scholarly journals Computational generation of slogans

2020 ◽  
pp. 1-33
Author(s):  
Khalid Alnajjar ◽  
Hannu Toivonen
Keyword(s):  
Genetic Algorithms ◽  
Semantic Relatedness ◽  
Language Models ◽  
Target Concept ◽  
Empirical Results ◽  
Linguistic Resources ◽  
Rhetorical Devices ◽  
Novel Method ◽  
Metaphor Interpretation ◽  
Interpretation Model

Abstract In advertising, slogans are used to enhance the recall of the advertised product by consumers and to distinguish it from others in the market. Creating effective slogans is a resource-consuming task for humans. In this paper, we describe a novel method for automatically generating slogans, given a target concept (e.g., car) and an adjectival property to express (e.g., elegant) as input. Additionally, a key component in our approach is a novel method for generating nominal metaphors, using a metaphor interpretation model, to allow generating metaphorical slogans. The method for generating slogans extracts skeletons from existing slogans. It then fills a skeleton in with suitable words by utilizing multiple linguistic resources (such as a repository of grammatical relations, and semantic and language models) and genetic algorithms to optimize multiple objectives such as semantic relatedness, language correctness, and usage of rhetorical devices. We evaluate the metaphor and slogan generation methods by running crowdsourced surveys. On a five-point Likert scale, we ask online judges to evaluate whether the generated metaphors, along with three other metaphors generated using different methods, highlight the intended property. The slogan generation method is evaluated by asking crowdsourced judges to rate generated slogans from five perspectives: (1) how well is the slogan related to the topic, (2) how correct is the language of the slogan, (3) how metaphoric is the slogan, (4) how catchy, attractive, and memorable is it, and (5) how good is the slogan overall. Similarly, we evaluate existing expert-made slogans. Based on the evaluations, we analyze the method and provide insights regarding existing slogans. The empirical results indicate that our metaphor generation method is capable of producing apt metaphors. Regarding the slogan generator, the results suggest that the method has successfully produced at least one effective slogan for every evaluated input.

scholarly journals Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction

2018 ◽  
Vol 6 ◽  
pp. 451-465 ◽  
Author(s):  
Daniela Gerz ◽  
Ivan Vulić ◽  
Edoardo Ponti ◽  
Jason Naradowsky ◽  
Roi Reichart ◽  
...  
Keyword(s):  
Large Scale ◽  
Language Modeling ◽  
Language Models ◽  
Data Sets ◽  
High Type ◽  
Word Level ◽  
Level Information ◽  
Character Sequences ◽  
Novel Method ◽  
Morphologically Rich Languages

Neural architectures are prominent in the construction of language models (LMs). However, word-level prediction is typically agnostic of subword-level information (characters and character sequences) and operates over a closed vocabulary, consisting of a limited word set. Indeed, while subword-aware models boost performance across a variety of NLP tasks, previous work did not evaluate the ability of these models to assist next-word prediction in language modeling tasks. Such subword-level informed models should be particularly effective for morphologically-rich languages (MRLs) that exhibit high type-to-token ratios. In this work, we present a large-scale LM study on 50 typologically diverse languages covering a wide variety of morphological systems, and offer new LM benchmarks to the community, while considering subword-level information. The main technical contribution of our work is a novel method for injecting subword-level information into semantic word vectors, integrated into the neural language modeling training, to facilitate word-level prediction. We conduct experiments in the LM setting where the number of infrequent words is large, and demonstrate strong perplexity gains across our 50 languages, especially for morphologically-rich languages. Our code and data sets are publicly available.

scholarly journals Strategic Team AI Path Plans: Probabilistic Pathfinding

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Tng C. H. John ◽  
Edmond C. Prakash ◽  
Narendra S. Chaudhari
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computer Games ◽  
Fitness Function ◽  
New Method ◽  
High Quality ◽  
Plan Generation ◽  
Novel Method ◽  
Games And Simulations

This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002), in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006). We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

A Novel Approach to Managing the Dynamic Nature of Semantic Relatedness

2020 ◽  
pp. 1085-1114
Author(s):  
Youngseok Choi ◽  
Jungsuk Oh ◽  
Jinsoo Park
Keyword(s):  
Computer Science ◽  
Computational Linguistics ◽  
Critical Role ◽  
Semantic Relatedness ◽  
Semantic Networks ◽  
Dynamic Semantic ◽  
Novel Approach ◽  
Flow Of Time ◽  
Novel Method ◽  
Corpus Data

This research proposes a novel method of measuring the dynamics of semantic relatedness. Research on semantic relatedness has a long history in the fields of computational linguistics, psychology, computer science, as well as information systems. Computing semantic relatedness has played a critical role in various situations, such as data integration and keyword recommendation. Many researchers have tried to propose more sophisticated techniques to measure semantic relatedness. However, little research has considered the change of semantic relatedness with the flow of time and occurrence of events. The authors' proposed method is validated by actual corpus data collected from a particular context over a specific period of time. They test the feasibility of our proposed method by constructing semantic networks by using the corpus collected during a different period of time. The experiment results show that our method can detect and manage the changes in semantic relatedness between concepts. Based on the results, the authors discuss the need for a dynamic semantic relatedness paradigm.

A Novel Approach to Managing the Dynamic Nature of Semantic Relatedness

2016 ◽  
Vol 27 (2) ◽  
pp. 1-26 ◽  
Author(s):  
Youngseok Choi ◽  
Jungsuk Oh ◽  
Jinsoo Park
Keyword(s):  
Computational Linguistics ◽  
Critical Role ◽  
Semantic Relatedness ◽  
Semantic Networks ◽  
Dynamic Nature ◽  
Dynamic Semantic ◽  
Novel Approach ◽  
Flow Of Time ◽  
Novel Method ◽  
Corpus Data

This research proposes a novel method of measuring the dynamics of semantic relatedness. Research on semantic relatedness has a long history in the fields of computational linguistics, psychology, computer science, as well as information systems. Computing semantic relatedness has played a critical role in various situations, such as data integration and keyword recommendation. Many researchers have tried to propose more sophisticated techniques to measure semantic relatedness. However, little research has considered the change of semantic relatedness with the flow of time and occurrence of events. The authors' proposed method is validated by actual corpus data collected from a particular context over a specific period of time. They test the feasibility of our proposed method by constructing semantic networks by using the corpus collected during a different period of time. The experiment results show that our method can detect and manage the changes in semantic relatedness between concepts. Based on the results, the authors discuss the need for a dynamic semantic relatedness paradigm.

scholarly journals A Semantics of the Financial Crisis in Spain

10.29007/w61x ◽  
2018 ◽  
Author(s):  
Keith Stuart ◽  
Ana Botella ◽  
Lucia Gadea-Boronat
Keyword(s):  
Financial Crisis ◽  
Social Services ◽  
Economic Downturn ◽  
Housing Bubble ◽  
Linguistic Features ◽  
Financial Situation ◽  
Linguistic Resources ◽  
Rhetorical Devices ◽  
Growing Body ◽  
Evaluative Meaning

This article presents research carried out on a corpus of newspaper articles about the financial crisis in Spain (Corpus de la Crisis Financiera - CCF). The genesis and compilation of the CCF coincided with a growing body of publications about the financial situation in Spain, a severe economic downturn involving a banking crisis, a burst housing bubble, a dramatic increase in unemployment, and cuts in social services. In this paper, we are going to focus on the semantics and rhetorical functions in the different texts that make up the corpus. Our main objective is to explore the realizations of evaluative meaning in our corpus, either overtly expressed by the journalist or implicitly transmitted in texts by means of rhetorical devices such as metaphors.We will provide examples from our corpus to show how the recurrence and coexistence of such linguistic features play a cohesive role providing texts consistency and texture. These linguistic resources persuade individual readers and even shape collective opinions and ideologies.

scholarly journals A Linguistic Study of Borrowing in Moroccan Teenage Talk

2017 ◽  
Vol 5 (1) ◽  
pp. 162 ◽  
Author(s):  
Samira Elouakili
Keyword(s):  
High School ◽  
Linguistic Study ◽  
Linguistic Resources ◽  
Rhetorical Devices ◽  
Female High School ◽  
Group Interviews ◽  
Novel Words

This paper aims to examine one of the most productive linguistic resources Moroccan teenagers use widely to create novel lexical and phrasal items–borrowing. Of particular interest to us are the varied aspects of their borrowings’ innovativeness, which has often been reported to be one of the main features of youngspeak. The examples are taken from recorded dyadic and triadic conversations mainly between six female high school mates and relaxed group interviews involving four of the latter and two female others from the same school. The results reveal first that Moroccan teenagers are ‘linguistic doers’ capable of creating, through borrowing, novel words and expressions to talk about their concerns, interests, and attitudes. Second, they corroborate findings of previous research that teenagers are highly innovative. To achieve innovativeness, they employ various linguistic and rhetorical devices and break the linguistic norms of both the source and recipient languages. The product is thus a distinct language that is colourful, vivid, and expressive, which scholars largely agree teenagers use to express their autonomy and affiliation to their peers.

scholarly journals A Novel Method for Obtaining the Signature of Household Consumer Pairs

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6030
Author(s):  
Dadiana-Valeria Căiman ◽  
Toma-Leonida Dragomir
Keyword(s):  
Genetic Algorithms ◽  
Case Studies ◽  
Nonlinear Regression ◽  
Power Level ◽  
Electricity Consumption ◽  
The Other ◽  
Total Current ◽  
Novel Method

The management of electricity consumption by household consumers requires multiple ways of consumer monitoring. One of these is the signature i(v) determined by monitoring the consumer voltage-current trajectory. The paper proposes a novel method for obtaining signatures of 2-multiple consumers, i.e., a pair of consumers connected in parallel. Signatures are obtained from samples of the voltage at the consumers’ terminals and of the total current absorbed by the consumers, measured at a frequency of only 20 Hz. Within the method, signatures are calculated using genetic algorithms (GA) and nonlinear regression, according to a procedure developed by the authors in a previous paper. The management of the data selected for the signature assignment represents the novelty. The method proposed in this paper is applied in two case studies, one concerning household consumers within the same power level, the other for household consumers of different power levels. The results confirm the possibility of obtaining signatures of i(v) type.

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