Do translation universals exist at the syntactic-semantic level? A study using semantic role labeling and textual entailment analysis of English-Chinese translations Humanities and Social Sciences Communications

The wonderful world of semantic and syntactic genre analysis: The function of a Wes Anderson film as a genre 2024

semantics analysis

The idea of transfer learning was widely applied in the field of natural language processing when word2vec was displayed20. Nevertheless, the word vectors obtained by word2vec are static, which is hard to solve polysemy problem. ChatGPT In response to the polysemy problem, ELMo based on bi-directional long short-term memory structure was presented21. Nonetheless, the difficulty of parallel training in ELMo prevents its network depth increasing.

Semantic integration of diverse data in materials science: Assessing Orowan strengthening Scientific Data – Nature.com

Semantic integration of diverse data in materials science: Assessing Orowan strengthening Scientific Data.

Posted: Tue, 30 Apr 2024 07:00:00 GMT [source]

That means that a company with a small set of domain-specific training data can start out with a commercial tool and adapt it for its own needs. Companies can use this more nuanced version of sentiment analysis to detect whether people are getting frustrated or feeling uncomfortable. The Hedonometer also uses a simple positive-negative scale, which is the most common type of sentiment analysis. Adding more preprocessing steps would help us cleave through the noise that words like “say” and “said” are creating, but we’ll press on for now. Let’s do one more pair of visualisations for the 6th latent concept (Figures 12 and 13). Although a REDCap mobile application44 is available to enable offline data collection, more may be needed due to the dependency on smartphones and/or tablets available in research centers, the poor usability, and the non-compatibility of some advanced features45.

A technique to forecast Pakistan’s news using deep hybrid learning model

All factors considered, Uber uses semantic analysis to analyze and address customer support tickets submitted by riders on the Uber platform. The analysis can segregate tickets based on their content, such as map data-related issues, and deliver them to the respective teams to handle. The platform allows Uber to streamline and optimize the map data triggering the ticket. Thus, as and when a new change is introduced on the Uber app, the semantic analysis algorithms start listening to social network feeds to understand whether users are happy about the update or if it needs further refinement.

semantics analysis

Vladimir Putin has certainly not quashed Ukraine’s willingness to fight – or its domestic political unity. In spite of the recent loss of territory, massive destruction of infrastructure, and growing frustration, most Ukrainians trust their president and their army. In the United States, the support package for Kyiv was dramatically delayed in the Congress, causing a shortage of ammunition on the frontline. This allowed Russia to outshell Ukraine, destroy half of the country’s electricity generation capacity, and reconquer territory. Traditional semantic theories involve formal logical representations, truth conditions, and the idea that meaning is grounded in real-world knowledge and experience.

Self-inspired learning for denoising live-cell super-resolution microscopy

Furthermore, we used the package qgraph for the visualization of the network (Epskamp et al., 2012). In the network models, variables are characterized as nodes, and the relations between variables are presented as edges. More specifically speaking, in the network the nodes represent the factors of social support and self-acceptance. The green lines linking different nodes stand for that the relation between the correlated nodes is positive and the red lines indicate the opposite.

Although schizophrenia typically exhibits a high degree of individual variability, resting-state microstates show a relatively high degree of stability. This distribution plot helps us to understand the influence of different quality features on SCZ identification and provides an important reference for further research. Computing temporal parameters for subsequences of different lengths achieves a deeper understanding of the relationship between microstates and SCZ. The introduction of this approach is expected to provide additional insights into microstate analysis and enhance the methodology and theory in the field of SCZ research. This study introduced the concept of microstate semantic features into traditional microstate research and identifies microstate semantic sequences highly correlated with SCZ.

  • Additionally, Table 7 shows each country’s total number of international citations, the average international citations per article, and the top five countries for the most often-cited the corresponding country’s publications.
  • Considering that the research has a practical component in addition to its theoretical development, action research appears to be a good approach.
  • For the remaining 21 participants, we re-referenced their EEG recordings offline from the original central reference to a linked mastoid reference.
  • According to the table, it can be observed that in the combination of template and data consistency, the GEV of SCZ patients reached 88.5%, while the GEV of HC was 85.5%.
  • Their objective was to attempt to predict whether a tweet could be identified as election related based upon the vector representations of words contained in the tweet.
  • During each of the first two rounds, all 60 pairs were presented on the screen in randomized order, with the text written in capital letters.

Additionally, international collaborations among the 13 target countries were also active; China, Hong Kong, and Iran were the top three with which Asian countries often collaborated. For analyzing research impact, the current study separately sampled citing articles from Scopus to secure at least five years’ worth of data to cite the target articles from the time of the data collection, February 2022. To date, for the Social Sciences and Humanities, there is no universally accepted citation window.

Clinical research outcomes depend on the correct definition of the research protocol, the data collection strategy, and the data management plan. Furthermore, researchers often need to work within challenging contexts, as is the case in tuberculosis services, where human and technological resources for research may be scarce. Electronic Data Capture Systems mitigate such risks and enable a reliable environment to conduct health research and promote result dissemination and data reusability. You can foun additiona information about ai customer service and artificial intelligence and NLP. The proposed solution is based on needs pinpointed by researchers, considering the need for an accommodating solution to conduct research in low-resource environments. The REDbox framework was developed to facilitate data collection, management, sharing, and availability in tuberculosis research and improve the user experience through user-friendly, web-based tools.

At least according to CDP, the resolution of phonology generated by inconsistent words occurs later in the reading process than the phonology generated by consistent words. Given this, it means the processing of phonology, at least for words that are consistent, would occur even earlier, and thus may be able to affect semantics early in the ERP time-course. This would be especially the case if the results of Sereno et al. reflected the use of attention to help choose the correct phonological form32 rather than being a more direct measure of phonological processing. In this case, the results on the P2 may represent an effect elicited by attention that occurs after the initial generation of phonology.

The REDbox framework offers valuable tools and a better user experience by integrating the REDCap and KoBoToolbox EDC systems and using semantics. Despite being based on the TB context, the framework can be applied in other contexts with the same demands. Since our method of Granger analysis was based on time-varying autoregressive parameter estimation, we detected changes in connectivity strength over time and frequency. We investigated differences in information flow using the statistical analysis described in Materials and Methods (testing for significant difference in information flow between abstract and concrete trials). Since the entire set of available trials is used to estimate Granger causality per subject and condition, there is no estimate of its variability.

Finally, we aim to study the evolutionary dynamics of different concepts, to figure out whether there are any inherent differences between concepts based on their meaning. This includes also in relation to their semantic classification as well as possible cultural connotations, which may affect their change rate. Comparisons of different scalar formulas were conducted across several tuning parameters.

semantics analysis

The technique is used to divide a network into sub-groups by ensuring internal cohesion within each sub-group and external separations between sub-groups as much as possible (Vacca, 2020). The first sub-group consists of the largest number of countries and most European countries, including the United Kingdom, Germany, Sweden, Spain, and France, belong to this group. This sub-group also includes a few African countries and Southern American countries.

Media bias estimation by media embedding

The most appropriate way to avoid researchers’ subjectivity and to achieve objective and successful meaning patterns is to cluster these lexical items by implementing a hierarchical cluster analysis. Per the next analyses concerning the scope of impact, the characteristics of citing articles that referenced Asian ‘language and linguistics’ research were investigated. Specifically, self-citations and the dispersal of countries that had most often utilized Asian ‘language and linguistics’ research as references were examined. Existing studies (Aksnes, 2003; Costas et al., 2010) suggested several ways to count self-citations, ranging from author-level, coauthor-level, and institution-level to journal-level and to country-level. Table 5 displays the top 20 keywords for every three years; for articles published every three years, the most popular keywords were listed.

semantics analysis

This required additional error handling in the code representing the scoring formulas. After training, the Word2Vec neural network produces vectors for terms but not tweets. For the results of this analysis to be compatible with the other scoring mechanisms, a single scalar value would need to be determined for each tweet. The following formulae were used to derive a scalar score for the tweet from an amalgamation of the component term vectors.

Whether a parental leave reform will encourage fathers to take leave depends not only on its economic implications for families but also on how it is presented and understood, societally. To investigate the media presentation of the parental leave reform in Denmark, we first used sentiment analysis on a corpus of news articles about the leave reform. We tested whether the sentiment expressed in articles differed based on the gender of the journalist and also the political alignment of the newspaper, a variable that can impact a newspaper’s information dynamics19.

semantics analysis

A control (healthy) cell treated with the siRNA vehicle water, imaged by SIM for the comparison of ER phenotypes. Sequential images (43.5 s at 1.5 s per frame) demonstrated rapid reshaping and complex connectivity in a control (healthy) cell sample (Fig. 6a). A representative sample of ATL KO cells imaged by SIM for the comparison of ER phenotypes. Sequential images (43.5 s at 1.5 s per frame) demonstrated compromised reshaping and connectivity defects in an ATL KO cell sample (Fig. 6a).

I’ll explain the conceptual and mathematical intuition and run a basic implementation in Scikit-Learn using the 20 newsgroups dataset. The Form Converter avoids rework in defining variables/fields and designing data collection instruments. The Data Quality module speeds up and enhances data management by reducing the workload of time-consuming ChatGPT App and delicate tasks. Supporting semantic data integration is also another significant contribution of this work. The Ontology Service allows users to add meaning to raw data and monitor the evolution of ontologies through versioning, which is essential to promote the quality and availability of research data over time.

  • This suggests that the weaker results are likely to be in large part due to predictable individual differences in semantic processing caused by task type, as has been found in other priming tasks34.
  • Thus, these puzzling and indiscerptible patterns among the three groups deserve to be addressed by further research, to figure out which topics Asian researchers had worked well with different countries, for instance, based on topic clustering or keyword network-based clustering.
  • Consequently, differences in data expressiveness and spatial correlation are observed in microstate sequences modeled by different microstate templates.
  • Li et al.34 applied general rough set concepts to reveal the association between historical customer needs and design specifications.
  • The same strategy cannot be used to determine that ball beach has low meaningfulness.

It is worth establishing a more complete picture of not only the temporal, spatial and spectral dynamics of brain areas, but also of the nature of the interactions between them. It would therefore be beneficial to conduct a connectivity analysis of high spatio-temporal resolution data, such as that generated by EEG, to understand the dynamic interactions that support language processing37,38. Despite the small N400 effect based on overall mean differences found here, the correlational results point semantics analysis to reliable individual differences between size of the priming effect with consistent and inconsistent words in the related/unrelated prime group. If the data on this component was noisy, it would be hard to see how we could have obtained such results as the noise should have weakened any correlation. This suggests that the weaker results are likely to be in large part due to predictable individual differences in semantic processing caused by task type, as has been found in other priming tasks34.

Detecting Parkinson’s disease and its cognitive phenotypes via automated semantic analyses of action stories – Nature.com

Detecting Parkinson’s disease and its cognitive phenotypes via automated semantic analyses of action stories.

Posted: Fri, 25 Nov 2022 08:00:00 GMT [source]

For example, “死而后已”, a material-transformative-elaboration-intransitive clause, was translated as a material–transformative–extension–transitive process “till the heart beats it lasts”. Theoretically, there should be 30 categories of shifts among different processes, as listed in Table 4, but many types were not present in this study. Instead, the transformations from other process types to the three major types comprised a large proportion, with the change from other types to material process and relational process being the top two, accounting for over 46.25 and 32.5% respectively. Though the mental process is among the main process types, there were not too many processes being shifted into the mental one, making up less than 10%, much lower than the figure for material and relational processes.

semantics analysis

This section focuses on the effect of microstate sequence length on SCZ recognition. For this purpose, the study introduces a sliding window approach, in which the original EEG data is segmented into EEG segments of length T, each with the same label as the original data, by setting a sliding window with window length T and window move 0. The goal of this approach is to systematically explore the effects of different microstate sequence lengths on the SCZ classification task. The optimal window length can be determined to improve the classification performance of SCZ.

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