Maintaining regularity and generalization in data using the minimum description length principle and genetic algorithm: case of grammatical inference

In this paper, a genetic algorithm with minimum description length (GAWMDL) is proposed for grammatical inference. The primary challenge of identifying a language of infinite cardinality from a finite set of examples should know when to generalize and specialize the training data. The minimum description length principle that has been incorporated addresses this issue is discussed in this paper. Previously, the e-GRIDS learning model was proposed, which enjoyed the merits of the minimum description length principle, but it is limited to positive examples only. The proposed GAWMDL, which incorporates a traditional genetic algorithm and has a powerful global exploration capability that can exploit an optimum offspring. This is an effective approach to handle a problem which has a large search space such the grammatical inference problem. The computational capability, the genetic algorithm poses is not questionable, but it still suffers from premature convergence mainly arising due to lack of population diversity. The proposed GAWMDL incorporates a bit mask oriented data structure that performs the reproduction operations, creating the mask, then Boolean based procedure is applied to create an offspring in a generative manner. The Boolean based procedure is capable of introducing diversity into the population, hence alleviating premature convergence. The proposed GAWMDL is applied in the context free as well as regular languages of varying complexities. The computational experiments show that the GAWMDL finds an optimal or close-to-optimal grammar. Two fold performance analysis have been performed. First, the GAWMDL has been evaluated against the elite mating pool genetic algorithm which was proposed to introduce diversity and to address premature convergence. GAWMDL is also tested against the improved tabular representation algorithm. In addition, the authors evaluate the performance of the GAWMDL against a genetic algorithm not using the minimum description length principle. Statistical tests demonstrate the superiority of the proposed algorithm. Overall, the proposed GAWMDL algorithm greatly improves the performance in three main aspects: maintains regularity of the data, alleviates premature convergence and is capable in grammatical inference from both positive and negative corpora

Maintaining regularity and generalization in data using the minimum description length principle and genetic algorithm: Case of grammatical inference

In this paper, a genetic algorithm with minimum description length (GAWMDL) is proposed for grammatical inference. The primary challenge of identifying a language of infinite cardinality from a finite set of examples should know when to generalize and specialize the training data. The minimum description length principle that has been incorporated addresses this issue is discussed in this paper. Previously, the e-GRIDS learning model was proposed, which enjoyed the merits of the minimum description length principle, but it is limited to positive examples only. The proposed GAWMDL, which incorporates a traditional genetic algorithm and has a powerful global exploration capability that can exploit an optimum offspring. This is an effective approach to handle a problem which has a large search space such the grammatical inference problem. The computational capability, the genetic algorithm poses is not questionable, but it still suffers from premature convergence mainly arising due to lack of population diversity. The proposed GAWMDL incorporates a bit mask oriented data structure that performs the reproduction operations, creating the mask, then Boolean based procedure is applied to create an offspring in a generative manner. The Boolean based procedure is capable of introducing diversity into the population, hence alleviating premature convergence. The proposed GAWMDL is applied in the context free as well as regular languages of varying complexities. The computational experiments show that the GAWMDL finds an optimal or close-to-optimal grammar. Two fold performance analysis have been performed. First, the GAWMDL has been evaluated against the elite mating pool genetic algorithm which was proposed to introduce diversity and to address premature convergence. GAWMDL is also tested against the improved tabular representation algorithm. In addition, the authors evaluate the performance of the GAWMDL against a genetic algorithm not using the minimum description length principle. Statistical tests demonstrate the superiority of the proposed algorithm. Overall, the proposed GAWMDL algorithm greatly improves the performance in three main aspects: maintains regularity of the data, alleviates premature convergence and is capable in grammatical inference from both positive and negative corpora

Maintaining regularity and generalization in data using the minimum description length principle and genetic algorithm: case of grammatical inference

In this paper, a genetic algorithm with minimum description length (GAWMDL) is proposed for grammatical inference. The primary challenge of identifying a language of infinite cardinality from a finite set of examples should know when to generalize and specialize the training data. The minimum description length principle that has been incorporated addresses this issue is discussed in this paper. Previously, the e-GRIDS learning model was proposed, which enjoyed the merits of the minimum description length principle, but it is limited to positive examples only. The proposed GAWMDL, which incorporates a traditional genetic algorithm and has a powerful global exploration capability that can exploit an optimum offspring. This is an effective approach to handle a problem which has a large search space such the grammatical inference problem. The computational capability, the genetic algorithm poses is not questionable, but it still suffers from premature convergence mainly arising due to lack of population diversity. The proposed GAWMDL incorporates a bit mask oriented data structure that performs the reproduction operations, creating the mask, then Boolean based procedure is applied to create an offspring in a generative manner. The Boolean based procedure is capable of introducing diversity into the population, hence alleviating premature convergence. The proposed GAWMDL is applied in the context free as well as regular languages of varying complexities. The computational experiments show that the GAWMDL finds an optimal or close-to-optimal grammar. Two fold performance analysis have been performed. First, the GAWMDL has been evaluated against the elite mating pool genetic algorithm which was proposed to introduce diversity and to address premature convergence. GAWMDL is also tested against the improved tabular representation algorithm. In addition, the authors evaluate the performance of the GAWMDL against a genetic algorithm not using the minimum description length principle. Statistical tests demonstrate the superiority of the proposed algorithm. Overall, the proposed GAWMDL algorithm greatly improves the performance in three main aspects: maintains regularity of the data, alleviates premature convergence and is capable in grammatical inference from both positive and negative corpora

THE EFFECTIVENESS OF USING JAKARTA POST TO IMPROVE STUDENTS’ READING COMPREHENSION AT THE TENTH GRADE OF THE SECOND SEMESTER OF SMAN 01 ABUNG SEMULI NORTH LAMPUNG IN THE ACADEMIC YEAR OF 2017/2018

One of the most important skills in English is reading. It is often considered as the most difficult skill by the students. This problem was also faced by the students of the tenth grade of SMAN 01 Abung Semuli, North Lampung. Some media were needed by the teacher to overcome that problem. One of the media is Jakarta post article or newspaper. The objective of this research is to know whether the Jakarta post had been effective to teach reading comprehension at the second semester of the tenth grade of SMAN01 Abung Semuli North Lampung in the academic year of 2017/2018 or not. The research methodology was quasi experimental design. In this research, the population was the tenth grade of SMAN 01 Abung Semuli, North Lampung. The sample of this research was two classes consisting of 30 students for experimental class and 30 students for control class. In the experimental class, the researcher used the Jakarta Post or newspaper as a media. The treatments were held in 3 meetings in which 2 x 45 minutes for each class. In collecting the data, the researcher used instrument in the form of multiple choice questions which had been tried out before the pretest. The instrument was given in pre-test and post-test. Before giving the treatment, the researcher gave pre-test for both classes. Then, after conducting the treatments, the instrument was given in post-test. After giving pre-test and post-test, the researcher analyzed the data using SPSS to compute independent sample t-test. From the data analysis computed by using SPSS, it was obtained that Sig. = 0.000 and α = 0.05. It means Ha is accepted because Sig.< α = 0.000 < 0.05. Therefore, there is an effective using Jakarta Post or newspaper to improve students reading comprehension at the tenth grade of SMAN 01 Abung Semuli, North Lampung

Contexts of social action: guest editors' introduction

Cataloged from PDF version of article.In traditional linguistic accounts of context, one thinks of the immediate features of a speech situation, that is, a situation in which an expression is uttered. Thus, features such as time, location, speaker, hearer and preceding discourse are all parts of context. But context is a wider and more transcendental notion than what these accounts imply. For one thing, context is a relational concept relating social actions and their surroundings, relating social actions, relating individual actors and their surroundings, and relating the set of individual actors and their social actions to their surroundings

AI EDAM special issue: advances in implemented shape grammars: solutions and applications

This paper introduces the special issue “Advances in Implemented Shape Grammars: Solutions and Applications” and frames the topic of computer implementations of shape grammars, both with a theoretical and an applied focus. This special issue focuses on the current state of the art regarding computer implementations of shape grammars and brings a discussion about how those systems can evolve in the coming years so that they can be used in real life design scenarios. This paper presents a brief state of the art of shape grammars implementation and an overview of the papers included in the current special issue categorized under technical design, interpreters and interface design, and uses cases. The paper ends with a comprehensive outlook into the future of shape grammars implementations.info:eu-repo/semantics/acceptedVersio

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

Persuading consumers: The use of conditional constructions in British hotel websites

Hotel websites display textual and non-textual strategies with the aim of turning online visitors into customers. This article focuses on two related textual aspects: how consumers are discursively construed and how conditional constructions are used in order to persuade and convince consumers of the adequacy of the hotel. The framework adopted for the analysis combines Stern's notion of 'implied consumer' with a corpus-driven approach. The corpus data comprises 114 British hotel websites and totals half a million words. This is a subcorpus of COMETVAL, a database compiled at the University of València. The results reveal the importance of a number of words that address consumers directly or indirectly. These words intertwine with others to form patterns that help establish a bond between hoteliers and their clients. Further exploration of the corpus confirmed that some conditional sequences such as if you and should you are used by advertisers to speculate about the needs and wishes of consumers that the hotel can fulfil for them. The analysis suggests that conditional structures are a distinctive discursive characteristic strongly associated with the dialogic nature of the discourse hotel websites