scholarly journals S4 enriched multimodal categorial grammars are context-free

2007 ◽  
Vol 388 (1-3) ◽  
pp. 173-180 ◽  
Author(s):  
Andrew R. Plummer
Keyword(s):  
Categorial Grammars ◽  
Context Free

scholarly journals S4 enriched multimodal categorial grammars are context-free: Corrigendum

2008 ◽  
Vol 403 (2-3) ◽  
pp. 406-408 ◽  
Author(s):  
Andrew R. Plummer
Keyword(s):  
Categorial Grammars ◽  
Context Free

scholarly journals Parsing Linear Context-Free Rewriting Systems with Fast Matrix Multiplication

2016 ◽  
Vol 42 (3) ◽  
pp. 421-455
Author(s):  
Shay B. Cohen ◽  
Daniel Gildea
Keyword(s):  
Matrix Multiplication ◽  
Recognition Algorithm ◽  
Running Time ◽  
Context Sensitive ◽  
Rewriting Systems ◽  
Categorial Grammars ◽  
Grammar Rules ◽  
Tree Adjoining Grammars ◽  
Asymptotic Complexity ◽  
Context Free

We describe a recognition algorithm for a subset of binary linear context-free rewriting systems (LCFRS) with running time O(nωd) where M(m) = O(mω) is the running time for m × m matrix multiplication and d is the “contact rank” of the LCFRS—the maximal number of combination and non-combination points that appear in the grammar rules. We also show that this algorithm can be used as a subroutine to obtain a recognition algorithm for general binary LCFRS with running time O(nωd+1). The currently best known ω is smaller than 2.38. Our result provides another proof for the best known result for parsing mildly context-sensitive formalisms such as combinatory categorial grammars, head grammars, linear indexed grammars, and tree-adjoining grammars, which can be parsed in time O(n4.76). It also shows that inversion transduction grammars can be parsed in time O(n5.76). In addition, binary LCFRS subsumes many other formalisms and types of grammars, for some of which we also improve the asymptotic complexity of parsing.

Framework for rare event detection using Artificial Neural Network based context free grammar

2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Event Detection ◽  
Performance Metrics ◽  
Rare Events ◽  
Rare Event ◽  
Video Stream ◽  
Context Free Grammar ◽  
Artificial Neural ◽  
Context Free

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.

Saussurelaisen kielikäsityksen kritiikki

Virittäjä ◽  
2020 ◽  
Vol 124 (1) ◽  
Author(s):  
Mikko Laasanen
Keyword(s):  
Communication System ◽  
Written Language ◽  
Strong Form ◽  
Continuous Speech ◽  
Language Bias ◽  
Context Free ◽  
Ontological Concept

Artikkeli käsittelee saussurelaista kielikäsitystä kohtaan esitettyä kritiikkiä. Artikkelin tavoitteena on puolustaa saussurelaista kielikäsitystä ja esittää Saussure moni-puolisempana ajattelijana kuin mitä Kurssin vahvasti strukturalisesta luennasta voisi päätellä. Artikkelissa tarkastellaan käsitystä kielestä järjestelmänä (Saussuren langue), kontekstivapaata merkitystä, kirjoitetun kielen vääristymää (written language bias), Roy Harrisin kielimyyttiä sekä kielen dynaamisuutta. Artikkelissa esitetään, että langue on sekä metodologinen että ontologinen käsite, joka viittaa sekä kielen järjestäytymättömiin sääntöihin että kielitieteilijän niistä luomaan järjestelmään. Kontekstivapaan merkityksen osalta korostetaan sitä, että jonkinlainen merkityksen pysyvyys on välttämätön osa kieltä kommunikaatiojärjestelmänä. Artikkelissa argumentoidaan kirjoitetun kielen vääristymän vahvaa muotoa vastaan, jonka mukaan esimerkiksi puheen analysoiminen diskreeteiksi yksiköiksi johtuu kirjoitetun kielen vaikutuksesta. Harrisin kielimyytin osalta esitetään, että kyse ei ole Saussuren näkemyksistä vaan Harrisin tulkinnoista. Artikkelissa esitetään myös, että dynaamisuus ei ole yhteensopimaton käsite saussurelaisen kielikäsityksen kanssa.   On the critique of the Saussurean concept of language: some perspectives and counter-arguments The article deals with the critique of the Saussurean concept of language. The purpose of the article is to defend the Saussurean concept of language and to present Saussure as a more versatile thinker than may be assumed from a purely structuralist reading of Course. The article discusses the concept of language as a system (Saussure’s langue), the notion of context-free meaning, the so-called written-language bias, Roy Harris’ language myth, and the notion of dynamicity in language in relation to the Saussurean concept of language. The article begins by arguing that langue is both a methodological and an ontological concept that refers both to the unorganised rules of language and to the system of language rules as organised by the linguist. Second, the author asserts that some kind of permanence of meaning is essential to the concept of language as a communication system. Third, an argument is presented against the strong form of written-language bias, according to which, for instance, the analysis and reduction of continuous speech into discrete units is based on the model of written language. Fourth, the author posits that the language myth, developed by Harris, is not based on Saussure’s views but on Harris’ interpretation of Saussure’s views. The article ends with the contention that the notion of dynamicity is not incompatible with the Saussurean concept of language.

PrePrint - Exploring Perceptions of Meaningful Relationships

2018 ◽  
Author(s):  
Nataly Beribisky ◽  
Heather Davidson ◽  
Rob Cribbie
Keyword(s):  
Effect Size ◽  
Mean Difference ◽  
Practical Significance ◽  
Equivalence Testing ◽  
Significant Variability ◽  
Meaningful Relationship ◽  
Meaningful Relationships ◽  
Context Free

Researchers often need to consider the practical significance of a relationship. For example, interpreting the magnitude of an effect size or establishing bounds in equivalence testing requires knowledge of the meaningfulness of a relationship. However, there has been little research exploring the degree of relationship among variables (e.g., correlation, mean difference) necessary for an association to be interpreted as meaningful or practically significant. In this study, we presented statistically trained and untrained participants with a collection of figures that displayed varying degrees of mean difference between groups or correlations among variables and participants indicated whether or not each relationship was meaningful. The results suggest that statistically trained and untrained participants differ in their qualification of a meaningful relationship, and that there is significant variability in how large a relationship must be before it is labeled meaningful. The results also shed some light on what degree of relationship is considered meaningful by individuals in a context-free setting.

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