Pub Date : 2016-12-01DOI: 10.1109/IC3I.2016.7917953
Mandeep Kaur, M. Agnihotri
Cloud computing is really a new computing mode. Load balancing of resources across virtual machines is the fundamental problem of Cloud Computing. Effective job scheduling device must meet people 'requirements and increase the source usage, to be able to increase the entire efficiency of the cloud processing environment. In optimization issue. Genetic Algorithm and Ant Colony Optimization Algorithm have already been referred to as excellent option method. GA is created by adopting the organic progress process, while ACO is encouraged by the foraging behavior of ant species. This paper evaluated hybridization of ACO and GA adopt with multi-objective function to improve the global optimization solution.
{"title":"Performance evaluation of hybrid GAACO for task scheduling in cloud computing","authors":"Mandeep Kaur, M. Agnihotri","doi":"10.1109/IC3I.2016.7917953","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917953","url":null,"abstract":"Cloud computing is really a new computing mode. Load balancing of resources across virtual machines is the fundamental problem of Cloud Computing. Effective job scheduling device must meet people 'requirements and increase the source usage, to be able to increase the entire efficiency of the cloud processing environment. In optimization issue. Genetic Algorithm and Ant Colony Optimization Algorithm have already been referred to as excellent option method. GA is created by adopting the organic progress process, while ACO is encouraged by the foraging behavior of ant species. This paper evaluated hybridization of ACO and GA adopt with multi-objective function to improve the global optimization solution.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131779472","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918049
Yang Li, Da Xu
Traditional game AI is aimed at the standard players in the beginning of the construction. After designing the AI, The whole game decision-making system will not be dynamically adjusted, Because of the strong regularity, the traditional game AI is easy to be found the weakness by users, which is not easy to maintain the rationality of the decision. This paper presents a design scheme of game AI based on decision tree algorithm ID3. It through the mining of the player with the NPC interactive data on the set target has a significant correlation of data clues, real-time control of the decision-making system, to maintain the rationality of the decision. The experimental results show that the proposed scheme can adapt to the player's operation well, and it can keep the rationality of the decision in the actual operating environment.
{"title":"A game AI based on ID3 algorithm","authors":"Yang Li, Da Xu","doi":"10.1109/IC3I.2016.7918049","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918049","url":null,"abstract":"Traditional game AI is aimed at the standard players in the beginning of the construction. After designing the AI, The whole game decision-making system will not be dynamically adjusted, Because of the strong regularity, the traditional game AI is easy to be found the weakness by users, which is not easy to maintain the rationality of the decision. This paper presents a design scheme of game AI based on decision tree algorithm ID3. It through the mining of the player with the NPC interactive data on the set target has a significant correlation of data clues, real-time control of the decision-making system, to maintain the rationality of the decision. The experimental results show that the proposed scheme can adapt to the player's operation well, and it can keep the rationality of the decision in the actual operating environment.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131789038","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917982
Mukesh Taneja
Wireless networks for IoT applications support different types or classes of end devices. Each such class results in different uplink and downlink traffic behavior. It is important to identify suitable class for each end device. We first propose a generic framework for this purpose. We propose an element, called Software Controller, which learns device profile using variety of means such as information provided by the device itself, information provided by the associated IoT operator and contextual information using other sources. It can also use machine learning techniques to learn how a device might behave during certain period. Suitable resource management methods are to be associated with such classification schemes. We propose one such resource management method for 802.11ah type of networks. Next, we look at some traffic scenarios that may not be supported well by the existing device classes in some of these networks. Some IoT devices may always communicate low amount of data sporadically but some may need to communicate large amount of uplink or downlink (or bi-directional) data during certain time intervals. For example, an IoT device may need to measure (and report) certain parameters more frequently on detection of certain events, or a network server may want to set certain parameters or upgrade software at an IoT device during some time interval. It becomes important to control uplink / downlink communication opportunities and sleep interval at IoT devices in the network effectively. We propose a new device class and dynamic switching mechanism to handle such traffic scenarios effectively. We also include a software defined controller that provides for dynamic management of these communication opportunities at IoT devices and Access Points in the network.
{"title":"A framework for traffic management in IoT networks","authors":"Mukesh Taneja","doi":"10.1109/IC3I.2016.7917982","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917982","url":null,"abstract":"Wireless networks for IoT applications support different types or classes of end devices. Each such class results in different uplink and downlink traffic behavior. It is important to identify suitable class for each end device. We first propose a generic framework for this purpose. We propose an element, called Software Controller, which learns device profile using variety of means such as information provided by the device itself, information provided by the associated IoT operator and contextual information using other sources. It can also use machine learning techniques to learn how a device might behave during certain period. Suitable resource management methods are to be associated with such classification schemes. We propose one such resource management method for 802.11ah type of networks. Next, we look at some traffic scenarios that may not be supported well by the existing device classes in some of these networks. Some IoT devices may always communicate low amount of data sporadically but some may need to communicate large amount of uplink or downlink (or bi-directional) data during certain time intervals. For example, an IoT device may need to measure (and report) certain parameters more frequently on detection of certain events, or a network server may want to set certain parameters or upgrade software at an IoT device during some time interval. It becomes important to control uplink / downlink communication opportunities and sleep interval at IoT devices in the network effectively. We propose a new device class and dynamic switching mechanism to handle such traffic scenarios effectively. We also include a software defined controller that provides for dynamic management of these communication opportunities at IoT devices and Access Points in the network.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133373271","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918013
R. K. Lenka, Rabindra Kumar Barik, Noopur Gupta, Syed Mohd Ali, A. Rath, Harishchandra Dubey
In this digitalised world where every information is stored, the data a are growing exponentially. It is estimated that data are doubles itself every two years. Geospatial data are one of the prime contributors to the big data scenario. There are numerous tools of the big data analytics. But not all the big data analytics tools are capabilities to handle geospatial big data. In the present paper, it has been discussed about the recent two popular open source geospatial big data analytical tools i.e. SpatialHadoop and GeoSpark which can be used for analysis and process the geospatial big data in efficient manner. It has compared the architectural view of SpatialHadoop and GeoSpark. Through the architectural comparison, it has also summarised the merits and demerits of these tools according the execution times and volume of the data which has been used.
{"title":"Comparative analysis of SpatialHadoop and GeoSpark for geospatial big data analytics","authors":"R. K. Lenka, Rabindra Kumar Barik, Noopur Gupta, Syed Mohd Ali, A. Rath, Harishchandra Dubey","doi":"10.1109/IC3I.2016.7918013","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918013","url":null,"abstract":"In this digitalised world where every information is stored, the data a are growing exponentially. It is estimated that data are doubles itself every two years. Geospatial data are one of the prime contributors to the big data scenario. There are numerous tools of the big data analytics. But not all the big data analytics tools are capabilities to handle geospatial big data. In the present paper, it has been discussed about the recent two popular open source geospatial big data analytical tools i.e. SpatialHadoop and GeoSpark which can be used for analysis and process the geospatial big data in efficient manner. It has compared the architectural view of SpatialHadoop and GeoSpark. Through the architectural comparison, it has also summarised the merits and demerits of these tools according the execution times and volume of the data which has been used.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114443992","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917936
Tribid Debbarma, K. Chandrasekaran
Current computing systems comes with different power management and profiling tools to run the system in its optimal state. Though the hardware systems have advanced a lot in-terms of energy efficiency and computing power, the software's energy and resources efficiency is still lacking behind. In many cases due to poor/bad designing of software it cannot utilize the hardware efficiently and end up a system with high energy consumption. To address this issues software' s need a careful profiling in its development process to make the software efficient and less resource hungry. In this paper we compared some of the profiling tools available as Free and Open Source Software (FOSS) which are used under Linux environment. These software tools uses different strategies and have different accuracies in finding a system and software programs behavior and its resource requirements. Their performance and resource overheads such as memory, CPU, disk consumption were compared and results are summarized for making the tools selection easier to researchers and developers alike. Another important issue with these tools are that, their reporting formats are not always easy to understand and it makes them less user friendly.
{"title":"Comparison of FOSS based profiling tools in Linux operating system environment","authors":"Tribid Debbarma, K. Chandrasekaran","doi":"10.1109/IC3I.2016.7917936","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917936","url":null,"abstract":"Current computing systems comes with different power management and profiling tools to run the system in its optimal state. Though the hardware systems have advanced a lot in-terms of energy efficiency and computing power, the software's energy and resources efficiency is still lacking behind. In many cases due to poor/bad designing of software it cannot utilize the hardware efficiently and end up a system with high energy consumption. To address this issues software' s need a careful profiling in its development process to make the software efficient and less resource hungry. In this paper we compared some of the profiling tools available as Free and Open Source Software (FOSS) which are used under Linux environment. These software tools uses different strategies and have different accuracies in finding a system and software programs behavior and its resource requirements. Their performance and resource overheads such as memory, CPU, disk consumption were compared and results are summarized for making the tools selection easier to researchers and developers alike. Another important issue with these tools are that, their reporting formats are not always easy to understand and it makes them less user friendly.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114871226","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917941
Anand Shanker Tewari, Naina Yadav, A. Barman
Recommender System is a set of programs and techniques used for predicting items or rating of items in fields in which a user may be interested. The objectives of recommendation techniques are to assess and mitigate the problem of information overload where a user is not able to receive a clear result of his search. From these recommendations may help in various decision-making processes such as which items to buy, which music to listen, or which online news to read and which research paper to read etc. In this paper, we introduce a new recommendation model which takes into consideration a user's information based on tagging. The proposed approach offers significant advantages in terms of improving the recommendation quality for movies.
{"title":"Efficient tag based personalised collaborative movie reccommendation system","authors":"Anand Shanker Tewari, Naina Yadav, A. Barman","doi":"10.1109/IC3I.2016.7917941","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917941","url":null,"abstract":"Recommender System is a set of programs and techniques used for predicting items or rating of items in fields in which a user may be interested. The objectives of recommendation techniques are to assess and mitigate the problem of information overload where a user is not able to receive a clear result of his search. From these recommendations may help in various decision-making processes such as which items to buy, which music to listen, or which online news to read and which research paper to read etc. In this paper, we introduce a new recommendation model which takes into consideration a user's information based on tagging. The proposed approach offers significant advantages in terms of improving the recommendation quality for movies.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122553796","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918042
Ashwin S. Ravi, Akshay Sarvesh, K. George
Financial market prediction, being a complex problem, has intrigued researchers for a long time. In this paper, we try to address the problem by treating it as a time-series and employing artificial neural networks (ANNs) to forecast the future stock value. Two types of neural network learning algorithms are illustrated for the current application: The backward propagation algorithm and an online sequential learning algorithm. Several training strategies are also proposed. The principle objective of this paper is to demonstrate the improvement in predictive performance using multiple neural networks. Towards this, an attempt is made at predicting the SENSEX value of the Bombay Stock Exchange.
{"title":"Online multiple-model approach to prediction for financial markets","authors":"Ashwin S. Ravi, Akshay Sarvesh, K. George","doi":"10.1109/IC3I.2016.7918042","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918042","url":null,"abstract":"Financial market prediction, being a complex problem, has intrigued researchers for a long time. In this paper, we try to address the problem by treating it as a time-series and employing artificial neural networks (ANNs) to forecast the future stock value. Two types of neural network learning algorithms are illustrated for the current application: The backward propagation algorithm and an online sequential learning algorithm. Several training strategies are also proposed. The principle objective of this paper is to demonstrate the improvement in predictive performance using multiple neural networks. Towards this, an attempt is made at predicting the SENSEX value of the Bombay Stock Exchange.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122658586","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917938
Odunayo Fadahunsi, Mithileysh Sathiyanarayanan
Business processes are modelled, visualized and analyzed using process maps, and implemented using productivity suites such as MS Visio, Business Process Extraction Language (BPEL), and some other productivity suites. However, the problem with such current process models is that it is static. Business process tasks modelled using non-interactive visualisation tool does not allow active engagement of the analyst or users developing the process maps with the process maps to determine what if scenarios. The constant changes to existing business processes are enforced due to several external and internal factors with an objective of improving process efficiency and effectiveness. So, we developed a Petri net process model to visualise business process tasks and allow interaction with the process model to allow the user or analyst to compute from an ‘as-is’ business process model to a ‘to be’ business process model that would optimise both the time it takes to complete the process (process duration) and the cost of executing the business process tasks (process costs). Petri nets whilst a form of visualisation of tasks also enables mathematical modelling of the process model. Methodology: We applied mathematical combination theory, combined with Petri nets formalism to create design options in generating alternative business process options with different process duration and cost factors to enable the process modeller or analyst make a better decision. We visualized and evaluated different dynamic ‘transitions’ sequence generated based on best duration and cost, modelled the ‘design options’ in the Platform Independent Petri Net editor (PIPE2) tool and performed further analysis of the Petri net properties of the modelled processes. Finally, we discussed how to visualize and analyze ‘design options’ and provided certain views on business processes. Results: We demonstrated through our research that Petri nets could be used in visualising different process tasks as and users can interact with the process model. This was implemented using a case study of a supermarket chain business process. This research helped in identifying six out of the eleven business process ‘design options’ generated are best optimised each with process duration of 28 hours and process cost of 35.57 dollars. However, further qualitative analysis of these optimised ‘design options’ effectively resulted in only one out of the eleven as the most optimal process design indicating the selected revised business process. The visualization is helpful in analyzing dynamic transitions for exploring and understanding complex behaviour in the business processes. The results suggest that the combination of mathematical approach in conjunction with the analytical properties of Petri Nets could be used to generate unbiased alternative business process designs that can be further evaluated by the business process re-engineer or analyst in order to revise an existing business process.
{"title":"Visualizing and analyzing dynamic business process using Petri nets","authors":"Odunayo Fadahunsi, Mithileysh Sathiyanarayanan","doi":"10.1109/IC3I.2016.7917938","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917938","url":null,"abstract":"Business processes are modelled, visualized and analyzed using process maps, and implemented using productivity suites such as MS Visio, Business Process Extraction Language (BPEL), and some other productivity suites. However, the problem with such current process models is that it is static. Business process tasks modelled using non-interactive visualisation tool does not allow active engagement of the analyst or users developing the process maps with the process maps to determine what if scenarios. The constant changes to existing business processes are enforced due to several external and internal factors with an objective of improving process efficiency and effectiveness. So, we developed a Petri net process model to visualise business process tasks and allow interaction with the process model to allow the user or analyst to compute from an ‘as-is’ business process model to a ‘to be’ business process model that would optimise both the time it takes to complete the process (process duration) and the cost of executing the business process tasks (process costs). Petri nets whilst a form of visualisation of tasks also enables mathematical modelling of the process model. Methodology: We applied mathematical combination theory, combined with Petri nets formalism to create design options in generating alternative business process options with different process duration and cost factors to enable the process modeller or analyst make a better decision. We visualized and evaluated different dynamic ‘transitions’ sequence generated based on best duration and cost, modelled the ‘design options’ in the Platform Independent Petri Net editor (PIPE2) tool and performed further analysis of the Petri net properties of the modelled processes. Finally, we discussed how to visualize and analyze ‘design options’ and provided certain views on business processes. Results: We demonstrated through our research that Petri nets could be used in visualising different process tasks as and users can interact with the process model. This was implemented using a case study of a supermarket chain business process. This research helped in identifying six out of the eleven business process ‘design options’ generated are best optimised each with process duration of 28 hours and process cost of 35.57 dollars. However, further qualitative analysis of these optimised ‘design options’ effectively resulted in only one out of the eleven as the most optimal process design indicating the selected revised business process. The visualization is helpful in analyzing dynamic transitions for exploring and understanding complex behaviour in the business processes. The results suggest that the combination of mathematical approach in conjunction with the analytical properties of Petri Nets could be used to generate unbiased alternative business process designs that can be further evaluated by the business process re-engineer or analyst in order to revise an existing business process.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125123515","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918801
Ancy Gonsalves, M. Narvekar
With the advancements of technology in wireless environment coupled with cheap cost of smart phones, mobile services such as net surfing, chatting, social networking etc, have become an integral part of day to day life. The user wants data as fast as possible. Due to constraints such as limited bandwidth and limited network connectivity it is therefore necessary to address issues of query processing in wireless distributed environment. This paper investigates various approaches for processing queries in mobile environment.
{"title":"A review of approaches for processing of queries in distributed mobile environment","authors":"Ancy Gonsalves, M. Narvekar","doi":"10.1109/IC3I.2016.7918801","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918801","url":null,"abstract":"With the advancements of technology in wireless environment coupled with cheap cost of smart phones, mobile services such as net surfing, chatting, social networking etc, have become an integral part of day to day life. The user wants data as fast as possible. Due to constraints such as limited bandwidth and limited network connectivity it is therefore necessary to address issues of query processing in wireless distributed environment. This paper investigates various approaches for processing queries in mobile environment.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129754142","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917937
Gaurav Khatwani, Praveen Ranjan Srivastava
As information technology has evolved, digital media has become increasingly fragmented and has started to proliferate multiple information channels. In order to optimize on the various digital channels that are available, organizations are increasingly recognizing the importance of gaining solid insights into consumer behavior and preferences that can be translated into marketing strategies. Specifically, they are keen to identify which information channels they can use to effectively reach and communicate with their target market. This paper describes how fuzzy AHP and TOPSIS can be used to develop a new method of decision making that will enable an effective and systematic decision process. This paper provides a demonstration of the underpinning working methodology of the proposed model by examining an illustrative example that is based on the decision process Internet users employ during their online search for information.
{"title":"Consumer preferences of information search channel and the role of information technology","authors":"Gaurav Khatwani, Praveen Ranjan Srivastava","doi":"10.1109/IC3I.2016.7917937","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917937","url":null,"abstract":"As information technology has evolved, digital media has become increasingly fragmented and has started to proliferate multiple information channels. In order to optimize on the various digital channels that are available, organizations are increasingly recognizing the importance of gaining solid insights into consumer behavior and preferences that can be translated into marketing strategies. Specifically, they are keen to identify which information channels they can use to effectively reach and communicate with their target market. This paper describes how fuzzy AHP and TOPSIS can be used to develop a new method of decision making that will enable an effective and systematic decision process. This paper provides a demonstration of the underpinning working methodology of the proposed model by examining an illustrative example that is based on the decision process Internet users employ during their online search for information.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121855215","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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