Pub Date : 2021-01-01DOI: 10.1504/ijie.2021.112320
D. Karuppaiah, P. Vincent
{"title":"Word sense disambiguation in Tamil using Indo-WordNet and cross-language semantic similarity","authors":"D. Karuppaiah, P. Vincent","doi":"10.1504/ijie.2021.112320","DOIUrl":"https://doi.org/10.1504/ijie.2021.112320","url":null,"abstract":"","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-22DOI: 10.1504/ijie.2020.10027864
D. Karuppaiah, P. Vincent
Word sense disambiguation is the way to compute the correct sense of a word. It is considered as one of the important subtasks in natural language processing, machine translation and information retrieval. WSD found improving the overall performances of these systems. The job of WSD is to eliminate all senses of a word except the appropriate one as per the given context. The work in Tamil linguistics domain for information retrieval or natural language processing is very less. WSD can be performed in supervised and unsupervised manner. Here, we have proposed an unsupervised approach to disambiguate Tamil words in a given context using the context words and their dictionary gloss definitions. We have proposed two variants of our approach. The first approach uses the number of word overlapping between the glosses of context words whereas the second one uses the similarity between the glosses of context words with that of the ambiguous word. The second one found best among the two. For our approach, we have used Tamil Indo-WordNet, Oxford Tamil Dictionary and English WordNet dictionary glosses. Our method achieves better result in recognising correct senses in Tamil text.
{"title":"Word Sense Disambiguation in Tamil using Indo Wordnet and Cross-Language Semantic Similarity","authors":"D. Karuppaiah, P. Vincent","doi":"10.1504/ijie.2020.10027864","DOIUrl":"https://doi.org/10.1504/ijie.2020.10027864","url":null,"abstract":"Word sense disambiguation is the way to compute the correct sense of a word. It is considered as one of the important subtasks in natural language processing, machine translation and information retrieval. WSD found improving the overall performances of these systems. The job of WSD is to eliminate all senses of a word except the appropriate one as per the given context. The work in Tamil linguistics domain for information retrieval or natural language processing is very less. WSD can be performed in supervised and unsupervised manner. Here, we have proposed an unsupervised approach to disambiguate Tamil words in a given context using the context words and their dictionary gloss definitions. We have proposed two variants of our approach. The first approach uses the number of word overlapping between the glosses of context words whereas the second one uses the similarity between the glosses of context words with that of the ambiguous word. The second one found best among the two. For our approach, we have used Tamil Indo-WordNet, Oxford Tamil Dictionary and English WordNet dictionary glosses. Our method achieves better result in recognising correct senses in Tamil text.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":"1 1","pages":"62"},"PeriodicalIF":0.0,"publicationDate":"2020-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41623499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1504/ijie.2020.10027855
Taanika Arora, Arvind Kumar, Bhawna Agarwal
The phenomenal growth of social media sites, has enticed the companies to target their consumers by advertising through most used mediums, hence it becomes crucial for the advertisers to carefully design the ads thereafter also check its effectiveness. The purpose of this paper is to propose a conceptual model which determines the impact of various advertising content factors such as informativeness, entertainment, credibility, interactivity and privacy concerns on attitude of Indian millennials towards social media advertising. Using non-probability sampling, the data was collected using the online questionnaire through Google Forms from a total of 470 social media users. The adapted scales have been validated through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), after which path analysis has been applied using SPSS AMOS 22.0 for testing the various formulated hypothesis. The results indicated significant relationships which can be useful in understanding the attitude and behavioural responses of Indian millennials towards social media advertising. The study can be useful to the marketers, advertisers and brand managers in designing advertisements on social media sites by embedding certain essential features which can positively shape up the attitudes and further develop behavioural responses.
{"title":"Impact of social media advertising on millennials buying behaviour","authors":"Taanika Arora, Arvind Kumar, Bhawna Agarwal","doi":"10.1504/ijie.2020.10027855","DOIUrl":"https://doi.org/10.1504/ijie.2020.10027855","url":null,"abstract":"The phenomenal growth of social media sites, has enticed the companies to target their consumers by advertising through most used mediums, hence it becomes crucial for the advertisers to carefully design the ads thereafter also check its effectiveness. The purpose of this paper is to propose a conceptual model which determines the impact of various advertising content factors such as informativeness, entertainment, credibility, interactivity and privacy concerns on attitude of Indian millennials towards social media advertising. Using non-probability sampling, the data was collected using the online questionnaire through Google Forms from a total of 470 social media users. The adapted scales have been validated through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), after which path analysis has been applied using SPSS AMOS 22.0 for testing the various formulated hypothesis. The results indicated significant relationships which can be useful in understanding the attitude and behavioural responses of Indian millennials towards social media advertising. The study can be useful to the marketers, advertisers and brand managers in designing advertisements on social media sites by embedding certain essential features which can positively shape up the attitudes and further develop behavioural responses.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42760256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1504/ijie.2020.10024606
Mandy Mok Kim Man, Lo May Chiun
This study examines innovativeness and environmental factors that can influence the performance of small and medium-sized enterprises (SMEs) in the Malaysian manufacturing sector. Previous research have focused mainly on technological innovation rather than innovativeness in administration process and innovation culture. The present study examines the fundamental nature of innovativeness and relates these various elements of innovativeness to SMEs performance. The present study includes the role of the government. Firstly, in the Malaysian context, the government interferes in the market through new business policies, increasing or decreasing the interest rate, controlling money supply and implementing competition policy law. Secondly, the role of government has been neglected in most previous research in measuring the environment influences on business in spite of their importance in determining the environment indicators, such as, environmental uncertainty and intensity of competition. The present study shows that the innovativeness and environmental factors have significant impact on SMEs performance.
{"title":"Innovativeness, Environment and Performance of Small and Medium-sized Enterprises (SMEs) in the Manufacturing Sector in Malaysia","authors":"Mandy Mok Kim Man, Lo May Chiun","doi":"10.1504/ijie.2020.10024606","DOIUrl":"https://doi.org/10.1504/ijie.2020.10024606","url":null,"abstract":"This study examines innovativeness and environmental factors that can influence the performance of small and medium-sized enterprises (SMEs) in the Malaysian manufacturing sector. Previous research have focused mainly on technological innovation rather than innovativeness in administration process and innovation culture. The present study examines the fundamental nature of innovativeness and relates these various elements of innovativeness to SMEs performance. The present study includes the role of the government. Firstly, in the Malaysian context, the government interferes in the market through new business policies, increasing or decreasing the interest rate, controlling money supply and implementing competition policy law. Secondly, the role of government has been neglected in most previous research in measuring the environment influences on business in spite of their importance in determining the environment indicators, such as, environmental uncertainty and intensity of competition. The present study shows that the innovativeness and environmental factors have significant impact on SMEs performance.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":"1 1","pages":"444"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43058077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-24DOI: 10.1504/ijie.2020.10026354
V. R. Dheera, J. Krishnan
This study investigates the influence of human resource management (HRM) practices on the organisational commitment in hospitality industry. The study hypothesises that HRM practices (employee motivation, rewards and awards, grievance handling, employee engagement, performance appraisal and training and development) will be positively related to commitment to organisation and career. The study was conducted with randomly selected employees (300 numbers) of leading hotels in Chennai, Tamilnadu. The statistical results of the data collected from the employees of hotels reveal that majority of the six HRM practices have direct positive and significant relationships with commitment to organisation and career. The employees of the hotels felt that 'grievance handling' function of HRM practices has to be given more importance and 'performance appraisal system' has to be more effective in a manner to motivate employees to perform better.
{"title":"Influence of human resource management practices on the organisational commitment with specific reference to selected hotels in Chennai","authors":"V. R. Dheera, J. Krishnan","doi":"10.1504/ijie.2020.10026354","DOIUrl":"https://doi.org/10.1504/ijie.2020.10026354","url":null,"abstract":"This study investigates the influence of human resource management (HRM) practices on the organisational commitment in hospitality industry. The study hypothesises that HRM practices (employee motivation, rewards and awards, grievance handling, employee engagement, performance appraisal and training and development) will be positively related to commitment to organisation and career. The study was conducted with randomly selected employees (300 numbers) of leading hotels in Chennai, Tamilnadu. The statistical results of the data collected from the employees of hotels reveal that majority of the six HRM practices have direct positive and significant relationships with commitment to organisation and career. The employees of the hotels felt that 'grievance handling' function of HRM practices has to be given more importance and 'performance appraisal system' has to be more effective in a manner to motivate employees to perform better.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45356569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-24DOI: 10.1504/ijie.2020.10026353
T. Vivek, V. Rajavarman, S. Madala
Security is the main aspect to explore human data from different web oriented applications present in artificial intelligence (AI). It is very difficult to use different web applications without security to access data in various places. So that various types of security related approaches were introduced to use services in securely in outside environment, but they have some limitations to protect data from outside attackers (hackers). So that in this paper, we propose and introduce a novel and advanced security model to provide security from outside attackers in AI related web oriented applications. In this approach, we follow the basic features related to Captcha as a graphical password to enable security services in our proposed approach. Using Captcha graphical passwords in our approach, we describe pushing attacks, pass-on attacks and guessing attacks in web applications with random selection of Captcha passwords to use web services. Our experimental results show efficient security relations when compare to existing security approaches in terms of Captcha generation, time and other parameters present in web security applications.
{"title":"Advanced graphical-based security approach to handle hard AI problems based on visual security","authors":"T. Vivek, V. Rajavarman, S. Madala","doi":"10.1504/ijie.2020.10026353","DOIUrl":"https://doi.org/10.1504/ijie.2020.10026353","url":null,"abstract":"Security is the main aspect to explore human data from different web oriented applications present in artificial intelligence (AI). It is very difficult to use different web applications without security to access data in various places. So that various types of security related approaches were introduced to use services in securely in outside environment, but they have some limitations to protect data from outside attackers (hackers). So that in this paper, we propose and introduce a novel and advanced security model to provide security from outside attackers in AI related web oriented applications. In this approach, we follow the basic features related to Captcha as a graphical password to enable security services in our proposed approach. Using Captcha graphical passwords in our approach, we describe pushing attacks, pass-on attacks and guessing attacks in web applications with random selection of Captcha passwords to use web services. Our experimental results show efficient security relations when compare to existing security approaches in terms of Captcha generation, time and other parameters present in web security applications.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42111656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-24DOI: 10.1504/ijie.2020.10026356
R. Dash
The huge volume and variety of data stored in big data provide more accurate predictive platform for the users. However, the decision-making process becomes a tedious task due to requirement of much computational time and memory to access them. Thus, a solution to the said problem is data scoring that provides the selection of only those variables or features that impact the decision-making process to a greater extend. To cater the need of an efficient data scoring model, the work carried out in this paper proposes a new data scoring model for big data. The proposed model uses adaptive LASSO as the statistical method. The steps involved in the design of the proposed model are outlined with proper explanation. The model is trained and tested by k-fold cross validation technique. The performance of the model is measured using ROC curve. The model is simulated using R and is applied on three distinct datasets. To make a comparison with LASSO, LASSO is also applied on these datasets. The simulated results reveal that the adaptive LASSO performs better than LASSO for large-sized datasets.
{"title":"Design of data scoring model for big data","authors":"R. Dash","doi":"10.1504/ijie.2020.10026356","DOIUrl":"https://doi.org/10.1504/ijie.2020.10026356","url":null,"abstract":"The huge volume and variety of data stored in big data provide more accurate predictive platform for the users. However, the decision-making process becomes a tedious task due to requirement of much computational time and memory to access them. Thus, a solution to the said problem is data scoring that provides the selection of only those variables or features that impact the decision-making process to a greater extend. To cater the need of an efficient data scoring model, the work carried out in this paper proposes a new data scoring model for big data. The proposed model uses adaptive LASSO as the statistical method. The steps involved in the design of the proposed model are outlined with proper explanation. The model is trained and tested by k-fold cross validation technique. The performance of the model is measured using ROC curve. The model is simulated using R and is applied on three distinct datasets. To make a comparison with LASSO, LASSO is also applied on these datasets. The simulated results reveal that the adaptive LASSO performs better than LASSO for large-sized datasets.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47543380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-24DOI: 10.1504/ijie.2020.10026345
Praveen Edward James, M. H. Kit, C. Vaithilingam, Alan Tan Wee Chiat
The purpose of this paper is to design an efficient recurrent neural network (RNN)-based speech recognition system using software with long short-term memory (LSTM). The design process involves speech acquisition, pre-processing, feature extraction, training and pattern recognition tasks for a spoken sentence recognition system using LSTM-RNN. There are five layers namely, an input layer, a fully connected layer, a hidden LSTM layer, SoftMax layer and a sequential output layer. A vocabulary of 80 words which constitute 20 sentences is used. The depth of the layer is chosen as 20, 42 and 60 and the accuracy of each system is determined. The results reveal that the maximum accuracy of 89% is achieved when the depth of the hidden layer is 42. Since the depth of the hidden layer is fixed for a task, increased performance can be achieved by increasing the number of hidden layers.
{"title":"Recurrent neural network-based speech recognition using MATLAB","authors":"Praveen Edward James, M. H. Kit, C. Vaithilingam, Alan Tan Wee Chiat","doi":"10.1504/ijie.2020.10026345","DOIUrl":"https://doi.org/10.1504/ijie.2020.10026345","url":null,"abstract":"The purpose of this paper is to design an efficient recurrent neural network (RNN)-based speech recognition system using software with long short-term memory (LSTM). The design process involves speech acquisition, pre-processing, feature extraction, training and pattern recognition tasks for a spoken sentence recognition system using LSTM-RNN. There are five layers namely, an input layer, a fully connected layer, a hidden LSTM layer, SoftMax layer and a sequential output layer. A vocabulary of 80 words which constitute 20 sentences is used. The depth of the layer is chosen as 20, 42 and 60 and the accuracy of each system is determined. The results reveal that the maximum accuracy of 89% is achieved when the depth of the hidden layer is 42. Since the depth of the hidden layer is fixed for a task, increased performance can be achieved by increasing the number of hidden layers.","PeriodicalId":39490,"journal":{"name":"International Journal of Intelligent Enterprise","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49343353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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