Florian Laws
Impact in
- Artificial Intelligence top 5%
- Natural Language Processing Techniques
- Topic Modeling
- Machine Learning and Algorithms
- Speech and dialogue systems
- Machine Learning and Data Classification
- Algorithms and Data Compression
- Text Readability and Simplification
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
Papers in
-
- Topic Modeling 6
- Natural Language Processing Techniques 4
- Machine Learning and Algorithms 4
- Algorithms and Data Compression 3
- Semantic Web and Ontologies 2
- Machine Learning and Data Classification 2
- Advanced Text Analysis Techniques 1
- Data Stream Mining Techniques 1
- Co-authors
- Helmut Schmid (1 shared paper)Hinrich Schütze (6 shared papers)Beate Dorow (3 shared papers)Ulrich Heid (2 shared papers)Udo Hahn (1 shared paper)Katrin Tomanek (1 shared paper)Florian Heimerl (1 shared paper)
- Journals
- Language Resources and Evaluation (1 paper)North American Chapter of the Association for Computational Linguistics (1 paper)International Conference on Computational Linguistics (2 papers)Empirical Methods in Natural Language Processing (1 paper)
- Partner nations
- Germany
In The Last Decade
Florian Laws
9 papers receiving 240 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 247
- Computer Science Applications 36
- Language and Linguistics 33
- Information Systems 16
- Linguistics and Language 3
Countries citing papers authored by Florian Laws
This map shows the geographic impact of Florian Laws'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 Florian Laws with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Laws more than expected).
Fields of papers citing papers by Florian Laws
This network shows the impact of papers produced by Florian Laws. 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 Florian Laws. The network helps show where Florian Laws may publish in the future.
Co-authors
The 7 scholars most cited alongside Florian Laws, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 120 | |
| 2 | Active Learning with Amazon Mechanical Turk | 2011 | 48 |
| 3 | 2008 | 46 | |
| 4 | A Linguistically Grounded Graph Model for Bilingual Lexicon Extraction | 2010 | 21 |
| 5 | 2009 | 13 | |
| 6 | Sentiment Translation through Multi-Edge Graphs | 2010 | 9 |
| 7 | 2009 | 9 | |
| 8 | Active Learning for Coreference Resolution | 2012 | 7 |
| 9 | Building a Cross-lingual Relatedness Thesaurus using a Graph Similarity Measure. | 2010 | 4 |
About Florian Laws
Florian Laws is a scholar working on Artificial Intelligence, Information Systems, Computer Science Applications, Infectious Diseases and Organic Chemistry, having authored 9 papers that have together received 277 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers), Machine Learning and Algorithms (4 papers), Algorithms and Data Compression (3 papers), Semantic Web and Ontologies (2 papers), Machine Learning and Data Classification (2 papers), Advanced Text Analysis Techniques (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (247 citations), Computer Science Applications (36 citations), Language and Linguistics (33 citations), Information Systems (16 citations) and Linguistics and Language (3 citations). Florian Laws has collaborated with scholars based in Germany. Frequent co-authors include Helmut Schmid, Hinrich Schütze, Beate Dorow, Ulrich Heid, Udo Hahn, Katrin Tomanek and Florian Heimerl. Their work appears in journals such as Language Resources and Evaluation, North American Chapter of the Association for Computational Linguistics, International Conference on Computational Linguistics and Empirical Methods in Natural Language Processing.
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.