Pavel Pecina
About
In The Last Decade
Pavel Pecina
81 papers receiving 1000 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 952
- Computer Vision and Pattern Recognition 177
- Information Systems 127
- Molecular Biology 87
- Language and Linguistics 85
Countries citing papers authored by Pavel Pecina
This map shows the geographic impact of Pavel Pecina'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 Pavel Pecina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavel Pecina more than expected).
Fields of papers citing papers by Pavel Pecina
This network shows the impact of papers produced by Pavel Pecina. 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 Pavel Pecina. The network helps show where Pavel Pecina may publish in the future.
Co-authorship network of co-authors of Pavel Pecina
This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Pecina. A scholar is included among the top collaborators of Pavel Pecina 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 Pavel Pecina. Pavel Pecina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | CUNI team: CLEF eHealth Consumer Health Search Task 2018. | 1 |
| 3 | Task3 Patient-Centred Information Retrieval: Team CUNI. | 3 |
| 4 | Feature Extraction for Native Language Identification Using Language Modeling | 2 |
| 5 | 335 | |
| 6 | CUNI at the ShARe/CLEF eHealth Evaluation Lab 2014 | 1 |
| 7 | Task 3 : User-centred health information retrieval : | 5 |
| 8 | Simpler unsupervised POS tagging with bilingual projections | 14 |
| 9 | Determining Compositionality of Word Expressions Using Word Space Models | 2 |
| 10 | Syntactic Identification of Occurrences of Multiword Expressions in Text using a Lexicon with Dependency Structures | 8 |
| 11 | Simple and Effective Parameter Tuning for Domain Adaptation of Statistical Machine Translation | 11 |
| 12 | A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation | 2 |
| 13 | Arabic Word Generation and Modelling for Spell Checking | 28 |
| 14 | An Open-Source Finite State Morphological Transducer for Modern Standard Arabic | 22 |
| 15 | Handling Named Entities and Compound Verbs in Phrase-Based Statistical Machine Translation | 19 |
| 16 | An Augmented Three-Pass System Combination Framework: DCU Combination System for WMT 2010 | 5 |
| 17 | Czech Information Retrieval with Syntax-based Language Models | 2 |
| 18 | MATREX: The DCU MT System for WMT 2010 | 25 |
| 19 | Validating the Quality of Full Morphological Annotation. | 1 |
| 20 | Semi-automatic Building of Swedish Collocation Lexicon. | 1 |
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.