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.
Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
2015431 citationsAliaksei Severyn, Alessandro MoschittiInstitutional Research Information System (Università degli Studi di Trento)profile →
Twitter Sentiment Analysis with Deep Convolutional Neural Networks
2015409 citationsAliaksei Severyn, Alessandro MoschittiInstitutional Research Information System (Università degli Studi di Trento)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Alessandro Moschitti
Since
Specialization
Citations
This map shows the geographic impact of Alessandro Moschitti'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 Alessandro Moschitti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alessandro Moschitti more than expected).
Fields of papers citing papers by Alessandro Moschitti
This network shows the impact of papers produced by Alessandro Moschitti. 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 Alessandro Moschitti. The network helps show where Alessandro Moschitti may publish in the future.
Co-authorship network of co-authors of Alessandro Moschitti
This figure shows the co-authorship network connecting the top 25 collaborators of Alessandro Moschitti.
A scholar is included among the top collaborators of Alessandro Moschitti 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 Alessandro Moschitti. Alessandro Moschitti is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Moschitti, Alessandro, et al.. (2018). Learning to Progressively Recognize New Named Entities with Sequence to Sequence Models. Institutional Research Information System (Università degli Studi di Trento). 2181–2191.8 indexed citations
3.
Hoque, Enamul, Shafiq Joty, Lluı́s Màrquez, et al.. (2016). An interactive system for exploring community question answering forums. International Conference on Computational Linguistics. 1–5.4 indexed citations
4.
Moschitti, Alessandro, et al.. (2015). Distant supervision for relation extraction using tree kernels.3 indexed citations
5.
Saleh, Iman, Scott Cyphers, Jim Glass, et al.. (2014). A Study of using Syntactic and Semantic Structures for Concept Segmentation and Labeling. Institutional Research Information System (Università degli Studi di Trento). 193–202.3 indexed citations
6.
Severyn, Aliaksei, et al.. (2013). Learning Adaptable Patterns for Passage Reranking. Institutional Research Information System (Università degli Studi di Trento). 75–83.30 indexed citations
7.
Moschitti, Alessandro. (2012). State-of-the-Art Kernels for Natural Language Processing. Institutional Research Information System (Università degli Studi di Trento). 2–2.7 indexed citations
8.
Moschitti, Alessandro, Qi Ju, & Richard Johansson. (2012). Modeling Topic Dependencies in Hierarchical Text Categorization. Institutional Research Information System (Università degli Studi di Trento). 759–767.3 indexed citations
9.
Uryupina, Olga, Alessandro Moschitti, & Massimo Poesio. (2012). BART goes multilingual: The UniTN / Essex submission to the CoNLL-2012 Shared Task. Empirical Methods in Natural Language Processing. 122–128.12 indexed citations
10.
Johansson, Richard & Alessandro Moschitti. (2011). Extracting Opinion Expressions and Their Polarities -- Exploration of Pipelines and Joint Models. Meeting of the Association for Computational Linguistics. 101–106.27 indexed citations
11.
Moschitti, Alessandro, et al.. (2010). Kernel-based Reranking for Named-Entity Extraction. Institutional Research Information System (Università degli Studi di Trento). 901–909.17 indexed citations
12.
Moschitti, Alessandro, et al.. (2010). Corpora for Automatically Learning to Map Natural Language Questions into SQL Queries. Language Resources and Evaluation.4 indexed citations
13.
Moschitti, Alessandro. (2010). Kernel Engineering for Fast and Easy Design of Natural Language Applications. Institutional Research Information System (Università degli Studi di Trento). 1–91.2 indexed citations
14.
Mehdad, Yashar, Alessandro Moschitti, & Fabio Massimo Zanzotto. (2009). SemKer: Syntactic/Semantic Kernels for Recognizing Textual Entailment.. Theory and applications of categories.5 indexed citations
15.
Versley, Yannick, Simone Paolo Ponzetto, Massimo Poesio, et al.. (2008). BART: A modular toolkit for coreference resolution. Language Resources and Evaluation.88 indexed citations
16.
Moschitti, Alessandro, Silvia Quarteroni, Roberto Basili, & Suresh Manandhar. (2007). Exploiting Syntactic and Shallow Semantic Kernels for Question Answer Classification. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 776–783.126 indexed citations
17.
Moschitti, Alessandro. (2006). Making Tree Kernels Practical for Natural Language Learning.. Institutional Research Information System (Università degli Studi di Trento). 113–120.203 indexed citations
Harabagiu, Sanda M., Steven J. Maiorano, Alessandro Moschitti, & Cosmin A. Bejan. (2004). Intentions, Implicatures and Processing of Complex Questions. North American Chapter of the Association for Computational Linguistics. 31–42.3 indexed citations
20.
Basili, Roberto, Alessandro Moschitti, & Maria Teresa Pazienza. (2000). Language sensitive text classification. Institutional Research Information System (Università degli Studi di Trento). 331–343.20 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.