1,472 research outputs found
Anna Simonetti Agostinetti, Flavio Arriano. Gli eventi dopo Alessandro
No full textStraus Jean A. Anna Simonetti Agostinetti, Flavio Arriano. Gli eventi dopo Alessandro. In: L'antiquité classique, Tome 64, 1995. pp. 303-304
Statistically Validated Network approach for document clustering and topic modeling
No full textIn machine learning, document clustering and topic modeling are scientific challenges
concerning the extraction of useful information from a collection of texts. Traditional
approaches, such as Latent Dirichlet Allocation (LDA), rely on maximising likeli-
hood functions. In this paper, we explore a paradigm shift towards network represen-
tation of textual data and the associated challenges of community detection [3]. We
proposes a new method to face the tasks of document clustering and topic modeling,
representing a collection of documents as a bipartite network. Then, we introduce the
application of Statistically Validated Networks (SVN) to filter out irrelevant con-
nections within the projected networks of words and documents. The SVN method is
promising in the framework of topic modeling. For instance, Simonetti et al. (2022) recently proposed a new application of SVN to measure the coherence of topics. In-
stead, we aim to identify the topics themselves. By doing so, we can naturally find topics
with high coherence according to the measure proposed by the authors. Moreover, the
modularity contribution of each community (topic) can be interpreted as a measure of
coherence since it is an intensive quantity that assesses the tendency of words within a
given topic to occur in the same sentences jointl
Statistically Validated Networks for assessing topic quality in LDA models
No full textProbabilistic topic models have become one of the most widespread machine learning technique for textual analysis purpose. In this framework, Latent Dirichlet Allocation (LDA) (Blei et al., 2003) gained more and more popularity as a text modelling technique. The idea is that documents are represented as random mixtures over latent topics, where a distribution overwords characterizes each topic. Unfortunately, topic models do not guarantee the interpretability of their outputs. The topics learned from the model may be only characterized by a set of irrelevant or unchained words, being useless for the interpretation. Although many topic-quality metrics were proposed (Newman et al., 2009; Aletras and Stevenson,2013; Roder et al., 2015; Nikolenko et al., 2017), the automatic evaluation of the coherence of topics remains an open research area. The main contributions of this paper are: i) to define a coherence measure (SVN-Coherence) based on a rigorous statistical model that approximates human ratings better than state-of-the-art methods, and ii) to filter out marginal associations of words and facilitate the graphical representation and interpretation of the obtained topics through Statically Validated Networks (SVN) (Tumminello et al., 2011). Specifically, the method builds a co-occurrence network for each topic whose most probable words are the nodes. We set a link between two nodes (words) in each network if their co-occurrences are statistically significant. The Hypergeometric distribution describes the probability mass function under the null hypothesis and it models the probability of co-occurrence between words conditionally to their marginals. Indeed, it allows taking into account the heterogeneity of the vocabulary on a collection of texts. Finally, we derive a global measure of coherence for each topic by considering the number of statistically validated links, the strength of the association between word pairs, and the relative relevance of each word in the topic. We claim that these links carry relevant information about the structure of topics, i.e., the more connected the network, the more semantically coherent the corresponding topic. The new measure provides a coherence-based ranking that distinguishes between high-quality and low-quality topics. We designed a survey to obtain human judgment, which we use as ground truth, to compare our method with the state-of-art coherence measures. Specifically, we asked 222 PhD students to evaluate the coherence of 32 topics (extracted from the New York Times articles dataset) on a 4-point scale. The results show that the proposed SVN-Coherence substantially outperforms all the state-of-art coherence metrics
Lo stile Ikea. Su Moccia e gli altri
No full textUn'analisi formale dei romanzi di alcuni scrittori italiani di consumo (Federico Moccia, Alessandro D'Avenia
MEASURING TOPIC COHERENCE THROUGH STATISTICALLY VALIDATED NETWORKS
No full textTopic models arise from the need of understanding and exploring large text
document collections and predicting their underlying structure. Latent Dirichlet
Allocation (LDA) (Blei et al., 2003) has quickly become one of the most popular
text modelling techniques. The idea is that documents are represented as random
mixtures over latent topics, where a distribution over words characterizes each topic.
Unfortunately, topic models give no guaranty on the interpretability of their outputs.
The topics learned from texts may be characterized by a set of irrelevant or
unchained words. Therefore, topic models require validation of the coherence of
estimated topics. However, the automatic evaluation of the latent space of a topic
model is a difficult task. Formerly, the most used metric for evaluating the quality of
a topic model was the held-out likelihood. Still, the literature has shown that this
method emphasizes complexity rather than interpretability. Although many
procedures were recently proposed (Röder et al., 2015), the automatic evaluation of
topic coherence remains an open research area. Our work aims to provide a new
technique based on Statistically Validated Network (Tumminello et al., 2011). Our
approach consists in representing each topic as a network of its most probable
words. The presence of a link between each pair of words is assessed by statistically
validating their co-occurrences in sentences against the null hypothesis of random
co-occurrence. Thus, we propose a new coherence measure based on the structure of
the statistically validated network. Furthermore, the new measure provides a ranking
of topics and distinguishes high-quality from low-quality topics. The intuition is that
the pairwise associations of words is strictly related to the semantic coherence and
interpretability of a topic
Alfonso Simonetti: "Mio figlio scontento" (1887)
No full textScheda storico-critica sul dipinto inedito "Mio figlio scontento" (1887) del pittore Alfonso Simonetti ( (Napoli, 1848 - Castrocielo/Frosinone, 1892), che ebbe alla metà dell'Ottocento la propria formazione tra Napoli e Firenze, aprendosi alle moderne istanze del verismo
Corrigendum to “An approach based on semantic stream reasoning to support decision processes in smart cities” [Telemat. Informat. 35 (1) (2018) 68–81](S0736585317304768)(10.1016/j.tele.2017.09.019)
No full textThe authors regret that, in the work “An approach based on semantic stream reasoning to support decision processes in smart cities”, Telematics and Informatics (https://doi.org/10.1016/j.tele.2017.09.019), the name of the fourth author Antonio Simonetti has not been reported in the string of authors but erroneously only in acknowledgements. Thus, the correct string of authors and their affiliations are shown above. The authors would like to apologise for any inconvenience caused
La critica italiana e le culture del progetto (1945-1960): strumenti, temi, attori
No full textIl seminario - a cura di Andrea Borsari, Elena Formia, Giovanni Leoni con Matteo Cassani Simonetti e Matteo Sintini – conclude un’attività condotta con gli studenti del Dottorato di Ricerca in Architettura e dedicata a proporre una riflessione sugli strumenti e le figure della critica elaborati dalla cultura italiana del progetto tra il 1945 e il 1960. L'attività è stata svolta nell'ambito della ricerca Mapping.Crit.Arch.: Architectural criticism XXth and XXIth centuries, a cartography finanziata dall'Agence Nationale de la Recherche (Francia) e in vista del Second International Workshop a Bologna (4-5 ottobre 2016), alla cui organizzazione il Dottorato in Architettura contribuisce (mac.hypotheses.org). Mostra e presentazione finale dei lavori degli studenti del Dottorato di Ricerca in Architettura dedicati all’analisi di progetti editoriali italiani inerenti la critica del design e dell’architettura (in collaborazione con Daniele Baratta, Ugo Cornia, Giulia Favaretto, Riccardo Foschi, Elisabetta Caterina Giovannini, Gioia Laura Iannilli, Stefano Politi, Davide Prati, Angela Santangelo, Alessandro Tognon)
A sample-and-hold circuit with very low gain error for time interleaving applications
No full textA high-performance sample-and-hold (S/H) front end is proposed. In the double-buffered S/H circuit, the standard voltage follower based on a high-gain two-stage opamp is replaced with a couple of low gain amplifiers in feedback mode. Simulation results show that the proposed active-feedback voltage follower allows a very low gain error with low sensitivity to circuit mismatches and a limited distortion penalty. This makes it suitable to be used in time interleaving applications with distributed sampling
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