Character-word Double-dimensional Semantic Classification Model for Judging Illegal and Irregular Behaviors for Internet Food Safety

Author(s):  
Min Zuo ◽  
Si-Yu He ◽  
Qing-Chuan Zhang ◽  
Qing-Bang Wang
Author(s):  
Lauren Fonteyn

AbstractThis study present a corpus-based comparison of two aspectual-sematic classification models proposed in theoretical literature (unidimensional vs. bidimensional) by applying them to a set of nominal and verbal gerunds from the Modern English period. It (i) summarises the differences between unidimensional and bidimensional classification models and (ii) the potential problems associated with them. Despite the difficulties of studying semantic aspect in Present-day as well as historical data, this study will argue that, (iii) at least for deverbal nominalization patterns, it is possible to take a bidimensional approach and maintain a clear distinction between, on the one hand, aspect features of the nominalized situation (stativity/dynamicity, durativity/punctuality, and telicity/atelicity), and temporal boundedness of that situation. The question of which semantic classification model to use, then, is not so much one of which one is practically feasible in a corpus analysis, but rather which one is best suited to describe the attested variation. In order to determine the best model (in terms of parsimony and descriptive accuracy), (iv) the models were compared by means of ‘akaike weights’. To describe the variation between nominal and verbal gerunds in Early and Late Modern English, the bidimensional model outperformed the unidimensional one, showing that (v) the aspectual-semantic distinctions between Modern English nominal and verbal gerunds are a matter of both aspect and temporal boundedness.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Li Xiang ◽  
Li ZongXun

The majority of the traditional methods deal with text matching at the word level which remains uncertain as the text semantic features are ignored. This also leads to the problems of low recall and high space utilization of text matching while the comprehensiveness of matching results is poor. The resultant method, thus, cannot process long text and short text simultaneously. The current study proposes a text matching algorithm for Korean Peninsula language knowledge base based on density clustering. Using the deep multiview semantic document representation model, the semantic vector of the text to be matched is captured for semantic dependency which is utilized to extract the text semantic features. As per the feature extraction outcomes, the text similarity is calculated by subtree matching method, and a semantic classification model based on SWEM and pseudo-twin network is designed for semantic text classification. Finally, the text matching of Korean Peninsula language knowledge base is carried out by applying density clustering algorithm. Experimental results show that the proposed method has high matching recall rate with low space requirements and can effectively match long and short texts concurrently.


2012 ◽  
Vol 82 (3) ◽  
pp. 216-222 ◽  
Author(s):  
Venkatesh Iyengar ◽  
Ibrahim Elmadfa

The food safety security (FSS) concept is perceived as an early warning system for minimizing food safety (FS) breaches, and it functions in conjunction with existing FS measures. Essentially, the function of FS and FSS measures can be visualized in two parts: (i) the FS preventive measures as actions taken at the stem level, and (ii) the FSS interventions as actions taken at the root level, to enhance the impact of the implemented safety steps. In practice, along with FS, FSS also draws its support from (i) legislative directives and regulatory measures for enforcing verifiable, timely, and effective compliance; (ii) measurement systems in place for sustained quality assurance; and (iii) shared responsibility to ensure cohesion among all the stakeholders namely, policy makers, regulators, food producers, processors and distributors, and consumers. However, the functional framework of FSS differs from that of FS by way of: (i) retooling the vulnerable segments of the preventive features of existing FS measures; (ii) fine-tuning response systems to efficiently preempt the FS breaches; (iii) building a long-term nutrient and toxicant surveillance network based on validated measurement systems functioning in real time; (iv) focusing on crisp, clear, and correct communication that resonates among all the stakeholders; and (v) developing inter-disciplinary human resources to meet ever-increasing FS challenges. Important determinants of FSS include: (i) strengthening international dialogue for refining regulatory reforms and addressing emerging risks; (ii) developing innovative and strategic action points for intervention {in addition to Hazard Analysis and Critical Control Points (HACCP) procedures]; and (iii) introducing additional science-based tools such as metrology-based measurement systems.


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