David Martins de Matos

848 total citations
58 papers, 449 citations indexed

About

David Martins de Matos is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, David Martins de Matos has authored 58 papers receiving a total of 449 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 15 papers in Computer Vision and Pattern Recognition and 10 papers in Information Systems. Recurrent topics in David Martins de Matos's work include Topic Modeling (25 papers), Natural Language Processing Techniques (21 papers) and Speech and dialogue systems (10 papers). David Martins de Matos is often cited by papers focused on Topic Modeling (25 papers), Natural Language Processing Techniques (21 papers) and Speech and dialogue systems (10 papers). David Martins de Matos collaborates with scholars based in Portugal, United States and Japan. David Martins de Matos's co-authors include Ricardo Ribeiro, Paula Vaz, Luís Marujo, Bruno Martins, João P. Neto, Anatole Gershman, Jaime Carbonell, Luísa Coheur, Hugo Rosa and João Paulo Carvalho and has published in prestigious journals such as SHILAP Revista de lepidopterología, Knowledge-Based Systems and Pattern Recognition Letters.

In The Last Decade

David Martins de Matos

49 papers receiving 429 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
David Martins de Matos Portugal	13	323	101	89	79	36	58	449
Fuliang Weng United States	14	567 1.8×	116 1.1×	62 0.7×	91 1.2×	37 1.0×	48	668
Luísa Coheur Portugal	11	596 1.8×	103 1.0×	40 0.4×	91 1.2×	176 4.9×	68	689
Elias Iosif Greece	13	332 1.0×	142 1.4×	60 0.7×	37 0.5×	43 1.2×	53	525
Xingyu Pan China	8	264 0.8×	325 3.2×	87 1.0×	33 0.4×	14 0.4×	15	470
Gaël Dias France	13	368 1.1×	128 1.3×	42 0.5×	79 1.0×	81 2.3×	60	525
Fadi Biadsy United States	20	821 2.5×	57 0.6×	158 1.8×	295 3.7×	23 0.6×	41	1.0k
Gary Geunbae Lee South Korea	15	608 1.9×	82 0.8×	52 0.6×	30 0.4×	55 1.5×	67	681
Kenji Kita Japan	10	310 1.0×	79 0.8×	118 1.3×	69 0.9×	12 0.3×	114	494
Francis Ferraro United States	9	262 0.8×	68 0.7×	145 1.6×	23 0.3×	11 0.3×	40	383
Roeland Ordelman Netherlands	14	499 1.5×	82 0.8×	295 3.3×	254 3.2×	91 2.5×	77	798

Countries citing papers authored by David Martins de Matos

Since Specialization

Citations

This map shows the geographic impact of David Martins de Matos'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 David Martins de Matos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Martins de Matos more than expected).

Fields of papers citing papers by David Martins de Matos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Martins de Matos. 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 David Martins de Matos. The network helps show where David Martins de Matos may publish in the future.

Co-authorship network of co-authors of David Martins de Matos

This figure shows the co-authorship network connecting the top 25 collaborators of David Martins de Matos. A scholar is included among the top collaborators of David Martins de Matos 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 David Martins de Matos. David Martins de Matos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ferreira‐Gomes, Joana, et al.. (2023). Modeling Chronic Pain Experiences from Online Reports Using the Reddit Reports of Chronic Pain Dataset. Information. 14(4). 237–237. 1 indexed citations

Matos, David Martins de, et al.. (2021). Assessing kinetic meaning of music and dance via deep cross-modal retrieval. Neural Computing and Applications. 33(21). 14481–14493. 5 indexed citations

Ribeiro, Ricardo, et al.. (2020). Mapping the Dialog Act Annotations of the LEGO Corpus into ISO 24617-2 Communicative Functions.. Language Resources and Evaluation. 531–539. 1 indexed citations

Ribeiro, Ricardo, et al.. (2019). L2F/INESC-ID at SemEval-2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations. 130–136. 10 indexed citations

Ribeiro, Ricardo, et al.. (2019). A Multilingual and Multidomain Study on Dialog Act Recognition Using Character-Level Tokenization. Information. 10(3). 94–94. 7 indexed citations

Batista, Fernando, Isabel Trancoso, Alberto Abad, et al.. (2016). SPA: Web-based Platform for easy Access to Speech Processing Modules. Language Resources and Evaluation. 3886–3892. 1 indexed citations

Marujo, Luís, Ling Wang, Isabel Trancoso, et al.. (2015). Automatic Keyword Extraction on Twitter. 637–643. 38 indexed citations

Oliveira, Luís, et al.. (2015). Evaluating pictogram prediction in a location-aware augmentative and alternative communication system. Assistive Technology. 28(2). 83–92. 8 indexed citations

Moniz, Helena, Fernando Batista, Ricardo Ribeiro, et al.. (2014). Revising the annotation of a Broadcast News corpus: a linguistic approach. Language Resources and Evaluation. 3908–3913. 2 indexed citations

10.

Ribeiro, Ricardo, et al.. (2014). On the Application of Generic Summarization Algorithms to Music. IEEE Signal Processing Letters. 22(1). 26–30. 10 indexed citations

11.

Vaz, Paula, Ricardo Ribeiro, & David Martins de Matos. (2013). Understanding the Temporal Dynamics of Recommendations across Different Rating Scales. 2 indexed citations

12.

Vaz, Paula, Ricardo Ribeiro, & David Martins de Matos. (2012). LitRec vs. Movielens - A Comparative Study. 370–373. 3 indexed citations

13.

Vaz, Paula, David Martins de Matos, Bruno Martins, & Pável Calado. (2012). Improving a hybrid literary book recommendation system through author ranking. 387–388. 28 indexed citations

14.

Vaz, Paula, Ricardo Ribeiro, & David Martins de Matos. (2012). LitRec vs. Movielens - A Comparative Study. 370–373. 3 indexed citations

15.

Ribeiro, Ricardo & David Martins de Matos. (2011). Revisiting centrality-as-relevance: support sets and similarity as geometric proximity. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 42(1). 275–308. 15 indexed citations

16.

Wang, Ling, Joäo Graça, David Martins de Matos, Isabel Trancoso, & Alan W. Black. (2011). Discriminative Phrase-based Lexicalized Reordering Models using Weighted Reordering Graphs. International Joint Conference on Natural Language Processing. 47–55. 2 indexed citations

17.

Matos, David Martins de, et al.. (2010). Fairy Tale Corpus Organization Using Latent Semantic Mapping and an Item-to-item Top-n Recommendation Algorithm.. Language Resources and Evaluation. 13 indexed citations

18.

Ribeiro, Ricardo & David Martins de Matos. (2008). Using prior knowledge to assess relevance in speech summarization. 169–172. 2 indexed citations

19.

Mendes, Ana Cristina, Luísa Coheur, Nuno Mamede, et al.. (2007). QA@L2F@QA@CLEF.. CLEF (Working Notes). 1 indexed citations

20.

Matos, David Martins de, Ricardo Ribeiro, & Nuno Mamede. (2004). Rethinking Reusable Resources. Language Resources and Evaluation.

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.

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