Chris Mellish
About
In The Last Decade
Chris Mellish
126 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 172
- Artificial Intelligence 2.6k
- Information Systems 488
- Computational Theory and Mathematics 429
- Computer Networks and Communications 386
- Computer Vision and Pattern Recognition 308
Countries citing papers authored by Chris Mellish
This map shows the geographic impact of Chris Mellish'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 Chris Mellish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Mellish more than expected).
Fields of papers citing papers by Chris Mellish
This network shows the impact of papers produced by Chris Mellish. 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 Chris Mellish. The network helps show where Chris Mellish may publish in the future.
Co-authorship network of co-authors of Chris Mellish
This figure shows the co-authorship network connecting the top 25 collaborators of Chris Mellish. A scholar is included among the top collaborators of Chris Mellish 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 Chris Mellish. Chris Mellish is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | Overview of the First Content Selection Challenge from Open Semantic Web Data | 2 |
| 3 | Corpus-based metrics for assessing communal common ground | 2 |
| 4 | Blogging birds: Generating narratives about reintroduced species to promote public engagement | 5 |
| 5 | Content Selection From Semantic Web Data | 11 |
| 6 | A Policy-Based Approach to Context Dependent Natural Language Generation | 5 |
| 7 | Using semantic web technology to support NLG case study: OWL finds RAGS | 3 |
| 8 | 23 | |
| 9 | Natural Language Directed Inference in the Presentation of Ontologies | 8 |
| 10 | Using a Corpus of Sentence Orderings Defined by Many Experts to Evaluate Metrics of Coherence for Text Structuring | 6 |
| 11 | Proceedings of the First International Natural Language Generation Conference | 2 |
| 12 | Enabling Resource Sharing in Language Generation: an Abstract Reference Architecture | 11 |
| 13 | Pragmatic Analysis of Teachers' Language. Towards an Empirically Based Approach. | 6 |
| 14 | 49 | |
| 15 | Experiments Using Stochastic Search for Text Planning | 56 |
| 16 | An empirical study on the generation of anaphora in Chinese | 22 |
| 17 | 22 | |
| 18 | 1 | |
| 19 | Natural Language Generation Applications to Technical Documentation: A View Through IDAS | 0 |
| 20 | Implementing systemic classification by unification | 44 |
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.