Cimiano, Paul Buitelaar, Mihael Arčan, Ruba Priyadharshini, Elena Montiel-Ponsoda, Shardul Suryawanshi, Elizabeth Sherly, Navya Jose and Jorge Gracia. Their work appears in journals such as BMJ, BMC Bioinformatics and Pharmacoepidemiology and Drug Safety.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.