Massimo Melucci

2.2k citations
105 papers · 1.1k · h-index 19

Impact in

    • Topic Modeling
    • Advanced Text Analysis Techniques
    • Natural Language Processing Techniques
    • Semantic Web and Ontologies
    • Sentiment Analysis and Opinion Mining
    • Quantum Computing Algorithms and Architecture
    • Information Retrieval and Search Behavior
    • Web Data Mining and Analysis

Papers in

Massimo Melucci

101 papers receiving 990 citations

Peers

Massimo Melucci
Comparison fields: 5 of 101
  • Artificial Intelligence 682
  • Information Systems 348
  • Signal Processing 156
  • Computer Vision and Pattern Recognition 225
  • Computer Science Applications 46
Replace Dafna Shahaf with:
Dafna Shahaf United States
Gabriel Murray Canada
Judith L. Klavans United States
Benjamin Piwowarski France
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Zuhair Bandar United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Massimo Melucci

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Melucci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Melucci. 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 Massimo Melucci. The network helps show where Massimo Melucci may publish in the future.

Co-authors

The 25 scholars most cited alongside Massimo Melucci, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Massimo Melucci Line = papers co-authored together Massimo Melucci links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020102
2 200852
3 200351
4 201549
5 200444
6 201938
7 200735
8 199533
9 202132
10 199728
11 199925
12 200523
13 201823
14 199623
15 201522
16 201121
17 201220
18 200319
19 202119
20
201918

About Massimo Melucci

Massimo Melucci is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 105 papers that have together received 1.1k indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (30 papers), Semantic Web and Ontologies (21 papers), Advanced Text Analysis Techniques (19 papers), Web Data Mining and Analysis (13 papers), Music and Audio Processing (12 papers), Topic Modeling (12 papers), Image Retrieval and Classification Techniques (10 papers) and Data Management and Algorithms (9 papers). The work is most often cited by research in Artificial Intelligence (682 citations), Information Systems (348 citations), Signal Processing (156 citations), Computer Vision and Pattern Recognition (225 citations) and Computer Science Applications (46 citations). Massimo Melucci has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Nicola Orio, Fábio Crestani, Qiuchi Li, Prayag Tiwari, Dimitris Gkoumas, Maristella Agosti, Christina Lioma, Nicola Ferro, Monica Landoni and Ryen W. White. Their work appears in journals such as Information Processing & Management, ACM SIGIR Forum, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems and Computer Science Review.

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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