Pub Date : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257649
Vincent C. Hu, T. Grance, David F. Ferraiolo, D. R. Kuhn
Access Control (AC) systems are among the most critical of network security components. A system's privacy and security controls are more likely to be compromised due to the misconfiguration of access control policies rather than the failure of cryptographic primitives or protocols. This problem becomes increasingly severe as software systems become more and more complex, such as Big Data (BD) processing systems, which are deployed to manage a large amount of sensitive information and resources organized into a sophisticated BD processing cluster. Basically, BD access control requires the collaboration among cooperating processing domains to be protected as computing environments that consist of computing units under distributed AC managements. Many BD architecture designs were proposed to address BD challenges; however, most of them were focused on the processing capabilities of the “three Vs” (Velocity, Volume, and Variety). Considerations for security in protecting BD are mostly ad hoc and patch efforts. Even with some inclusion of security in recent BD systems, a critical security component, AC (Authorization), for protecting BD processing components and their users from the insider attacks, remains elusive. This paper proposes a general purpose AC scheme for distributed BD processing clusters.
{"title":"An Access Control scheme for Big Data processing","authors":"Vincent C. Hu, T. Grance, David F. Ferraiolo, D. R. Kuhn","doi":"10.4108/ICST.COLLABORATECOM.2014.257649","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257649","url":null,"abstract":"Access Control (AC) systems are among the most critical of network security components. A system's privacy and security controls are more likely to be compromised due to the misconfiguration of access control policies rather than the failure of cryptographic primitives or protocols. This problem becomes increasingly severe as software systems become more and more complex, such as Big Data (BD) processing systems, which are deployed to manage a large amount of sensitive information and resources organized into a sophisticated BD processing cluster. Basically, BD access control requires the collaboration among cooperating processing domains to be protected as computing environments that consist of computing units under distributed AC managements. Many BD architecture designs were proposed to address BD challenges; however, most of them were focused on the processing capabilities of the “three Vs” (Velocity, Volume, and Variety). Considerations for security in protecting BD are mostly ad hoc and patch efforts. Even with some inclusion of security in recent BD systems, a critical security component, AC (Authorization), for protecting BD processing components and their users from the insider attacks, remains elusive. This paper proposes a general purpose AC scheme for distributed BD processing clusters.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123588654","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257704
Teng Zhang, Ji Wu, Dingding Wang, Tao Li
Given a short query audio clip, the goal of audio retrieval is to automatically fetch all similar clips from a given audio database. Different from traditional audio similarity which is mainly based on priori knowledge of objective reality, this paper proposes to use a more subjective method to measure the perceptual similarity between audio clips. These perceptual features focus on users' personal experience, which can be very helpful for audio retrieval across different databases. In addition, indexing and audio matching methods are introduced to speed up the retrieval process. Experimental results on four different datasets are conducted to evaluate the effectiveness and efficiency of our proposed approaches..
{"title":"Audio retrieval based on perceptual similarity","authors":"Teng Zhang, Ji Wu, Dingding Wang, Tao Li","doi":"10.4108/ICST.COLLABORATECOM.2014.257704","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257704","url":null,"abstract":"Given a short query audio clip, the goal of audio retrieval is to automatically fetch all similar clips from a given audio database. Different from traditional audio similarity which is mainly based on priori knowledge of objective reality, this paper proposes to use a more subjective method to measure the perceptual similarity between audio clips. These perceptual features focus on users' personal experience, which can be very helpful for audio retrieval across different databases. In addition, indexing and audio matching methods are introduced to speed up the retrieval process. Experimental results on four different datasets are conducted to evaluate the effectiveness and efficiency of our proposed approaches..","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115018600","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257321
Youna Jung, R. Figueiredo, J. Fortes
The increasing use of online social networks (OSNs) in emergency situations shows us a promising future of human cooperation through OSNs. Despite this intense interest, a number of fundamental limitations still exist, such as lack of appropriate conceptual models and limitations on cooperation methods and shareable resources. To address existing limitations, we propose Whistle - a cooperation framework for OSN users which can dynamically organize an emergency community with nearby users and guarantee unrestricted cooperation and resource sharing by leveraging the Jitsi communicator and the SocialVPN. To test the feasibility and applicability of Whistle, we present an implemented prototype and demonstrate its applicability to an example use case.
{"title":"Location-based timely cooperation over social private network","authors":"Youna Jung, R. Figueiredo, J. Fortes","doi":"10.4108/ICST.COLLABORATECOM.2014.257321","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257321","url":null,"abstract":"The increasing use of online social networks (OSNs) in emergency situations shows us a promising future of human cooperation through OSNs. Despite this intense interest, a number of fundamental limitations still exist, such as lack of appropriate conceptual models and limitations on cooperation methods and shareable resources. To address existing limitations, we propose Whistle - a cooperation framework for OSN users which can dynamically organize an emergency community with nearby users and guarantee unrestricted cooperation and resource sharing by leveraging the Jitsi communicator and the SocialVPN. To test the feasibility and applicability of Whistle, we present an implemented prototype and demonstrate its applicability to an example use case.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122572737","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257553
A. Sheth, Pramod Anantharam, K. Thirunarayan
Physical objects with embedded sensors are increasingly being networked together using wireless and internet technologies to form Internet of Things (IoT). However, early applications that rely on IoT data fail to provide comprehensive situational awareness. This often requires combining physical (i.e., IoT) data with social data created by humans on the Web and increasingly on their mobile phones (i.e., citizen sensing) as well as other data such as structured open data and background knowledge available on the Web (i.e., cyber data and knowledge). In this paper, we explore how integration and analysis of multimodal physical-cybersocial data can support advanced applications and enrich human experience. Specifically, we illustrate the complementary role played by sensor and social data, often intermediated by other Web based data and knowledge, using real-world examples in the domain of situational awareness, traffic monitoring, and healthcare. We also show how semantic techniques and technologies support critical data interoperability needs, advanced computation capabilities including reasoning, and significantly enhance our ability to exploit growing amount of data from the proliferation of Internet of Things.
{"title":"Applications of multimodal physical (IoT), cyber and social data for reliable and actionable insights","authors":"A. Sheth, Pramod Anantharam, K. Thirunarayan","doi":"10.4108/ICST.COLLABORATECOM.2014.257553","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257553","url":null,"abstract":"Physical objects with embedded sensors are increasingly being networked together using wireless and internet technologies to form Internet of Things (IoT). However, early applications that rely on IoT data fail to provide comprehensive situational awareness. This often requires combining physical (i.e., IoT) data with social data created by humans on the Web and increasingly on their mobile phones (i.e., citizen sensing) as well as other data such as structured open data and background knowledge available on the Web (i.e., cyber data and knowledge). In this paper, we explore how integration and analysis of multimodal physical-cybersocial data can support advanced applications and enrich human experience. Specifically, we illustrate the complementary role played by sensor and social data, often intermediated by other Web based data and knowledge, using real-world examples in the domain of situational awareness, traffic monitoring, and healthcare. We also show how semantic techniques and technologies support critical data interoperability needs, advanced computation capabilities including reasoning, and significantly enhance our ability to exploit growing amount of data from the proliferation of Internet of Things.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114546080","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 : 2014-11-11DOI: 10.4108/eai.21-12-2015.150818
Alberto Castro-Hernández, K. Swigger, Mirna Patricia Ponce Flores
This paper describes a study that examines the effect of cohesion-based feedback on a team members' behaviors in a global software development project. Chat messages and forum posts were collected from a software development project involving students living in the US and Mexico. Half of the teams in the project received feedback in the form of a graphical representation that displayed the group's cohesion level, while the other teams received no feedback. The nature of the group interactions as well as the linguistic content of such interactions was then analyzed and compared. Results from this analysis show statistically significant differences between the feedback and non-feedback conditions. More specifically, cohesion-based feedback had a positive relation to a team's total message count, response rate, and individual cohesion score. In addition, the analysis of linguistic categories showed that the most salient categories observed were related to words about time and work. Although the feedback system did not appear to affect individual performance, the findings suggest that the cohesion measure defined in the study is positively correlated to the task cohesion construct and is also related to individual and team performance.
{"title":"Effects of cohesion-based feedback on the collaborations in global software development teams","authors":"Alberto Castro-Hernández, K. Swigger, Mirna Patricia Ponce Flores","doi":"10.4108/eai.21-12-2015.150818","DOIUrl":"https://doi.org/10.4108/eai.21-12-2015.150818","url":null,"abstract":"This paper describes a study that examines the effect of cohesion-based feedback on a team members' behaviors in a global software development project. Chat messages and forum posts were collected from a software development project involving students living in the US and Mexico. Half of the teams in the project received feedback in the form of a graphical representation that displayed the group's cohesion level, while the other teams received no feedback. The nature of the group interactions as well as the linguistic content of such interactions was then analyzed and compared. Results from this analysis show statistically significant differences between the feedback and non-feedback conditions. More specifically, cohesion-based feedback had a positive relation to a team's total message count, response rate, and individual cohesion score. In addition, the analysis of linguistic categories showed that the most salient categories observed were related to words about time and work. Although the feedback system did not appear to affect individual performance, the findings suggest that the cohesion measure defined in the study is positively correlated to the task cohesion construct and is also related to individual and team performance.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130393613","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257288
R. Liu, Akhil Kumar
There is a growing interest in socio-technical networks that encompass people, process and technology. They capture connections among technical artifacts and human resources. Existing studies have shown that social networks among resources that collaborate to work on a business process instance have an impact on the performance of the instance. Hence, the social network among the resources should be aligned with the technical work structure. Thus, we propose to identify empirically the specific features of social networks (e.g. size, closeness, density, etc.) that have the most significant impact on the performance of a process. Then, we can leverage these significant social network features to optimize dynamic assignment of tasks to resources for better performance. In general, organizations can use this two-part approach to evaluate their resource social networks and shape their resource networks to achieve socio-technical network alignment. We use real data from business processes in the IT incident management domain for this study to demonstrate our proposed methodology.
{"title":"Impact of socio-technical network on process performance","authors":"R. Liu, Akhil Kumar","doi":"10.4108/ICST.COLLABORATECOM.2014.257288","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257288","url":null,"abstract":"There is a growing interest in socio-technical networks that encompass people, process and technology. They capture connections among technical artifacts and human resources. Existing studies have shown that social networks among resources that collaborate to work on a business process instance have an impact on the performance of the instance. Hence, the social network among the resources should be aligned with the technical work structure. Thus, we propose to identify empirically the specific features of social networks (e.g. size, closeness, density, etc.) that have the most significant impact on the performance of a process. Then, we can leverage these significant social network features to optimize dynamic assignment of tasks to resources for better performance. In general, organizations can use this two-part approach to evaluate their resource social networks and shape their resource networks to achieve socio-technical network alignment. We use real data from business processes in the IT incident management domain for this study to demonstrate our proposed methodology.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125435139","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257591
Xin Jin, R. Krishnan, R. Sandhu
Cloud Infrastructure as a Service (IaaS), where traditional IT infrastructure resources such as compute, storage and networking are owned by a cloud service provider (CSP) and offered as on-demand virtual resources to customers (tenants), is the fastest maturing service model in cloud computing. The transformation of physical resources into virtual offers great flexibility to CSP customers including network based remote collaborative administration. This flexibility can be fully availed only if complemented by commensurately flexible access control to the customers remote IT resources by the customer's IT users. Since customer policies in this regard can vary greatly, the CSP needs a flexible model to accommodate diverse policy requirements. In this paper, we investigate attribute-based access control (ABAC) in cloud IaaS. In ABAC, access requests are evaluated based on the attributes of cloud tenant users and those of objects such as virtual machines, storage volumes, networks, etc. We investigate the access control models supported by commercial IaaS providers such as Amazon AWS and opensource OpenStack, as well as other models in the literature, which mostly use role-based access control (RBAC). We demonstrate their limitations and motivate the need for ABAC support to realize the true potential of IaaS. Building on prior published ABAC models we define a formal ABAC model suitable for IaaS. As proof-of-concept we implement this model in OpenStack, a widely-used open source cloud IaaS software platform. We discuss enforcement alternatives in this context and partially evaluate their performance.
{"title":"Role and attribute based collaborative administration of intra-tenant cloud IaaS","authors":"Xin Jin, R. Krishnan, R. Sandhu","doi":"10.4108/ICST.COLLABORATECOM.2014.257591","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257591","url":null,"abstract":"Cloud Infrastructure as a Service (IaaS), where traditional IT infrastructure resources such as compute, storage and networking are owned by a cloud service provider (CSP) and offered as on-demand virtual resources to customers (tenants), is the fastest maturing service model in cloud computing. The transformation of physical resources into virtual offers great flexibility to CSP customers including network based remote collaborative administration. This flexibility can be fully availed only if complemented by commensurately flexible access control to the customers remote IT resources by the customer's IT users. Since customer policies in this regard can vary greatly, the CSP needs a flexible model to accommodate diverse policy requirements. In this paper, we investigate attribute-based access control (ABAC) in cloud IaaS. In ABAC, access requests are evaluated based on the attributes of cloud tenant users and those of objects such as virtual machines, storage volumes, networks, etc. We investigate the access control models supported by commercial IaaS providers such as Amazon AWS and opensource OpenStack, as well as other models in the literature, which mostly use role-based access control (RBAC). We demonstrate their limitations and motivate the need for ABAC support to realize the true potential of IaaS. Building on prior published ABAC models we define a formal ABAC model suitable for IaaS. As proof-of-concept we implement this model in OpenStack, a widely-used open source cloud IaaS software platform. We discuss enforcement alternatives in this context and partially evaluate their performance.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130440140","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257266
P. Dewan
Group communication abstractions provide application-level multicasting to communicate information among distributed processes. A variety of such abstractions have been provided to implement synchronous collaborative applications but they do not allow control over the multicast of information to the selected group of processes. We have developed a new abstraction that overcomes this limitation. It defines a two-level grouping of distributed processes, with one level defining the users interacting with a specific collaborative application, and the other defining the set of collaborative applications a set of users is sharing simultaneously to perform some collaborative task. It allows information to be sent directly to the receiving processes or through a centralized relayer. In either case, programmer-choosable and replaceable send and receive filters provide consistency guarantees. The abstraction provides message passing rather than remote procedure calls, and supports asynchronous sending and receiving of messages. It is designed to support both centralized and replicated architectures. The abstraction has been implemented on top of the Java Remote Method Invocation layer and has been used to implement a broad range of collaboration functions.
{"title":"Programmer-controlled application-level multicast","authors":"P. Dewan","doi":"10.4108/ICST.COLLABORATECOM.2014.257266","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257266","url":null,"abstract":"Group communication abstractions provide application-level multicasting to communicate information among distributed processes. A variety of such abstractions have been provided to implement synchronous collaborative applications but they do not allow control over the multicast of information to the selected group of processes. We have developed a new abstraction that overcomes this limitation. It defines a two-level grouping of distributed processes, with one level defining the users interacting with a specific collaborative application, and the other defining the set of collaborative applications a set of users is sharing simultaneously to perform some collaborative task. It allows information to be sent directly to the receiving processes or through a centralized relayer. In either case, programmer-choosable and replaceable send and receive filters provide consistency guarantees. The abstraction provides message passing rather than remote procedure calls, and supports asynchronous sending and receiving of messages. It is designed to support both centralized and replicated architectures. The abstraction has been implemented on top of the Java Remote Method Invocation layer and has been used to implement a broad range of collaboration functions.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134008292","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257329
Andrew Ghobrial, Jacob W. Bartel, P. Dewan
Users' contacts often need to be grouped into equivalence classes for various purposes such as easily sending a message to all members of the group. Several approaches have been recently developed to make such predictions (a) for both ephemeral and persistent groups (b) in both email and social networks systems. However, no research has attempted to compare these approaches or compose them by using ideas of one in another. We have taken a step in this direction. We have developed and compared multiple approaches to predicting persistent contact groups in email. These approaches compose an algorithm that generates friend lists in Facebook from a social graph with different techniques for generating the social graph. One of these techniques is based on a scoring algorithm used by Google to predict ephemeral groups incrementally. To compare the approaches we ran a user study involving 19 participants and used two simple metrics that calculated the average percentage difference between a predicted group and the group of addresses in a future message. The evaluation showed that using the Google score was the best approach though it offered very small improvements over all but one of the simpler methods.
{"title":"Towards composable prediction of contact groups","authors":"Andrew Ghobrial, Jacob W. Bartel, P. Dewan","doi":"10.4108/ICST.COLLABORATECOM.2014.257329","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257329","url":null,"abstract":"Users' contacts often need to be grouped into equivalence classes for various purposes such as easily sending a message to all members of the group. Several approaches have been recently developed to make such predictions (a) for both ephemeral and persistent groups (b) in both email and social networks systems. However, no research has attempted to compare these approaches or compose them by using ideas of one in another. We have taken a step in this direction. We have developed and compared multiple approaches to predicting persistent contact groups in email. These approaches compose an algorithm that generates friend lists in Facebook from a social graph with different techniques for generating the social graph. One of these techniques is based on a scoring algorithm used by Google to predict ephemeral groups incrementally. To compare the approaches we ran a user study involving 19 participants and used two simple metrics that calculated the average percentage difference between a predicted group and the group of addresses in a future message. The evaluation showed that using the Google score was the best approach though it offered very small improvements over all but one of the simpler methods.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129082371","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257382
Makbule Gülçin Özsoy, Faruk Polat, R. Alhajj
Social networks, personal blog pages, on-line transaction web-sites, expertise web pages and location based social networks provide an attractive platform for millions of users to share opinions, comments, ratings, etc. Having this kind of diverse and comprehensive information leads to difficulties for users to reach the most appropriate and reliable conclusions. Recommendation systems form one of the solutions to deal with the information overload problem by providing personalized services. Using spatial, temporal and social information on recommender systems is a recent trend that increases the performance. Also, taking into account more than one criterion can improve the performance of the recommender systems. In this paper, a location and social network aware recommender system enhanced with multi objective filtering is proposed and described. The results show that the proposed method reaches high coverage while preserving precision. Besides, the proposed method is not affected by the range of ratings and provides persistent results in different settings.
{"title":"Multi-objective optimization based location and social network aware recommendation","authors":"Makbule Gülçin Özsoy, Faruk Polat, R. Alhajj","doi":"10.4108/ICST.COLLABORATECOM.2014.257382","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257382","url":null,"abstract":"Social networks, personal blog pages, on-line transaction web-sites, expertise web pages and location based social networks provide an attractive platform for millions of users to share opinions, comments, ratings, etc. Having this kind of diverse and comprehensive information leads to difficulties for users to reach the most appropriate and reliable conclusions. Recommendation systems form one of the solutions to deal with the information overload problem by providing personalized services. Using spatial, temporal and social information on recommender systems is a recent trend that increases the performance. Also, taking into account more than one criterion can improve the performance of the recommender systems. In this paper, a location and social network aware recommender system enhanced with multi objective filtering is proposed and described. The results show that the proposed method reaches high coverage while preserving precision. Besides, the proposed method is not affected by the range of ratings and provides persistent results in different settings.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131460137","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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