Search

Your search keyword '"Faralli, Stefano"' showing total 376 results
Start Over Author "Faralli, Stefano"

Refine your results

more »

more »

more »

more »
376 results on '"Faralli, Stefano"'

2. Large-scale Taxonomy Induction Using Entity and Word Embeddings

Author

Ristoski, Petar, Faralli, Stefano, Ponzetto, Simone Paolo, and Paulheim, Heiko

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract

Taxonomies are an important ingredient of knowledge organization, and serve as a backbone for more sophisticated knowledge representations in intelligent systems, such as formal ontologies. However, building taxonomies manually is a costly endeavor, and hence, automatic methods for taxonomy induction are a good alternative to build large-scale taxonomies. In this paper, we propose TIEmb, an approach for automatic unsupervised class subsumption axiom extraction from knowledge bases using entity and text embeddings. We apply the approach on the WebIsA database, a database of subsumption relations extracted from the large portion of the World Wide Web, to extract class hierarchies in the Person and Place domain., Comment: Published at IEEE/WIC/ACM International Conference on Web Intelligence 2017 (WI'17)

Published
2021

3. Fourth International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2023)

Author

Boratto, Ludovico, Faralli, Stefano, Marras, Mirko, Stilo, Giovanni, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kamps, Jaap, editor, Goeuriot, Lorraine, editor, Crestani, Fabio, editor, Maistro, Maria, editor, Joho, Hideo, editor, Davis, Brian, editor, Gurrin, Cathal, editor, Kruschwitz, Udo, editor, and Caputo, Annalina, editor

Published
2023
Full Text
View/download PDF

4. ECIR 2020 Workshops: Assessing the Impact of Going Online

Author

Nunes, Sérgio, Little, Suzanne, Bhatia, Sumit, Boratto, Ludovico, Cabanac, Guillaume, Campos, Ricardo, Couto, Francisco M., Faralli, Stefano, Frommholz, Ingo, Jatowt, Adam, Jorge, Alípio, Marras, Mirko, Mayr, Philipp, and Stilo, Giovanni

Subjects
Computer Science - Information Retrieval, Computer Science - Computers and Society
Abstract

ECIR 2020 https://ecir2020.org/ was one of the many conferences affected by the COVID-19 pandemic. The Conference Chairs decided to keep the initially planned dates (April 14-17, 2020) and move to a fully online event. In this report, we describe the experience of organizing the ECIR 2020 Workshops in this scenario from two perspectives: the workshop organizers and the workshop participants. We provide a report on the organizational aspect of these events and the consequences for participants. Covering the scientific dimension of each workshop is outside the scope of this article., Comment: 10 pages, 3 figures, submitted to ACM SIGIR Forum

Published
2020

6. Neural Word Sense Disambiguation to Prune a Large Knowledge Graph of the Italian Cultural Heritage

Author

Faggiani, Erica, Faralli, Stefano, Velardi, Paola, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Chiusano, Silvia, editor, Cerquitelli, Tania, editor, Wrembel, Robert, editor, Nørvåg, Kjetil, editor, Catania, Barbara, editor, Vargas-Solar, Genoveva, editor, and Zumpano, Ester, editor

Published
2022
Full Text
View/download PDF

7. Third International Workshop on Algorithmic Bias in Search and Recommendation (BIAS@ECIR2022)

Author

Boratto, Ludovico, Faralli, Stefano, Marras, Mirko, Stilo, Giovanni, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hagen, Matthias, editor, Verberne, Suzan, editor, Macdonald, Craig, editor, Seifert, Christin, editor, Balog, Krisztian, editor, Nørvåg, Kjetil, editor, and Setty, Vinay, editor

Published
2022
Full Text
View/download PDF

8. Enriching Frame Representations with Distributionally Induced Senses

Author

Faralli, Stefano, Panchenko, Alexander, Biemann, Chris, and Ponzetto, Simone Paolo

Subjects
Computer Science - Computation and Language
Abstract

We introduce a new lexical resource that enriches the Framester knowledge graph, which links Framnet, WordNet, VerbNet and other resources, with semantic features from text corpora. These features are extracted from distributionally induced sense inventories and subsequently linked to the manually-constructed frame representations to boost the performance of frame disambiguation in context. Since Framester is a frame-based knowledge graph, which enables full-fledged OWL querying and reasoning, our resource paves the way for the development of novel, deeper semantic-aware applications that could benefit from the combination of knowledge from text and complex symbolic representations of events and participants. Together with the resource we also provide the software we developed for the evaluation in the task of Word Frame Disambiguation (WFD)., Comment: In Proceedings of the 11th Conference on Language Resources and Evaluation (LREC 2018). Miyazaki, Japan. ELRA

Published
2018

9. A Framework for Enriching Lexical Semantic Resources with Distributional Semantics

Author

Biemann, Chris, Faralli, Stefano, Panchenko, Alexander, and Ponzetto, Simone Paolo

Subjects
Computer Science - Computation and Language
Abstract

We present an approach to combining distributional semantic representations induced from text corpora with manually constructed lexical-semantic networks. While both kinds of semantic resources are available with high lexical coverage, our aligned resource combines the domain specificity and availability of contextual information from distributional models with the conciseness and high quality of manually crafted lexical networks. We start with a distributional representation of induced senses of vocabulary terms, which are accompanied with rich context information given by related lexical items. We then automatically disambiguate such representations to obtain a full-fledged proto-conceptualization, i.e. a typed graph of induced word senses. In a final step, this proto-conceptualization is aligned to a lexical ontology, resulting in a hybrid aligned resource. Moreover, unmapped induced senses are associated with a semantic type in order to connect them to the core resource. Manual evaluations against ground-truth judgments for different stages of our method as well as an extrinsic evaluation on a knowledge-based Word Sense Disambiguation benchmark all indicate the high quality of the new hybrid resource. Additionally, we show the benefits of enriching top-down lexical knowledge resources with bottom-up distributional information from text for addressing high-end knowledge acquisition tasks such as cleaning hypernym graphs and learning taxonomies from scratch., Comment: Accepted for publication in the journal of Natural Language Engineering, 2018

Published
2017

10. Improving Hypernymy Extraction with Distributional Semantic Classes

Author

Panchenko, Alexander, Ustalov, Dmitry, Faralli, Stefano, Ponzetto, Simone P., and Biemann, Chris

Subjects
Computer Science - Computation and Language
Abstract

In this paper, we show how distributionally-induced semantic classes can be helpful for extracting hypernyms. We present methods for inducing sense-aware semantic classes using distributional semantics and using these induced semantic classes for filtering noisy hypernymy relations. Denoising of hypernyms is performed by labeling each semantic class with its hypernyms. On the one hand, this allows us to filter out wrong extractions using the global structure of distributionally similar senses. On the other hand, we infer missing hypernyms via label propagation to cluster terms. We conduct a large-scale crowdsourcing study showing that processing of automatically extracted hypernyms using our approach improves the quality of the hypernymy extraction in terms of both precision and recall. Furthermore, we show the utility of our method in the domain taxonomy induction task, achieving the state-of-the-art results on a SemEval'16 task on taxonomy induction., Comment: In Proceedings of the 11th Conference on Language Resources and Evaluation (LREC 2018). Miyazaki, Japan

Published
2017

11. Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl

Author

Panchenko, Alexander, Ruppert, Eugen, Faralli, Stefano, Ponzetto, Simone Paolo, and Biemann, Chris

Subjects
Computer Science - Computation and Language
Abstract

We present DepCC, the largest-to-date linguistically analyzed corpus in English including 365 million documents, composed of 252 billion tokens and 7.5 billion of named entity occurrences in 14.3 billion sentences from a web-scale crawl of the \textsc{Common Crawl} project. The sentences are processed with a dependency parser and with a named entity tagger and contain provenance information, enabling various applications ranging from training syntax-based word embeddings to open information extraction and question answering. We built an index of all sentences and their linguistic meta-data enabling quick search across the corpus. We demonstrate the utility of this corpus on the verb similarity task by showing that a distributional model trained on our corpus yields better results than models trained on smaller corpora, like Wikipedia. This distributional model outperforms the state of art models of verb similarity trained on smaller corpora on the SimVerb3500 dataset., Comment: In Proceedings of the 11th Conference on Language Resources and Evaluation (LREC'2018). Miyazaki, Japan

Published
2017

12. Unsupervised, Knowledge-Free, and Interpretable Word Sense Disambiguation

Author

Panchenko, Alexander, Marten, Fide, Ruppert, Eugen, Faralli, Stefano, Ustalov, Dmitry, Ponzetto, Simone Paolo, and Biemann, Chris

Subjects
Computer Science - Computation and Language, I.2.6, I.5.3, I.2.4
Abstract

Interpretability of a predictive model is a powerful feature that gains the trust of users in the correctness of the predictions. In word sense disambiguation (WSD), knowledge-based systems tend to be much more interpretable than knowledge-free counterparts as they rely on the wealth of manually-encoded elements representing word senses, such as hypernyms, usage examples, and images. We present a WSD system that bridges the gap between these two so far disconnected groups of methods. Namely, our system, providing access to several state-of-the-art WSD models, aims to be interpretable as a knowledge-based system while it remains completely unsupervised and knowledge-free. The presented tool features a Web interface for all-word disambiguation of texts that makes the sense predictions human readable by providing interpretable word sense inventories, sense representations, and disambiguation results. We provide a public API, enabling seamless integration., Comment: In Proceedings of the the Conference on Empirical Methods on Natural Language Processing (EMNLP 2017). 2017. Copenhagen, Denmark. Association for Computational Linguistics

Published
2017
Full Text
View/download PDF

13. A Novel Pulse Compression Scheme in Coherent OTDR Using Direct Digital Synthesis and Nonlinear Frequency Modulation

Author

Muanenda, Yonas, Faralli, Stefano, Velha, Philippe, Oton, Claudio, Di Pasquale, Fabrizio, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Saponara, Sergio, editor, and De Gloria, Alessandro, editor

Published
2021
Full Text
View/download PDF

14. Second International Workshop on Algorithmic Bias in Search and Recommendation (BIAS@ECIR2021)

Author

Boratto, Ludovico, Faralli, Stefano, Marras, Mirko, Stilo, Giovanni, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hiemstra, Djoerd, editor, Moens, Marie-Francine, editor, Mothe, Josiane, editor, Perego, Raffaele, editor, Potthast, Martin, editor, and Sebastiani, Fabrizio, editor

Published
2021
Full Text
View/download PDF

16. A High-SNR Distributed Acoustic Sensor Based on ϕ-OTDR Using a Scalable Phase Demodulation Scheme Without Phase Unwrapping

Author

Muanenda, Yonas, Faralli, Stefano, Oton, Claudio J., Di Pasquale, Fabrizio, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Saponara, Sergio, editor, and De Gloria, Alessandro, editor

Published
2020
Full Text
View/download PDF

17. International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2020)

Author

Boratto, Ludovico, Marras, Mirko, Faralli, Stefano, Stilo, Giovanni, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jose, Joemon M., editor, Yilmaz, Emine, editor, Magalhães, João, editor, Castells, Pablo, editor, Ferro, Nicola, editor, Silva, Mário J., editor, and Martins, Flávio, editor

Published
2020
Full Text
View/download PDF

21. An FPGA-Based Real-Time Acquisition System for a Distributed Acoustic Sensor Based on Φ-OTDR

Author

Martina, Francesco, Muanenda, Yonas, Faralli, Stefano, Di Pasquale, Fabrizio, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Saponara, Sergio, editor, and De Gloria, Alessandro, editor

Published
2019
Full Text
View/download PDF

22. A Two-Phase Bug Localization Approach Based on Multi-layer Perceptrons and Distributional Features

Author

Distante, Damiano, Faralli, Stefano, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Misra, Sanjay, editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Stankova, Elena, editor, Korkhov, Vladimir, editor, Torre, Carmelo, editor, Rocha, Ana Maria A.C., editor, Taniar, David, editor, Apduhan, Bernady O., editor, and Tarantino, Eufemia, editor

Published
2019
Full Text
View/download PDF

23. Wiki-MID: A Very Large Multi-domain Interests Dataset of Twitter Users with Mappings to Wikipedia

Author

Di Tommaso, Giorgia, Faralli, Stefano, Stilo, Giovanni, Velardi, Paola, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Vrandečić, Denny, editor, Bontcheva, Kalina, editor, Suárez-Figueroa, Mari Carmen, editor, Presutti, Valentina, editor, Celino, Irene, editor, Sabou, Marta, editor, Kaffee, Lucie-Aimée, editor, and Simperl, Elena, editor

Published
2018
Full Text
View/download PDF

24. Distributed Raman optical amplification in phase coherent transfer of optical frequencies

Author

Clivati, Cecilia, Bolognini, Gabriele, Calonico, Davide, Faralli, Stefano, Levi, Filippo, Mura, Alberto, and Poli, Nicola

Subjects
Physics - Optics
Abstract

We describe the application of Raman Optical-fiber Amplification (ROA) for the phase coherent transfer of optical frequencies in an optical fiber link. ROA uses the transmission fiber itself as a gain medium for bi-directional coherent amplification. In a test setup we evaluated the ROA in terms of on-off gain, signal-to-noise ratio, and phase noise added to the carrier. We transferred a laser frequency in a 200 km optical fiber link with an additional 16 dB fixed attenuator (equivalent to 275 km of fiber on a single span), and evaluated both co-propagating and counter-propagating amplification pump schemes, demonstrating nonlinear effects limiting the co-propagating pump configuration. The frequency at the remote end has a fractional frequency instability of 3e-19 over 1000 s with the optical fiber link noise compensation.

Published
2012
Full Text
View/download PDF

30. DWS at the 2016 Open Knowledge Extraction Challenge: A Hearst-Like Pattern-Based Approach to Hypernym Extraction and Class Induction

Author

Faralli, Stefano, Ponzetto, Simone Paolo, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Sack, Harald, editor, Dietze, Stefan, editor, Tordai, Anna, editor, and Lange, Christoph, editor

Published
2016
Full Text
View/download PDF

31. Linked Disambiguated Distributional Semantic Networks

Author

Faralli, Stefano, Panchenko, Alexander, Biemann, Chris, Ponzetto, Simone P., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Groth, Paul, editor, Simperl, Elena, editor, Gray, Alasdair, editor, Sabou, Marta, editor, Krötzsch, Markus, editor, Lecue, Freddy, editor, Flöck, Fabian, editor, and Gil, Yolanda, editor

Published
2016
Full Text
View/download PDF

37. Embedding Fiber Bragg Grating Sensors in Carbon Composite Structures for Accurate Strain Measurement

Author

Gabardi, Massimiliano, Tozzetti, Lorenzo, Faralli, Stefano, Solazzi, Massimiliano, Benedetti, David, Rajbhandari, Samina, Buttaro, Gianni, Pasquale, Fabrizio Di, Gabardi, Massimiliano, Tozzetti, Lorenzo, Faralli, Stefano, Solazzi, Massimiliano, Benedetti, David, Rajbhandari, Samina, Buttaro, Gianni, and Pasquale, Fabrizio Di

Abstract

Fiber Bragg grating (FBG) sensors written by femtosecond laser pulses in polyamide-coated low bending loss optical fibers are successfully embedded in carbon composite structures, following laminating and light resin molding processes which optimize the size of each ply to address esthetic, drapability, and structural requirements of the final components. The sensors are interrogated by a tunable laser operating at around $1.55 ~\mu \text{m}$ , and their response to temperature and strain variations is characterized in a thermally controlled chamber and by bending tests using suspended calibrated loads and a laser scanning system. Experimental results are in good agreement with simulations, confirming that the embedding process effectively overcomes potential issues related to FBG spectral distortion, birefringence, and losses. In particular, the effects of the composite material nonhomogeneity and FBG birefringence are investigated to evaluate their impact on the monitoring capabilities. A bimaterial mechanical beam model is proposed to characterize the orthotropic laminates, pointing out better accuracy in estimating the applied load with respect to the classical homogeneous beam model. A comparative analysis, performed on different instrumented carbon composite samples and supported by theory, points out the repeatability of the FBG sensors’ embedding process and the effectiveness of the technology for real-time accurate strain measurement. Based on such measurements, damages and/or changes in local stiffness can be effectively detected, allowing for structural health monitoring (SHM) of composite structures for applications in specific industrial fields such as automotive and aerospace.

Published
2023

42. The Situation Lens: Looking into Personal Service Composition

Author

Celentano, Augusto, Faralli, Stefano, Pittarello, Fabio, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Song, Il-Yeol, editor, Piattini, Mario, editor, Chen, Yi-Ping Phoebe, editor, Hartmann, Sven, editor, Grandi, Fabio, editor, Trujillo, Juan, editor, Opdahl, Andreas L., editor, Ferri, Fernando, editor, Grifoni, Patrizia, editor, Caschera, Maria Chiara, editor, Rolland, Colette, editor, Woo, Carson, editor, Salinesi, Camille, editor, Zimányi, Esteban, editor, Claramunt, Christophe, editor, Frasincar, Flavius, editor, Houben, Geert-Jan, editor, and Thiran, Philippe, editor

Published
2008
Full Text
View/download PDF

43. Multimedia Annotation of Geo-Referenced Information Sources

Author

Bottoni, Paolo, Cinnirella, Alessandro, Faralli, Stefano, Maurelli, Patrick, Panizzi, Emanuele, Trinchese, Rosa, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Gunsel, Bilge, editor, Jain, Anil K., editor, Tekalp, A. Murat, editor, and Sankur, Bülent, editor

Published
2006
Full Text
View/download PDF

47. DomainSenticNet: An Ontology and a Methodology Enabling Domain-aware Sentic Computing

Author

Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica, AGENCIA ESTATAL DE INVESTIGACION, Distante, Damiano, Faralli, Stefano, Rittinghaus, Steve, Rosso, Paolo, Samsami, Nima, Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica, AGENCIA ESTATAL DE INVESTIGACION, Distante, Damiano, Faralli, Stefano, Rittinghaus, Steve, Rosso, Paolo, and Samsami, Nima

Abstract

[EN] In recent years, SenticNet and OntoSenticNet have represented important developments in the novel interdisciplinary field of research known as sentic computing, enabling the development of a variety of Sentic applications. In this paper, we propose an extension of the OntoSenticNet ontology, named DomainSenticNet, and contribute an unsupervised methodology to support the development of domain-aware Sentic applications. We developed an unsupervised methodology that, for each concept in OntoSenticNet, mines semantically related concepts from WordNet and Probase knowledge bases and computes domain distributional information from the entire collection of Kickstarter domain-specific crowdfunding campaigns. Subsequently, we applied DomainSenticNet to a prototype tool for Kickstarter campaign authoring and success prediction, demonstrating an improvement in the interpretability of sentiment intensities. DomainSenticNet is an extension of the OntoSenticNet ontology that integrates each of the 100,000 concepts included in OntoSenticNet with a set of semantically related concepts and domain distributional information. The defined unsupervised methodology is highly replicable and can be easily adapted to build similar domain-aware resources from different domain corpora and external knowledge bases. Used in combination with OntoSenticNet, DomainSenticNet may favor the development of novel hybrid aspect-based sentiment analysis systems and support further research on sentic computing in domain-aware applications.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results