Christopher Akiki
Impact in
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- Music and Audio Processing
Papers in
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- Topic Modeling 4
- Natural Language Processing Techniques 4
- Semantic Web and Ontologies 3
- Imbalanced Data Classification Techniques 1
- Sentiment Analysis and Opinion Mining 1
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- Information Retrieval and Search Behavior 2
- Web Data Mining and Analysis 1
- Co-authors
- Manuel Burghardt (2 shared papers)Martin Potthast (6 shared papers)Aleksandra Piktus (3 shared papers)Anna Rogers (1 shared paper)Sebastian Simon (1 shared paper)Paulo Villegas (1 shared paper)Benno Stein (3 shared papers)Gérard Dupont (1 shared paper)
- Journals
- Physical Review Materials (1 paper)Qucosa (Saxon State and University Library Dresden) (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- GermanyItalyUnited States
In The Last Decade
Christopher Akiki
7 papers receiving 31 citations
Peers
Comparison fields: 5 of 26
- Health Informatics 2
- Signal Processing 7
- Health Information Management 2
- Artificial Intelligence 13
- Computer Science Applications 2
Countries citing papers authored by Christopher Akiki
This map shows the geographic impact of Christopher Akiki'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 Christopher Akiki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Akiki more than expected).
Fields of papers citing papers by Christopher Akiki
This network shows the impact of papers produced by Christopher Akiki. 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 Christopher Akiki. The network helps show where Christopher Akiki may publish in the future.
Co-authors
The 21 scholars most cited alongside Christopher Akiki, 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 | 2023 | 12 | |
| 2 | 2023 | 11 | |
| 3 | 2021 | 6 | |
| 4 | 2023 | 1 | |
| 5 | 2024 | 1 | |
| 6 | Toward a Musical Sentiment (MuSe) Dataset for Affective Distant Hearing. | 2020 | 1 |
| 7 | 2023 | 1 | |
| 8 | 2024 | 0 | |
| 9 | Exploring Argument Retrieval with Transformers. | 2020 | 0 |
| 10 | 2023 | 0 | |
| 11 | 2023 | 0 |
About Christopher Akiki
Christopher Akiki is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Cognitive Neuroscience and Speech and Hearing, having authored 11 papers that have together received 33 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers), Semantic Web and Ontologies (3 papers), Music and Audio Processing (2 papers), Information Retrieval and Search Behavior (2 papers), Imbalanced Data Classification Techniques (1 paper), Web Data Mining and Analysis (1 paper) and Sentiment Analysis and Opinion Mining (1 paper). The work is most often cited by research in Health Informatics (2 citations), Signal Processing (7 citations), Health Information Management (2 citations), Artificial Intelligence (13 citations) and Computer Science Applications (2 citations). Christopher Akiki has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Manuel Burghardt, Martin Potthast, Aleksandra Piktus, Anna Rogers, Sebastian Simon, Paulo Villegas, Benno Stein, Gérard Dupont, Norbert Siegmund and Yacine Jernite. Their work appears in journals such as Physical Review Materials, Qucosa (Saxon State and University Library Dresden), DOAJ (DOAJ: Directory of Open Access Journals), ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.