Search results for "dated"
showing 10 items of 70 documents
(Table 2) Age determination of sediment core NIOP-C2_929
2007
In this study we present a sea surface temperature (SST) record from the western Arabian Sea for the last 20,000 years. We produced centennial-scale d18O and Mg/Ca SST time series of core NIOP929 with focus on the glacial-interglacial transition. The western Arabian Sea is influenced by the seasonal NE and SW monsoon wind systems. Lowest SSTs occur during the SW monsoon season because of upwelling of cold water, and highest SSTs can be found in the low-productivity intermonsoon season. The Mg/Ca-based temperature record reflects the integrated SST of the SW and NE monsoon seasons. The results show a glacial-interglacial SST difference of ~2°C, which is corroborated by findings from other Ar…
Una nuova popolazione isolata di xenopo liscio in Sicilia sud-occidentale
2017
African clawed frog is a sub-saharan native anuran that has been introduced in various states of the old and the new world. The only Italian population of this species is located in western Sicily, and it is known as the European clawed frog population with wider distribution area. This paper describes a new Sicilian population of this species, and sets out to verify the effective isolation from the currently known distribution. The new site is a disused swimming pool, located near the mouth of the Belice River (province of Trapani), 31 km away from the nearest edge of the African clawed frog distribution area. To test whether this new population is the result of natural expansion of its ra…
Statistically Validated Networks for assessing topic quality in LDA models
2022
Probabilistic 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; Alet…
Statistically Validated Networks for evaluating coherence in topic models
2022
Probabilistic topic models have become one of the most widespread machine learning technique for textual analysis purpose. In this framework, Latent Dirichlet Allocation (LDA) 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 over words characterizes each topic. Unfortunately, topic models do not guarantee the interpretability of their outputs. The topics learned from the model may be characterized by a set of irrelevant or unchained words, being useless for the interpretation. In the framework of topic quality evaluation, the pairwise semantic cohesion among the top-N most pr…
MEASURING TOPIC COHERENCE THROUGH STATISTICALLY VALIDATED NETWORKS
2020
Topic 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 …
STRANIERI, MERIDIONALI O PROVINCIALI? I CONSUMI NEL TEMPO LIBERO DELLE SECONDE GENERAZIONI
2022
In this paper, we analyze consumption patterns of leisure time among young people belonging to the so-called “second generation” of immigrants in Italy. Leisure time consumption describes how young immigrants use cultural products and services. We analyze data collected by the ISTAT through the survey on the “second generations” (2015). A comparison of leisure consumption patterns between second-generation immigrants and their Italian peers does not show significant differences. Rather, differences in consumption styles are associated to gender (male/female), geographic area of residence (North/South), and size of the municipality (large municipality/small municipality) of residence.
Percepciones del alumnado de Educación Secundaria (15-17 años) hacia la función social de la ciencia
2020
En esta investigación se estudian las percepciones del alumnado de Educación Secundaria (15-17 años), en función de su género y nivel educativos (educación obligatoria y postobligatoria), hacia tres aspectos relacionados con la función social de la ciencia. Los 158 participantes cumplimentaron un cuestionario validado internacionalmente, que nos ha permitido alcanzar datos diagnósticos respecto a estos factores que indica un mayor reconocimiento sobre la importancia del papel de la Ciencia en la sociedad, frente a los restantes, que decrecen en el siguiente orden: adopción de actitudes científicas e interés respecto a ella en el tiempo de ocio, respectivamente. Finalmente se aportan implica…
Consolidated challenge to social demand for resilient platforms : Lessons from Uber's global expansion
2017
Many in the industry see the ride-sharing company Uber as the significant advancement through information and communication technology (ICT) particularly of the digital service platform and sharing economy. Uber has been exploring the new frontier of the ICT-driven disruptive business model (IDBM) and succeeded in its global expansion to over 479 cities in more than 75 countries worldwide in June of 2016. Such rapid expansion provides constructive insights regarding the significance of IDBM, not only in transportation but also in almost all other business fields. While at the same time Uber's legal battles in some cities around the world raise a serious question regarding the rationale of I…
Exploring topics in LDA models through Statistically Validated Networks: directed and undirected approaches
2022
Probabilistic topic models are machine learning tools for processing and understanding large text document collections. Among the different models in the literature, Latent Dirichlet Allocation (LDA) has turned out to be the benchmark of the topic modelling community. The key idea is to represent text documents as random mixtures over latent semantic structures called topics. Each topic follows a multinomial distribution over the vocabulary words. In order to understand the result of a topic model, researchers usually select the top-n (essential words) words with the highest probability given a topic and look for meaningful and interpretable semantic themes. This work proposes a new method …
Ranking coherence in topic models using statistically validated networks
2023
Probabilistic topic models have become one of the most widespread machine learning techniques in textual analysis. Topic discovering is an unsupervised process that does not guarantee the interpretability of its output. Hence, the automatic evaluation of topic coherence has attracted the interest of many researchers over the last decade, and it is an open research area. This article offers a new quality evaluation method based on statistically validated networks (SVNs). The proposed probabilistic approach consists of representing each topic as a weighted network of its most probable words. The presence of a link between each pair of words is assessed by statistically validating their co-oc…