Search results for: whole word method

Authors: Yidan Shao

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With the advancement of the economy, technology promotes online teaching, and learning has become one of the common features in the educational field. Meanwhile, the dramatic expansion of the online environment provides opportunities for more learners, including second language learners. A greater command of vocabulary improves students’ learning capacity, and word acquisition and development play a critical role in learning. Furthermore, the Word Wall is an effective tool to improve students’ knowledge of words, which works for a wide range of age groups. Therefore, this study is going to use the Word Wall as an intervention to examine whether it can bring some memorization changes in an online English language class for a second language learner based on the word morphology method. The participant will take ten courses in the experiment as it plans. The findings show that the Word Wall activity plays a slight role in improving word memorizing, but it does affect instant memorization. If longer periods and more comprehensive designs of research can be applied, it is expected to have more value.

Keywords: second language acquisition, word morphology, word memorization, the Word Wall

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Authors: Elnaz Dabiri, Somayeh Hamidnezhad

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Background and Objective: This study aims at investigating the effect of whole word method on Mean Length of Utterance (MLU) of 3 to 6 years old children with cochlear implants having normal IQ. Materials and Methods: In this quasi-experimental and interventional study, 20 children with cochlear implants, aged between 3and 6 years, and normal IQ were selected from Tabriz cochlear implants center using convenience sampling. Afterward, they were randomly bifurcated. The first group was educated by whole-word reading method along with traditional methods and the second group by traditional methods. Both groups had three sessions of 45-minutes each, every week continuously for a period of 3 months. Pre-test and post-test language abilities of both groups were assessed using the TOLD test. Results: Both groups before training have the same age, IQ, and MLU, but after training the first group shows a considerable improvement in MLU in comparison with the second group. Conclusions: Reading training by the whole word method have more effect on MLU of children with cochlear implants in comparison of the traditional method.

Keywords: cochlear implants, reading training, traditional methods, language therapy, whole word method, Mean Length of Utterance (MLU)

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Authors: Fatima Naz, Ayesha Tariq

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In view of growing of the internet users for e-commerce and taking into account, the emergent impact of word of mouth phenomenon this research has different aims. The aims of this study were built following dissimilar discussion with teachers and colleagues enlightening that word of mouth information for online purchasing do not have the same effect for everybody. Then they were born following dissimilar researchers together with what was already done in previous researches and what was completed. As a result different aims were drawn; the initial aim of this research is to study the attention of the customers in the word of mouth to power their online purchasing activities. The next aim is to analyze the people influenced by the interest of word of mouth. The following aim is to examine the marketing behavior bearing in mind the internet progress and word of mouth, their consideration for word of mouth marketing. In the form of research questions the aims of the study are: 1) How community utilizes and multiplies word of mouth information about online purchasing experience? 2) How communities perceive the word of mouth marketing? 3) How marketers take the word of mouth phenomenon and how they handle it?

Keywords: belief, power, inspiration, self-expression, positive attitude to online marketing, forwarding of contents, purchasing decision, standard marketing

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Authors: Mohamed Ali Al Shaari, Khalid M. El Fitori

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In the field of Quran Studies known as Ghareeb A Quran (the study of the meanings of strange words and structures in Holy Quran), it is difficult to distinguish some pragmatic meanings from conceptual meanings. One who wants to study this subject may need to look for a common usage between any two words or more; to understand general meaning, and sometimes may need to look for common differences between them, even if there are synonyms (word sisters). Some of the distinguished scholars of Arabic linguistics believe that there are no synonym words, they believe in varieties of meaning and multi-context usage. Based on this viewpoint, our method was designed to look for synonyms of a word, then the differences that distinct the word and their synonyms. There are many available books that use such a method e.g. synonyms books, dictionaries, glossaries, and some books on the interpretations of strange vocabulary of the Holy Quran, but it is difficult to look up words in these written works. For that reason, we proposed a logical entity, which we called Differences Matrix (DM). DM groups the synonyms words to extract the relations between them and to know the general meaning, which defines the skeleton of all word synonyms; this meaning is expressed by a word of its sisters. In Differences Matrix, we used the sisters(words) as titles for rows and columns, and in the obtained cells we tried to define the row title (word) by using column title (her sister), so the relations between sisters appear, the expected result is well defined groups of sisters for each word. We represented the obtained results formally, and used the defined groups as a base for building the ontology of the Holy Quran synonyms.

Keywords: Quran, synonyms, differences matrix, ontology

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Authors: Sandra Rizkallah, Amir F. Atiya

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This work presents a novel word to vector representation that is based on embedding the words into a sphere, whereby the dot product of the corresponding vectors represents the similarity between any two words. Embedding the vectors into a sphere enabled us to take into consideration the antonymity between words, not only the synonymity, because of the suitability to handle the polarity nature of words. For example, a word and its antonym can be represented as a vector and its negative. Moreover, we have managed to extract an adequate vocabulary. The obtained results show that the proposed approach can capture the essence of the language, and can be generalized to estimate a correct similarity of any new pair of words.

Keywords: natural language processing, word to vector, text similarity, text mining

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Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

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In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: word sense disambiguation (wsd), contextual sense model (csm), most frequent sense (mfs), part of speech (pos), natural language processing (nlp), oov (out of vocabulary), lemma_pos (a token where lemma and pos of word are joined by underscore), information retrieval (ir), machine translation (mt)

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Authors: Po-Chun Lee, Li-Lin Liang, Ching-Yuan Huang

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Purpose: Research on electronic word-of-mouth (eWOM)& online review has been widely used in service industry management research in recent years. The SERVQUAL scale is the most commonly used method to measure service quality. Therefore, the purpose of this research is to combine electronic word of mouth & online review with the SERVQUAL scale. To explore the comparative study of positive and negative electronic word-of-mouth reviews of a certain armed force general hospital in Taiwan. Data sources: This research obtained online word-of-mouth comment data on google maps from a military hospital in Taiwan in the past ten years through Internet data mining technology. Research methods: This study uses the semantic content analysis method to classify word-of-mouth reviews according to the revised PZB SERVQUAL scale. Then carry out statistical analysis. Results of data synthesis: The results of this study disclosed that the negative reviews of this military hospital in Taiwan have been increasing year by year. Under the COVID-19 epidemic, positive word-of-mouth has a downward trend. Among the five determiners of SERVQUAL of PZB, positive word-of-mouth reviews performed best in “Assurance,” with a positive review rate of 58.89%, Followed by 43.33% of “Responsiveness.” In negative word-of-mouth reviews, “Assurance” performed the worst, with a positive rate of 70.99%, followed by responsive 29.01%. Conclusions: The important conclusions of this study disclosed that the total number of electronic word-of-mouth reviews of the military hospital has revealed positive growth in recent years, and the positive word-of-mouth growth has revealed negative growth after the epidemic of COVID-19, while the negative word-of-mouth has grown substantially. Regardless of the positive and negative comments, what patients care most about is “Assurance” of the professional attitude and skills of the medical staff, which needs to be strengthened most urgently. In addition, good “Reliability” will help build positive word-of-mouth. However, poor “Responsiveness” can easily lead to the spread of negative word-of-mouth. This study suggests that the hospital should focus on these few service-oriented quality management and audits.

Keywords: quality of medical service, electronic word-of-mouth, armed forces general hospital

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Authors: Kevin Chan, Kevin K. H. Chung, Patcy P. S. Yeung, H. L. Ip, Bill T. C. Chung, Karen M. K. Chung

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Purpose: Recent evidence shows that reading self-efficacy and students perceived difficulty in reading are significantly associated with word reading and reading fluency. However, little is known about these relationships among students learning to read English as a second language, particularly in Chinese students. This study examined the contributions of reading self-efficacy, perception of difficulty in reading, and cognitive-linguistic skills to performance on English word reading and reading fluency in Chinese students. Method: A sample of 122 second-and third-grade students in Hong Kong, China, participated in this study. Students completed the measures of reading self-efficacy and perception of difficulty in reading. They were assessed on their English cognitive-linguistic and reading skills: rapid automatized naming, nonword reading, phonological awareness, word reading, and one-minute word reading. Results: Results of path analysis indicated that when students’ grades were controlled, reading self-efficacy was a significant correlate of word reading and reading fluency, whereas perception of difficulty in reading negatively predicted word reading. Conclusion: These findings underscore the importance of taking students’ reading self-efficacy and perception of difficulty in reading and their cognitive-linguistic skills into consideration when designing reading intervention and instructions for students learning English as a second language.

Keywords: self-efficacy, perception of difficulty in reading, english as a second language, word reading

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Authors: Irena Smetackova

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The important part of school mathematics are word problems which represent the connection between school knowledge and life reality. To find the reasons why students consider word problems to be difficult, it is necessary to take into consideration the motivational settings, besides mathematical knowledge and reading skills. Our goal is to identify whether the familiar or unfamiliar context of math word problem influences solving success rate and if so, whether the reasons are motivational or cognitive. For this purpose, we conducted three steps study in group of fifty pupils 9-10 years old. In the first step, we asked pupils to create ‘the best’ word problems for entered numerical formula. The set of 19 word problems with different contexts were selected. In the second step, pupils were asked to evaluate (without solving) how they like each item and how easy it is for them. The 6 word problems with low preference and low estimated success rate were selected and combined with other 6 problems with high preference and success rate. In the third step, the same pupils were asked to solve the word problems. The analysis showed that pupils attitudes and solving toward word problems varied by the context. The strong gender patterns both in preferred contexts and in estimated success rates were identified however the real success rate did not differ so strongly. The success gap between word problems with and without preferred contexts were stronger than the gap between problems with and without real experience with the context. The hypothesis that motivational factors are more important than cognitive factors was confirmed.

Keywords: mathematics, context of reality, motivation, cognition, word problems

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Authors: Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park, Sang-Jo Lee

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This paper proposes a method of learning topics for broadcasting contents. There are two kinds of texts related to broadcasting contents. One is a broadcasting script which is a series of texts including directions and dialogues. The other is blogposts which possesses relatively abstracted contents, stories and diverse information of broadcasting contents. Although two texts range over similar broadcasting contents, words in blogposts and broadcasting script are different. In order to improve the quality of topics, it needs a method to consider the word difference. In this paper, we introduce a semantic vocabulary expansion method to solve the word difference. We expand topics of the broadcasting script by incorporating the words in blogposts. Each word in blogposts is added to the most semantically correlated topics. We use word2vec to get the semantic correlation between words in blogposts and topics of scripts. The vocabularies of topics are updated and then posterior inference is performed to rearrange the topics. In experiments, we verified that the proposed method can learn more salient topics for broadcasting contents.

Keywords: broadcasting script analysis, topic expansion, semantic correlation analysis, word2vec

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Authors: Sutharsini Jesuthasan, N. Umakanth

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Presently the impact of electronic word of mouth on consumer’s purchasing intentions very popular one for a long time period. Even though now this E-WOM got a new evolution through social media. Before this new concept, general people were able to speak with any people on the internet. But likely social media enable people to talk with colleagues, friends and other people on the internet. Meanwhile, this new path way of E-WOM might be more powerful in terms of confusing purchase intention. And negative side of E-WOM very important in this competitive era. So, this study elaborates the negative E-WOM within the context of social media such as face book. And especially this study identifies the influence of negative E-WOM in social media on consumer’s purchase intention. Virtual snowball sampling method was used by researcher to identify the hidden population. Finally, spss 20.0 also used for data analysis purpose. And conclusion and recommendations are given based on the findings. And this research also will support to both parties such as researcher and participants.

Keywords: word of mouth, social media, purchase intention, electronic word of mouth

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Authors: Seyedeh Khadijeh. Mirbazel, Masoumeh Arjmandi

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Semantics is a linguistic approach and a scientific stream, and like all scientific streams, it is dynamic. The study of meaning is carried out in the broad semantic collections of words that form the discourse. In other words, meaning is not something that can be found in a word; rather, the formation of meaning is a process that takes place in a discourse as a whole. One of the contemporary semantic theories is Izutsu's Semantic Field Theory. According to this theory, the discovery of meaning depends on the function of words and takes place within the context of language. The purpose of this research is to identify the meaning of the word "Nas" in the discourse of verse 24 of Surah Al-Baqarah, which introduces "Nas" as the firewood of hell, but the translators have translated it as "people". The present research has investigated the semantic structure of the word "Nas" using the aforementioned theory through the descriptive-analytical method. In the process of investigation, by matching the semantic fields of the Quranic word "Nas", this research came to the conclusion that "Nas" implies those persons who have forgotten God and His covenant in believing in His Oneness. For this reason, God called them "Nas (the forgetful)" - the imperfect participle of the noun /næsiwoɔn/ in single trinity of Arabic language, which means “to forget”. Therefore, the intended meaning of "Nas" in the verses that have the word "Nas" is not equivalent to "People" which is a general noun.

Keywords: Nas, people, semantics, semantic field theory.

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Authors: João Rato, Nuno Costa

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The human verbal communication is a two-way process which requires a mutual understanding that will result in some considerations. This kind of communication, also called dialogue, besides the supposed human agents it can also be performed between human agents and machines. The interaction between Men and Machines, by means of a natural language, has an important role concerning the improvement of the communication between each other. Aiming at knowing the performance of some speech recognition systems, this document shows the results of the accomplished tests according to the Word Error Rate evaluation method. Besides that, it is also given a set of information linked to the systems of Man-Machine communication. After this work has been made, conclusions were drawn regarding the Speech Recognition Systems, among which it can be mentioned their poor performance concerning the voice interpretation in noisy environments.

Keywords: automatic speech recognition, man-machine conversation, speech recognition, spoken dialogue systems, word error rate

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Alaa Alrakaf, Sk. Md. Mizanur Rahman

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Since the last two decades’ Arabic natural language processing (ANLP) has become increasingly much more important. One of the key issues related to ANLP is ambiguity. In Arabic language different pronunciation of one word may have a different meaning. Furthermore, ambiguity also has an impact on the effectiveness and efficiency of Machine Translation (MT). The issue of ambiguity has limited the usefulness and accuracy of the translation from Arabic to English. The lack of Arabic resources makes ambiguity problem more complicated. Additionally, the orthographic level of representation cannot specify the exact meaning of the word. This paper looked at the diacritics of Arabic language and used them to disambiguate a word. The proposed approach of word sense disambiguation used Diacritizer application to Diacritize Arabic text then found the most accurate sense of an ambiguous word using Naïve Bayes Classifier. Our Experimental study proves that using Arabic Diacritics with Naïve Bayes Classifier enhances the accuracy of choosing the appropriate sense by 23% and also decreases the ambiguity in machine translation.

Keywords: Arabic natural language processing, machine learning, machine translation, Naive bayes classifier, word sense disambiguation

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Authors: Bowen Ding, Yihao Kuang

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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.

Keywords: deep metric learning, syntax tree probing, natural language processing, word representations

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Authors: Voronina Ekaterina Borisovna

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The problem of expressivity of advertising lexicon is studied in the article. The comparison of English and Russian advertising lexicons is done. The objects of the analysis were English and Russian advertising texts, both printed advertising texts and texts extracted from the commercials. Some conclusions concerning the expressivity of advertising lexicon were made. Expressivity can be included in the semantic structure of words or created by word-formation means. Expressivity caused by morphological derivatives includes such facilities as derivational affixes, models and types of word formation.

Keywords: advertising lexicon, expressivity, word-formation means, linguistics

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Authors: Gridaphat Sriharee

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Building semantic-relatedness Thai word ontology can be implemented by considering word forms and word meaning. This research proposed the methodology for building the ontology, which can be used for semantic analysis. There are four categories of words: similar form and the same meaning, similar form and similar meaning, different form and opposite/same meaning, and different form and similar meaning, which will be used as initial words for building the proposed ontology. Extension of the ontology can be augmented by considering the messages that give the meaning of the word from the dictionaries. Exploiting WordNet to construct the proposed ontology was investigated and discussed. The proposed ontology was evaluated for its quality. With the proposed methodology, it is promising that the constructed ontology is a well-defined ontology.

Keywords: Thai, NLP, semantics, ontology

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Authors: Shahriar M. Saadullah, Abdul-Quddoos Abdul-Basith, Zaki K. Abushawish

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As a part of academic research in Islamic Accounting it is important to know how the word Accounting is discussed in the Qur’aan. This paper identifies and analyzes the word Accounting in the Qur’aan, which is significant to know and understand. The paper uses a methodology of identifying the root word of Accounting Hasaba (حسب) in the Qur’aan with the help of Islam 360 software and analyzes the use of the relevant words derived from the root word. Then the paper attempts to connect the findings to the contemporary Accounting issues. The paper finds that the root word of Accounting Hasaba (حسب) appears in the Qur’aan 109 times but it is only used in the sense Account, Accountable, or Accounting 45 times. These words appear in 44 different verses in the Qur’aan, appearing twice in one of the verses. The paper divides these verses into 8 different themes namely, Day of Accounting, without any Accounting, Accounting of Time, Self-Accounting, Swift in Accounting, Accounting is only with God, Awareness and the Good Accounting, and Heedlessness and the Bad Accounting. The way the words Account, Accounting, and Accountable is discussed in the Qur’aan links to the contemporary accounting issues including Ethics, Agency Theory, and Internal Control. The links discovered in the paper clearly shows the timeless nature of the message of the Qur’aan.

Keywords: accounting, contemporary accounting issues, Qur'aan, root word of accounting hasaba

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Authors: Aarthy Anandan, Anitha Narasimhan, Madhan Karky

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Word-based games are popular in helping people to improve their vocabulary skills. Games like ‘word search’ and crosswords provide a smart way of increasing vocabulary skills. Word search games are fun to play, but also educational which actually helps to learn a language. Finding the words from word search puzzle helps the player to remember words in an easier way, and it also helps to learn the spellings of words. In this paper, we present a tile distribution algorithm for a Maze-Based Treasure Hunt Game 'Pudhaiyal’ for Tamil words, which describes how words can be distributed horizontally, vertically or diagonally in a 10 x 10 grid. Along with the tile distribution algorithm, we also present an algorithm for the scoring model of the game. The proposed game has been tested with 20,000 Tamil words.

Keywords: Pudhaiyal, Tamil word game, word search, scoring, maze, algorithm

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Authors: J. Marie Hicks

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The art of the poetic conjoins meaning and symbolism with imagery and rhythm. Perhaps the reader might read this opening sentence as 'The art of the poetic combines meaning and symbolism with imagery and rhythm,' which holds a similar message, but is not quite the same. The reader understands that these factors are combined in this literary form, but to gain a sense of the conjoining of these factors, the reader is forced to consider that these aspects of poetry are not simply combined, but actually adjoin, abut, skirt, or touch in the poetic form. This alternative word choice is an example of substitutional inference. Poetry is, ostensibly, a literary form where language is used precisely or creatively to evoke specific images or emotions for the reader. Often, the reader can predict a coming rhyme or descriptive word choice in a poem, based on previous rhyming pattern or earlier imagery in the poem. However, there are instances when the poet uses an unexpected word choice to create multiple meanings and connections. In these cases, the reader is presented with an unusual phrase or image, requiring that they think about what that image is meant to suggest, and their mind also suggests the word they expected, creating a second, overlying image or meaning. This is what is meant by the term 'substitutional inference.' This is different than simply using a double entendre, a word or phrase that has two meanings, often one complementary and the other disparaging, or one that is innocuous and the other suggestive. In substitutional inference, the poet utilizes an unanticipated word that is either visually or phonetically similar to the expected word, provoking the reader to work to understand the poetic phrase as written, while unconsciously incorporating the meaning of the line as anticipated. In other words, by virtue of a word substitution, an inference of the logical word choice is imparted to the reader, while they are seeking to rationalize the word that was actually used. There is a substitutional inference of meaning created by the alternate word choice. For example, Louise Bogan, 4th Poet Laureate of the United States, used substitutional inference in the form of homonyms, malapropisms, and other unusual word choices in a number of her poems, lending depth and greater complexity, while actively engaging her readers intellectually with her poetry. Substitutional inference not only adds complexity to the potential interpretations of Bogan’s poetry, as well as the poetry of others, but provided a method for writers to infuse additional meanings into their work, thus expressing more information in a compact format. Additionally, this nuancing enriches the poetic experience for the reader, who can enjoy the poem superficially as written, or on a deeper level exploring gradations of meaning.

Keywords: poetic inference, poetic word play, substitutional inference, word substitution

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Authors: Liana Lortkipanidze, Nino Amirezashvili, Nino Javashvili

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The purpose of the grammatical dictionary is to provide information on the morphological and syntactic characteristics of the basic word in the dictionary entry. The electronic grammatical dictionaries are used as a tool of automated morphological analysis for texts processing. The Georgian Grammatical Dictionary should contain grammatical information for each word: part of speech, type of declension/conjugation, grammatical forms of the word (paradigm), alternative variants of basic word/lemma. In this paper, we present the system for compiling the Georgian Grammatical Dictionary automatically. We propose dictionary-based methods for extending grammatical lexicons. The input lexicon contains only a few number of words with identical grammatical features. The extension is based on similarity measures between features of words; more precisely, we add words to the extended lexicons, which are similar to those, which are already in the grammatical dictionary. Our dictionaries are corpora-based, and for the compiling, we introduce the method for lemmatization of unknown words, i.e., words of which neither full form nor lemma is in the grammatical dictionary.

Keywords: acquisition of lexicon, Georgian grammatical dictionary, lemmatization rules, morphological processor

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Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

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The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

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Authors: Roya Alipour

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The present study concentrates on answering the question of whether there are unintentional differences between genders in the translation of emotive and non-emotive texts, resulting in female translators preferring more expressive words when translating emotive texts in comparison to their male counterparts. The works of four translators, two males and two females, who had translated Fredrik Backman’s novel: A Man Called Ove, from English into Persian were used as samples of the study. To answer the research question, qualitative method was used, and the data were collected by analyzing some words, phrases and sentences as the bases for analysis. It was concluded that although there were obvious differences in word choice in translations, no specific pattern was found that showed gender might affect translation of emotive and non-emotive texts.

Keywords: translation, gender, word choice, translator, A Man Called Ove

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Authors: S. B. Rathna Kumar, Pranjali A Ujwane, Panchanan Mohanty

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The present study aimed to develop a battery for assessing speech recognition performance by adults in Marathi. A total of four word lists were developed by considering word frequency, word familiarity, words in common use, and phonemic balance. Each word list consists of 25 words (15 monosyllabic words in CVC structure and 10 monosyllabic words in CVCV structure). Equivalence analysis and performance-intensity function testing was carried using the four word lists on a total of 150 native speakers of Marathi belonging to different regions of Maharashtra (Vidarbha, Marathwada, Khandesh and Northern Maharashtra, Pune, and Konkan). The subjects were further equally divided into five groups based on above mentioned regions. It was found that there was no significant difference (p > 0.05) in the speech recognition performance between groups for each word list and between word lists for each group. Hence, the four word lists developed were equally difficult for all the groups and can be used interchangeably. The performance-intensity (PI) function curve showed semi-linear function, and the groups’ mean slope of the linear portions of the curve indicated an average linear slope of 4.64%, 4.73%, 4.68%, and 4.85% increase in word recognition score per dB for list 1, list 2, list 3 and list 4 respectively. Although, there is no data available on speech recognition tests for adults in Marathi, most of the findings of the study are in line with the findings of research reports on other languages. The four word lists, thus developed, were found to have sufficient reliability and validity in assessing speech recognition performance by adults in Marathi.

Keywords: speech recognition performance, phonemic balance, equivalence analysis, performance-intensity function testing, reliability, validity

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Authors: Mohammad Ba’azm

Abstract:

The self-referentiality method as the missing ring of the Qur’an by Qur’an’s interpretation has a precise application at the level of the Quranic vocabulary, but after entering the domain of the verses, chapters and the whole Qur’an, it reveals its defect. Self-referentiality cannot show the clear concept of the Quranic scriptures, unlike the Qur’an by Qur’an’s interpretation method that guides us to the comprehension and exact hermeneutics. The Qur’an by Qur’an’s interpretation is a solid way of comprehension of the verses of the Qur'an and does not use external resources to provide implications and meanings with different theoretical and practical supports. In this method, theoretical supports are based on the basics and modalities that support and validate the legitimacy and validity of the interpretive method discussed, and the practical supports also relate to the practitioners of the religious elite. The combination of these two methods illustrates the exact understanding of the Qur'an at the level of Quranic verses, chapters, and the whole Qur’an. This study by examining the word 'book' in the Qur'an shows the difference between the two methods, and the necessity of attachment of these, in order to attain a desirable level for comprehensions meaning of the Qur'an. In this article, we have proven that by aspects of the meaning of the Quranic words, we cannot say any word has an exact meaning.

Keywords: Qur’an’s hermeneutic, self-referentiality, The Qur’an by Qur’an’s Interpretation, polysemy

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Authors: Pardeep Singh, Kamlesh Dutta

Abstract:

Many languages have fixed sentence structure and others are free word order. The accuracy of anaphora resolution of syntax based algorithm depends on structure of the sentence. So, it is important to analyze the structure of any language before implementing these algorithms. In this study, we analyzed the sentence structure exploiting the case marker in Hindi as well as some special tag for subject and object. We also investigated the word order for Hindi. Word order typology refers to the study of the order of the syntactic constituents of a language. We analyzed 165 news items of Ranchi Express from EMILEE corpus of plain text. It consisted of 1745 sentences. Eight file of dialogue based from the same corpus has been analyzed which will have 1521 sentences. The percentages of subject object verb structure (SOV) and object subject verb (OSV) are 66.90 and 33.10, respectively.

Keywords: anaphora resolution, free word order languages, SOV, OSV

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Authors: Pelumi Olowofoyeku

Abstract:

English as a language has great reach and influence; it is taught all over the world. For instance, in Nigeria, English language is been taught and learned as a second language; therefore second learners of English in Nigeria have certain problems they contend with. Because of the dissimilarities in word formation patterns of English and Yoruba languages, Yoruba learners of English mostly found in the south west of Nigeria, and some parts of Kwara, Kogi, and Edo states of Nigeria have problems with word formation patterns in English. The objectives of this paper therefore, are: to identify the levels of word formation dissimilarities in English and Yoruba languages and to examine the effects of these dissimilarities on the Yoruba learners of English. The data for this paper were graded words purposely selected and presented to selected students of Adeniran Ogunsanya College of Education, Oto-Ijanikin, Lagos, who are Yoruba learners of English. These respondents were randomly selected to form words which are purposively selected to test the effects of word formation dissimilarities between Yoruba (the respondent’s first language) and English language on the respondents. The dissimilarities are examined using contrastive analysis tools. This paper reveals that there are differences in the word formation patterns of Yoruba and English languages. The writer believes that there is need for language teachers to undertake comparative studies of the two languages involved for methodological reasons. The author then suggests that teachers should identify the problem areas and systematically teach their students. The paper concludes that although English and Yoruba word formation patterns differ very significantly in many respects, there exist language universals in all languages which language educators should take advantage of in teaching.

Keywords: word formation patterns, graded words, ESL, Yoruba learners

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Authors: Pui-sze Yeung, Connie Suk-han Ho, David Wai-ock Chan, Kevin Kien-hoa Chung

Abstract:

Background: Recent findings have shown that transcription skills play a unique and significant role in Chinese word reading and spelling (i.e. word dictation), and written composition development. The interrelationships among component skills of transcription, word reading, word spelling, and written composition in Chinese have rarely been examined in the literature. Is the contribution of component skills of transcription to Chinese written composition mediated by word level skills (i.e., word reading and spelling)? Methods: The participants in the study were 249 Chinese children in Grade 1, Grade 3, and Grade 5 in Hong Kong. They were administered measures of general reasoning ability, orthographic knowledge, stroke sequence knowledge, word spelling, handwriting fluency, word reading, and Chinese narrative writing. Orthographic knowledge- orthographic knowledge was assessed by a task modeled after the lexical decision subtest of the Hong Kong Test of Specific Learning Difficulties in Reading and Writing (HKT-SpLD). Stroke sequence knowledge: The participants’ performance in producing legitimate stroke sequences was measured by a stroke sequence knowledge task. Handwriting fluency- Handwriting fluency was assessed by a task modeled after the Chinese Handwriting Speed Test. Word spelling: The stimuli of the word spelling task consist of fourteen two-character Chinese words. Word reading: The stimuli of the word reading task consist of 120 two-character Chinese words. Written composition: A narrative writing task was used to assess the participants’ text writing skills. Results: Analysis of covariance results showed that there were significant between-grade differences in the performance of word reading, word spelling, handwriting fluency, and written composition. Preliminary hierarchical multiple regression analysis results showed that orthographic knowledge, word spelling, and handwriting fluency were unique predictors of Chinese written composition even after controlling for age, IQ, and word reading. The interaction effects between grade and each of these three skills (orthographic knowledge, word spelling, and handwriting fluency) were not significant. Path analysis results showed that orthographic knowledge contributed to written composition both directly and indirectly through word spelling, while handwriting fluency contributed to written composition directly and indirectly through both word reading and spelling. Stroke sequence knowledge only contributed to written composition indirectly through word spelling. Conclusions: Preliminary hierarchical regression results were consistent with previous findings about the significant role of transcription skills in Chinese word reading, spelling and written composition development. The fact that orthographic knowledge contributed both directly and indirectly to written composition through word reading and spelling may reflect the impact of the script-sound-meaning convergence of Chinese characters on the composing process. The significant contribution of word spelling and handwriting fluency to Chinese written composition across elementary grades highlighted the difficulty in attaining automaticity of transcription skills in Chinese, which limits the working memory resources available for other composing processes.

Keywords: orthographic knowledge, transcription skills, word reading, writing

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