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Roma Tre University

Academic institutioneurope · it
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Research library58linked papers
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Selected work

Representative Papers

Keyword Queries over the Deep Web

Nov 14, 2016International Conference on Conceptual Modeling

To address the challenge of keyword search over structured deep web data—particularly restricted tables—that are inherently inaccessible to conventional keyword-based retrieval, this paper proposes a keyword query modeling framework tailored for the deep web. The method comprises three key components: (1) schema-agnostic virtual document generation, which maps invisible database contents into indexable textual representations; (2) cross-table semantic matching integrated with query rewriting to enhance semantic alignment between keywords and underlying data; and (3) joint optimization of result ranking via table structure inference, query expansion, and learning-to-rank techniques. Experiments on real-world deep web datasets demonstrate substantial improvements: NDCG@10 increases by 32% on average over baseline methods, with concurrent gains in both recall and precision. This work establishes the first end-to-end, systematic modeling paradigm for deep web keyword search, advancing the discoverability of deep web data.

6 citations1 influentialRead paper

Preference Queries over Taxonomic Domains

Jun 01, 2021Proceedings of the VLDB Endowment

This paper addresses three key challenges in taxonomy-based multi-preference querying: preference conflicts, granularity mismatch, and non-transitivity. To tackle these, we propose a logic-driven preference optimization retrieval framework. First, we formalize a taxonomy-aware logical preference model grounded in ontological semantics. Second, we introduce two novel preference rewriting operators that enhance specificity while preserving transitivity. Third, we formally prove that only two preference interpretations simultaneously satisfy transitivity and minimal conflict, and based on this result, we design an original heuristic ranking mechanism. Extensive experiments on both synthetic and real-world datasets demonstrate significant improvements in result rationality and user satisfaction. Our approach establishes a verifiable, scalable paradigm for semantic retrieval under complex, heterogeneous preference constraints.

3 citationsRead paper

Trigger Optimization and Event Classification for Dark Matter Searches in the CYGNO Experiment Using Machine Learning

Jan 28, 2026

This work addresses the challenges of efficient real-time triggering, compression, and background suppression in high-resolution sparse optical imaging within the CYGNO experiment. To this end, two novel approaches are proposed: first, an unsupervised online compression framework based on a convolutional autoencoder that extracts regions of interest (ROIs) via reconstruction residuals, achieving fully unsupervised real-time ROI identification for the first time in CYGNO—retaining 93.0% of signal intensity while discarding 97.8% of background pixels with only 25 ms inference latency; second, the application of the weakly supervised Classification Without Labels (CWoLa) method to mixed data, which successfully identifies compact, circular nuclear recoil events and achieves performance approaching the theoretical optimum.

1 citationsRead paper

Finding a Shortest Curve that Separates Few Objects from Many

Apr 04, 2025

This paper addresses the NP-hard problem of computing a shortest closed curve in the plane that separates $k$ required polygons from numerous optional polygons: the curve must enclose all required polygons, avoid their interiors and any obstacles, and minimize the sum of its length and the weighted penalties of included optional polygons. We present the first fixed-parameter tractable (FPT) algorithm with time complexity $O(3^k n^3)$, unifying classical variants—including positive enclosure, negative isolation, and geometric knapsack—under a single framework. Our approach integrates planar embedding theory, computational geometry, dynamic programming, and topological separation analysis, supporting both geometric instances and abstract planar graph representations. Notably, we generalize the problem to optimal closed walks on weighted planar graphs, establishing the first FPT solution for this setting. The method bridges deep theoretical insights with practical algorithmic design, offering both rigorous guarantees and implementable efficiency.

1 citationsRead paper
Recent publications

Latest Papers

Theatre Chapbooks At Scale: A Statistical Comparative Analysis of Typography

Jul 29, 2026

This study addresses the inefficiency of manual methods in large-scale typographic comparison of 17th-century Spanish playbills by proposing a character prototype–based statistical framework. The approach automatically extracts, clusters, and aligns character images to compute inter-book font distances and introduces, for the first time, an a contrario significance test to assess the reliability of observed typographic differences, enabling robust automated comparison of both roman and italic typefaces. By overcoming the scalability limitations of traditional analyses, the method—validated by domain experts—successfully uncovers new printer attributions and revises existing conclusions, thereby advancing digital bibliographical scholarship toward large-scale, automated investigation.

0 citationsRead paper

Extending Biconnected Straight-Line Planar Drawings

Jul 28, 2026

This study addresses the Partial Drawing Extensibility (PDE) problem for planar graphs when the initial partial drawing is biconnected. By leveraging graph embedding analysis, complexity reductions, and the Existential Theory of the Reals (ETR), the authors establish for the first time that PDE remains NP-hard even when the given subgraph is biconnected and the input graph is subcubic. On the algorithmic side, they devise a polynomial-time algorithm running in $O(p^2 n)$ time under a fixed embedding and develop a fixed-parameter tractable (FPT) algorithm parameterized by the vertex cover number. This work delineates the computational complexity landscape of PDE in the biconnected setting and achieves efficient solutions under fixed embeddings and path-extension constraints.

0 citationsRead paper

Beyond Degree Four: Near-Orthogonal Planar Drawings

Jul 23, 2026

This study addresses the near-orthogonal polyline drawing problem for planar graphs with maximum degree exceeding four, where “near-orthogonality” is measured by the number of non-orthogonal faces. It establishes, for the first time, that this problem is NP-complete even on three-connected planar graphs, thereby overcoming the degree limitations inherent in traditional orthogonal graph drawing. Methodologically, the work integrates parameterized complexity theory, treewidth decomposition, and an outerplanarity index to develop an efficient algorithmic framework. Under a fixed embedding, the authors present a linear-time fixed-parameter tractable (FPT) algorithm parameterized by the outerplanarity index, the number of non-orthogonal faces, and treewidth, along with a polynomial-time approximation scheme (PTAS). For variable embeddings, they devise a treewidth-based FPT algorithm tailored to biconnected graphs.

0 citationsRead paper