Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Automatically assessing review helpfulness
2006353 citationsPatrick Pantel, Marco Pennacchiotti et al.profile →
Espresso
2006343 citationsPatrick Pantel, Marco Pennacchiottiprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Marco Pennacchiotti
Since
Specialization
Citations
This map shows the geographic impact of Marco Pennacchiotti'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 Marco Pennacchiotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Pennacchiotti more than expected).
Fields of papers citing papers by Marco Pennacchiotti
This network shows the impact of papers produced by Marco Pennacchiotti. 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 Marco Pennacchiotti. The network helps show where Marco Pennacchiotti may publish in the future.
Co-authorship network of co-authors of Marco Pennacchiotti
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Pennacchiotti.
A scholar is included among the top collaborators of Marco Pennacchiotti 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 Marco Pennacchiotti. Marco Pennacchiotti is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Jain, Alpa & Marco Pennacchiotti. (2010). Open Entity Extraction from Web Search Query Logs. International Conference on Computational Linguistics. 510–518.34 indexed citations
6.
Pennacchiotti, Marco & Ana-Maria Popescu. (2010). Detecting controversies in Twitter: a first study. North American Chapter of the Association for Computational Linguistics. 31–32.5 indexed citations
7.
Zanzotto, Fabio Massimo & Marco Pennacchiotti. (2010). Expanding textual entailment corpora fromWikipedia using co-training. International Conference on Computational Linguistics. 28–36.21 indexed citations
Hendrickx, Iris, Su Nam Kim, Zornitsa Kozareva, et al.. (2009). Multi-way classification of semantic relations between pairs of nominals. North American Chapter of the Association for Computational Linguistics. 94–99.10 indexed citations
10.
Hendrickx, Iris, Su Nam Kim, Zornitsa Kozareva, et al.. (2009). SemEval-2010 task 8. 94–94.239 indexed citations
11.
Pennacchiotti, Marco, et al.. (2008). Towards a Vector Space Model for FrameNet-like Resources.. Language Resources and Evaluation.4 indexed citations
12.
Burchardt, Aljoscha & Marco Pennacchiotti. (2008). FATE: a FrameNet-Annotated Corpus for Textual Entailment.. Language Resources and Evaluation.13 indexed citations
13.
Zanzotto, Fabio Massimo, Marco Pennacchiotti, & Alessandro Moschitti. (2008). PeMoZa submission to TAC 2008. Theory and applications of categories.1 indexed citations
14.
Gliozzo, Alfio, Marco Pennacchiotti, & Patrick Pantel. (2007). The Domain Restriction Hypothesis: Relating Term Similarity and Semantic Consistency. North American Chapter of the Association for Computational Linguistics. 131–138.6 indexed citations
15.
Pennacchiotti, Marco & Fabio Massimo Zanzotto. (2007). Learning shallow semantic rules for textual entailment. Cineca Institutional Research Information System (Tor Vergata University). 458–462.3 indexed citations
16.
Pazienza, Maria Teresa, Marco Pennacchiotti, & Fabio Massimo Zanzotto. (2006). Mixing WordNet, VerbNet and PropBank for studying verb relations. Language Resources and Evaluation. 1372–1377.7 indexed citations
17.
Pennacchiotti, Marco, et al.. (2006). Learning textual entailment from examples. Cineca Institutional Research Information System (Tor Vergata University).7 indexed citations
Basili, Roberto, et al.. (2005). Ontology-driven Information Retrieval in FF-Poirot..1 indexed citations
20.
Pazienza, Maria Teresa, Marco Pennacchiotti, & Fabio Massimo Zanzotto. (2004). Identifying relational concept lexicalisations by using general linguistic knowledge. European Conference on Artificial Intelligence. 1071–1072.3 indexed citations
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.