Pub Date : 2018-09-01DOI: 10.1109/ICDIM.2018.8847066
Marika Spiteri, G. Azzopardi
Customer churn poses a significant challenge in various industries, including motor insurance. Retaining customers within insurance companies is much more challenging than in any other industry as policies are generally renewed every year. The main aim of this research is to identify the risk factors associated with churn, establish who are the churning customers and to model time until churn. The dataset used includes 72,445 policy holders and covers a period of one year. The data comprises information related to premiums, claims, policies and policy holders. The random forest algorithm turns out to be a very effective model for forecasting customer churn, reaching an accuracy rate of 91.18%. On the other hand, survival analysis was used to model time until churn and it was concluded that approximately 90% of the policy holders survived for the first five years while the majority of the policy holders survived till the end of the policy period. These results could be used to target the identified customers in marketing campaigns aimed at reducing the rate of churn while increasing profitability.
{"title":"Customer Churn Prediction for a Motor Insurance Company","authors":"Marika Spiteri, G. Azzopardi","doi":"10.1109/ICDIM.2018.8847066","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8847066","url":null,"abstract":"Customer churn poses a significant challenge in various industries, including motor insurance. Retaining customers within insurance companies is much more challenging than in any other industry as policies are generally renewed every year. The main aim of this research is to identify the risk factors associated with churn, establish who are the churning customers and to model time until churn. The dataset used includes 72,445 policy holders and covers a period of one year. The data comprises information related to premiums, claims, policies and policy holders. The random forest algorithm turns out to be a very effective model for forecasting customer churn, reaching an accuracy rate of 91.18%. On the other hand, survival analysis was used to model time until churn and it was concluded that approximately 90% of the policy holders survived for the first five years while the majority of the policy holders survived till the end of the policy period. These results could be used to target the identified customers in marketing campaigns aimed at reducing the rate of churn while increasing profitability.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126308301","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8846983
Fateh ur Rehman, M. Abbas, Sajjad Murtaza, Wasi Haider Butt, S. Rehman, Usman Qamar
With the growth of heterogeneous data generation sources low-quality data volumes are expanding on a daily basis. This research proposed SimFiller: similarity-based missing (null) values filling algorithm, to enhance the quality of data for the data mining process. The proposed algorithm calculates the similarity of record pairs from the input data in such a way that at least one member of the pair has a non-null value for the attribute under consideration. After finding similar pairs, the algorithm fills the missing values by considering the pair having greatest similarity under the specified similarity threshold. The quality of resulted data is evaluated by analyzing the classification accuracy results for Audiology dataset. Five other missing values filling algorithms were selected and total six copies of filled Audiology dataset were created. All six copies of filled Audiology dataset were tested for their classification accuracy. Results show a huge boost in classification accuracy for the copy of the dataset filled with the proposed algorithm and indicate that the quality of the dataset is enhanced. The proposed algorithm can also be tested on other datasets for filling their missing (null) values and can also be extended to remove other inconsistencies from the datasets.
{"title":"SimFiller. Similarity-Based Missing Values Filling Algorithm","authors":"Fateh ur Rehman, M. Abbas, Sajjad Murtaza, Wasi Haider Butt, S. Rehman, Usman Qamar","doi":"10.1109/ICDIM.2018.8846983","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8846983","url":null,"abstract":"With the growth of heterogeneous data generation sources low-quality data volumes are expanding on a daily basis. This research proposed SimFiller: similarity-based missing (null) values filling algorithm, to enhance the quality of data for the data mining process. The proposed algorithm calculates the similarity of record pairs from the input data in such a way that at least one member of the pair has a non-null value for the attribute under consideration. After finding similar pairs, the algorithm fills the missing values by considering the pair having greatest similarity under the specified similarity threshold. The quality of resulted data is evaluated by analyzing the classification accuracy results for Audiology dataset. Five other missing values filling algorithms were selected and total six copies of filled Audiology dataset were created. All six copies of filled Audiology dataset were tested for their classification accuracy. Results show a huge boost in classification accuracy for the copy of the dataset filled with the proposed algorithm and indicate that the quality of the dataset is enhanced. The proposed algorithm can also be tested on other datasets for filling their missing (null) values and can also be extended to remove other inconsistencies from the datasets.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126397902","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8846971
A. Siagian, M. Aritsugi
In this paper, we exploit function words as a feature for classifying deceptive and truthful opinions in the online reviews. Initially, we employ function words as a single feature to classify deceptive and truthful reviews. Then, we combine those function words with widely used text features in this task, namely, word and character n-grams, as our proposed combination feature. The experimental results exhibit that our proposed feature could perform well in this deceptive and truthful reviews classification. In particular, the obtained results of our proposed combination feature could outperform those using the baseline feature, i.e., word and character n-grams combinations. In addition, we apply the feature attribute selection, that is, Information Gain in conjunction with Ranker of WEKA, on our proposed combination feature. This treatment is to examine further the robustness of our proposed combination feature when dealing with this task. The latter experiment shows that after applying the feature attribute selection, our proposed combination feature was able to increase the classification results.
{"title":"Exploiting Function Words Feature in Classifying Deceptive and Truthful Reviews","authors":"A. Siagian, M. Aritsugi","doi":"10.1109/ICDIM.2018.8846971","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8846971","url":null,"abstract":"In this paper, we exploit function words as a feature for classifying deceptive and truthful opinions in the online reviews. Initially, we employ function words as a single feature to classify deceptive and truthful reviews. Then, we combine those function words with widely used text features in this task, namely, word and character n-grams, as our proposed combination feature. The experimental results exhibit that our proposed feature could perform well in this deceptive and truthful reviews classification. In particular, the obtained results of our proposed combination feature could outperform those using the baseline feature, i.e., word and character n-grams combinations. In addition, we apply the feature attribute selection, that is, Information Gain in conjunction with Ranker of WEKA, on our proposed combination feature. This treatment is to examine further the robustness of our proposed combination feature when dealing with this task. The latter experiment shows that after applying the feature attribute selection, our proposed combination feature was able to increase the classification results.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131927850","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8847006
I. O. Biskupic, Robert Aapovic, Mateo Jurčić
The strength of an organization is based on the quality of its internal structure and the way business processes are conducted. Business processes per se require skilful, continuous and permanent management or modelling. Therefore, this management segment is the greatest challenge in the labour market and its performance success often determines the strength of competitiveness. The authors in this paper want to highlight the common problems that arise in the organization of management and business process modelling. In addition, they want to consider the environment in which they arise (restructuring, acquisition, …) and to present one of the possible approaches to problem solving.
{"title":"K2 platform in Business process management","authors":"I. O. Biskupic, Robert Aapovic, Mateo Jurčić","doi":"10.1109/ICDIM.2018.8847006","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8847006","url":null,"abstract":"The strength of an organization is based on the quality of its internal structure and the way business processes are conducted. Business processes per se require skilful, continuous and permanent management or modelling. Therefore, this management segment is the greatest challenge in the labour market and its performance success often determines the strength of competitiveness. The authors in this paper want to highlight the common problems that arise in the organization of management and business process modelling. In addition, they want to consider the environment in which they arise (restructuring, acquisition, …) and to present one of the possible approaches to problem solving.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116490221","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8847019
Sarunya Kanjanawattana, M. Kimura
Non-native researchers encountered a problem of lacking academic writing skill. During the writing, we may accidentally use a word repeatedly due to our familiarity that reduces a quality of writing. To solve the problem, a paraphrase is a good option. It helps the manuscript read more flowery by reducing duplicate words and refining sentence alignments. In this study, we propose a novel idea to use a sentence dependency ontology to suggest possible verbs replaceable on existing context without influence to the original intention. We created an ontology-based system and designed a new ontology. To discover a list of verb choices, our idea is based on sentence dependency, especially a dependency between subject and verb (nsubj) as well as a relationship between verb and object (dobj). We chose them because these two dependencies had a strong relationship to the verb of the sentence. To evaluate the system, we compared the efficiencies of two different systems, i.e., a tradition system utilizing synonyms as word choices and our ontology-based system. As the results, ours provided the better performance rather than the traditional system. This clarifies that our system should be a proper solution for studies on paraphrasing.
{"title":"Ontology of Academic Sentence Dependencies for a Verb Choice Suggestion","authors":"Sarunya Kanjanawattana, M. Kimura","doi":"10.1109/ICDIM.2018.8847019","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8847019","url":null,"abstract":"Non-native researchers encountered a problem of lacking academic writing skill. During the writing, we may accidentally use a word repeatedly due to our familiarity that reduces a quality of writing. To solve the problem, a paraphrase is a good option. It helps the manuscript read more flowery by reducing duplicate words and refining sentence alignments. In this study, we propose a novel idea to use a sentence dependency ontology to suggest possible verbs replaceable on existing context without influence to the original intention. We created an ontology-based system and designed a new ontology. To discover a list of verb choices, our idea is based on sentence dependency, especially a dependency between subject and verb (nsubj) as well as a relationship between verb and object (dobj). We chose them because these two dependencies had a strong relationship to the verb of the sentence. To evaluate the system, we compared the efficiencies of two different systems, i.e., a tradition system utilizing synonyms as word choices and our ontology-based system. As the results, ours provided the better performance rather than the traditional system. This clarifies that our system should be a proper solution for studies on paraphrasing.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125300431","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 : 2018-09-01DOI: 10.1109/icdim.2018.8847089
{"title":"ICDIM 2018 Program Committee","authors":"","doi":"10.1109/icdim.2018.8847089","DOIUrl":"https://doi.org/10.1109/icdim.2018.8847089","url":null,"abstract":"","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"1398 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132574592","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 : 2018-09-01DOI: 10.1109/icdim.2018.8846991
A. Pavlíček, F. Sudzina
Internet security and privacy is a trending issue. Different tools are being employed by different users to stay anonymous and safe. The research focused on impact of Big Five Inventory personality traits on use of VPN and proxy servers. The research was conducted in the Czech Republic. The respondents were 478 university students. Gender, age, and type of student’s job were used as control variables. With regards to the results, conscientiousness, openness to experience, gender, and type of student’s job influence the preference. It is less conscientious, more open to experience, male, and working full time in the field they study that use VPN and proxy servers.
{"title":"Use of virtual private networks (VPN) and proxy servers: Impact of personality and demographics","authors":"A. Pavlíček, F. Sudzina","doi":"10.1109/icdim.2018.8846991","DOIUrl":"https://doi.org/10.1109/icdim.2018.8846991","url":null,"abstract":"Internet security and privacy is a trending issue. Different tools are being employed by different users to stay anonymous and safe. The research focused on impact of Big Five Inventory personality traits on use of VPN and proxy servers. The research was conducted in the Czech Republic. The respondents were 478 university students. Gender, age, and type of student’s job were used as control variables. With regards to the results, conscientiousness, openness to experience, gender, and type of student’s job influence the preference. It is less conscientious, more open to experience, male, and working full time in the field they study that use VPN and proxy servers.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114897154","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8846986
S. Marcu, Adrian Florea
This paper presents our smart parking solution implemented at “Lucian Blaga” University of Sibiu (LBUS) Romania, which consists in a hardware / software embedded system for managing the institution’s parking lots, namely sharing the parking places in excess for people who are in traffic in neighbourhood of LBUS and are looking to park. Our solution is flexible, universal, applicable to all faculties that have car parks from Romania and not only, in university cities where the crowd is bigger, but also to other private institutions that own parking spaces inefficiently exploited. The advantages introduced are primarily economic, then social and even environmental. The first benefit is economic - for institutions which exploit their free parking spaces during the year, at different moments of time (holiday, afternoon, or time when people left from work) offering for people who are searching for. From a social point of view, ensuring the convenience of drivers, reducing crowding especially at rush hours and reducing the time spent in search of a parking space, is also an important advantage. Reducing the cost of fuel required by cars that are looking for a parking space contributes to reducing pollution and improving air quality, having a positive impact on the environment.
{"title":"Smart parking system - another way of sharing economy provided by private institutions","authors":"S. Marcu, Adrian Florea","doi":"10.1109/ICDIM.2018.8846986","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8846986","url":null,"abstract":"This paper presents our smart parking solution implemented at “Lucian Blaga” University of Sibiu (LBUS) Romania, which consists in a hardware / software embedded system for managing the institution’s parking lots, namely sharing the parking places in excess for people who are in traffic in neighbourhood of LBUS and are looking to park. Our solution is flexible, universal, applicable to all faculties that have car parks from Romania and not only, in university cities where the crowd is bigger, but also to other private institutions that own parking spaces inefficiently exploited. The advantages introduced are primarily economic, then social and even environmental. The first benefit is economic - for institutions which exploit their free parking spaces during the year, at different moments of time (holiday, afternoon, or time when people left from work) offering for people who are searching for. From a social point of view, ensuring the convenience of drivers, reducing crowding especially at rush hours and reducing the time spent in search of a parking space, is also an important advantage. Reducing the cost of fuel required by cars that are looking for a parking space contributes to reducing pollution and improving air quality, having a positive impact on the environment.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132812982","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8847123
Abdihakim Mao, M. O. Shafiq
Analyzing data by visualization can help medical institutions make more informed decisions on the admission of future patients. A dataset provided by the University of California, Irvine, (UCI) Machine Learning Repository contains information on patients with diabetes that represents 10 years (1999-2008) of clinical care at 130 US hospitals. Charts on the diabetes dataset were created using Tableau, a data visualization software. In addition, an extensive analysis of the dataset was completed by providing possible reasons for the output found in the charts. The knowledge obtained from analyzing the diabetes dataset will help provide important information to medical institutions concerning future diabetic patients in need of hospital services.
{"title":"On the Analysis of a Public Dataset for Diabetes","authors":"Abdihakim Mao, M. O. Shafiq","doi":"10.1109/ICDIM.2018.8847123","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8847123","url":null,"abstract":"Analyzing data by visualization can help medical institutions make more informed decisions on the admission of future patients. A dataset provided by the University of California, Irvine, (UCI) Machine Learning Repository contains information on patients with diabetes that represents 10 years (1999-2008) of clinical care at 130 US hospitals. Charts on the diabetes dataset were created using Tableau, a data visualization software. In addition, an extensive analysis of the dataset was completed by providing possible reasons for the output found in the charts. The knowledge obtained from analyzing the diabetes dataset will help provide important information to medical institutions concerning future diabetic patients in need of hospital services.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123235565","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 : 2018-09-01DOI: 10.1109/ICDIM.2018.8847141
U. Kuzelewska, Arkadiusz Kurylowicz
This article discusses clustering approach to recommender systems acceleration and presents application of multi-clustering algorithms in the recommender systems based on collaborative filtering. It is explained the motivation for multi-clustering usage in comparison to clustering techniques, as well as results of experiments. Multi-clustering is variously defined in literature, however the common issue is its multiple views of one dataset. Different views may represent distinct aspects of the same data, adapting the most appropriate one to the current problem. In recommender systems domain it can be applied as a tool for precise modelling neighbourhood of object the recommendations are generated to. This article presents results of experiments demonstrating multi-clustering advantage over traditional clustering in neighbourhood determination.
{"title":"Multi-Clustering Applied to Collaborative Recommender Systems","authors":"U. Kuzelewska, Arkadiusz Kurylowicz","doi":"10.1109/ICDIM.2018.8847141","DOIUrl":"https://doi.org/10.1109/ICDIM.2018.8847141","url":null,"abstract":"This article discusses clustering approach to recommender systems acceleration and presents application of multi-clustering algorithms in the recommender systems based on collaborative filtering. It is explained the motivation for multi-clustering usage in comparison to clustering techniques, as well as results of experiments. Multi-clustering is variously defined in literature, however the common issue is its multiple views of one dataset. Different views may represent distinct aspects of the same data, adapting the most appropriate one to the current problem. In recommender systems domain it can be applied as a tool for precise modelling neighbourhood of object the recommendations are generated to. This article presents results of experiments demonstrating multi-clustering advantage over traditional clustering in neighbourhood determination.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124654536","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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