Community discovery is a popular research problem in the realm of complex network analysis and many methods have been proposed to solve it. However, most of the existing methods only consider the usage of links information and ignore tags information of complex networks. As a result, the quality of their discovered communities is often poor owing to the sparse and noisy data existing in links information. Actually, both links and tags contain noisy but complementary information with each other. In this paper, we propose a multi-view clustering method for community discovery, which is based on multi-view Nonnegative Matrix Factorization (NMF) model and can provide a unified framework to integrate links and tags information. Its key idea is to build a joint NMF process with the constraint that pushes community indicator matrices of links view and tags view towards a common consensus matrix, which can uncover the common latent community structure shared by links view and tags view. Under the optimization framework of multiplicative update rules, we devise the corresponding community discovery algorithm, which can be used to obtain higher quality communities. We conduct extensive experiments on several real datasets and the results demonstrate the effectiveness of our method.
{"title":"A Multi-View Clustering Method for Community Discovery Integrating Links and Tags","authors":"Chaobo He, Xiang Fei, Hanchao Li, Yong Tang, Hai Liu, Qimai Chen","doi":"10.1109/ICEBE.2017.14","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.14","url":null,"abstract":"Community discovery is a popular research problem in the realm of complex network analysis and many methods have been proposed to solve it. However, most of the existing methods only consider the usage of links information and ignore tags information of complex networks. As a result, the quality of their discovered communities is often poor owing to the sparse and noisy data existing in links information. Actually, both links and tags contain noisy but complementary information with each other. In this paper, we propose a multi-view clustering method for community discovery, which is based on multi-view Nonnegative Matrix Factorization (NMF) model and can provide a unified framework to integrate links and tags information. Its key idea is to build a joint NMF process with the constraint that pushes community indicator matrices of links view and tags view towards a common consensus matrix, which can uncover the common latent community structure shared by links view and tags view. Under the optimization framework of multiplicative update rules, we devise the corresponding community discovery algorithm, which can be used to obtain higher quality communities. We conduct extensive experiments on several real datasets and the results demonstrate the effectiveness of our method.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121991731","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}
Customer experience management (CEM) denotes a set of practices, processes, and tools that aim to personalize a customer's interactions with a company around the customer's needs and desires. This personalization depends on the purchase scenario at hand, and on how much a company knows about its customers. In turn, the purchase scenario depends, among other things, on the complexity of the product or service being offered (e.g., a carton of milk versus a house), and the complex set of motivations that can trigger a purchasing process. E-commerce software tool vendors need to provide the building blocks that enable retailers to configure and develop CEM functionalities that take into account these factors. In earlier work, we proposed such building blocks within the context of a CEM development framework that relies on a cognitive modeling of the purchasing process and identifies the touch points between seller and buyer and relevant influence factors. We envision a CEM scenario specification tool that enables business analysts to specify their purchase scenario, from which we generate data structures and algorithms to implement CEM functionalities by instantiating the framework. The framework is embodied in a set of ontologies and algorithm templates that can be instantiated with the specification parameters. In this paper, we present the principles behind our approach, and a prototype CEM scenario specification tool. We illustrate the tool with a moderately complex purchasing scenario, to validate the underlying theory, and to explore implementation strategies
{"title":"A Development Framework for Customer Experience Management Applications: Principles and Case Study","authors":"Imen Benzarti, H. Mili","doi":"10.1109/ICEBE.2017.27","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.27","url":null,"abstract":"Customer experience management (CEM) denotes a set of practices, processes, and tools that aim to personalize a customer's interactions with a company around the customer's needs and desires. This personalization depends on the purchase scenario at hand, and on how much a company knows about its customers. In turn, the purchase scenario depends, among other things, on the complexity of the product or service being offered (e.g., a carton of milk versus a house), and the complex set of motivations that can trigger a purchasing process. E-commerce software tool vendors need to provide the building blocks that enable retailers to configure and develop CEM functionalities that take into account these factors. In earlier work, we proposed such building blocks within the context of a CEM development framework that relies on a cognitive modeling of the purchasing process and identifies the touch points between seller and buyer and relevant influence factors. We envision a CEM scenario specification tool that enables business analysts to specify their purchase scenario, from which we generate data structures and algorithms to implement CEM functionalities by instantiating the framework. The framework is embodied in a set of ontologies and algorithm templates that can be instantiated with the specification parameters. In this paper, we present the principles behind our approach, and a prototype CEM scenario specification tool. We illustrate the tool with a moderately complex purchasing scenario, to validate the underlying theory, and to explore implementation strategies","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116186437","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}
Service-oriented architecture (SOA) is a fast emerging architectural style to implement dynamic e-business solutions. It has been widely adopted by modern organizations to design and implement information systems that support their business processes. Benefits of using SOA include reuse, model-driven implementation, service composition, better integration through standardization, and business process management. This paper aims to bridge the gap between business processes and SOA-based software applications that support them. It proposes a novel model-driven development method that generates SOA services from the specification of business processes expressed in BPMN. We present the principles underlying our approach and describe the state of an ongoing implementation.
{"title":"A Model-Driven Service Specification Approach from BPMN Models","authors":"Redouane Blal, Abderrahmane Leshob","doi":"10.1109/ICEBE.2017.28","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.28","url":null,"abstract":"Service-oriented architecture (SOA) is a fast emerging architectural style to implement dynamic e-business solutions. It has been widely adopted by modern organizations to design and implement information systems that support their business processes. Benefits of using SOA include reuse, model-driven implementation, service composition, better integration through standardization, and business process management. This paper aims to bridge the gap between business processes and SOA-based software applications that support them. It proposes a novel model-driven development method that generates SOA services from the specification of business processes expressed in BPMN. We present the principles underlying our approach and describe the state of an ongoing implementation.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130791983","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}
Hanchao Li, Zhouhemu Tang, Xiang Fei, K. Chao, Ming Yang, Chaobo He
Music Recognition System has becoming popular these days. They are based on either audio or symbolic method, which compares the user's query with the existing music database. The investigation has shown that the audio-based method system is good for storing sound waves. However, the limitation is to illustrate the content of the music. The symbolic-based method system doing well in representing the content of the music, including recognize similar patterns, but limitation in creating the music, e.g., Electronic Music. We also carried some detailed tests based on the previous Neural Network systems, with Music Definition Language (MDL) and Music Manipulation Language (MML). Furthermore, we have tested our previous classification system with new melody query, to see how it can handle with external music pieces, which beyond the self-testing from a self-organising-map. The conclusion is that our system can classify variation type, including key variations, expansion and reduction, which is better than those existing Music Information Retrieval (MIR) systems.
{"title":"A Survey of Audio MIR Systems, Symbolic MIR Systems and a Music Definition Language Demo-System","authors":"Hanchao Li, Zhouhemu Tang, Xiang Fei, K. Chao, Ming Yang, Chaobo He","doi":"10.1109/ICEBE.2017.51","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.51","url":null,"abstract":"Music Recognition System has becoming popular these days. They are based on either audio or symbolic method, which compares the user's query with the existing music database. The investigation has shown that the audio-based method system is good for storing sound waves. However, the limitation is to illustrate the content of the music. The symbolic-based method system doing well in representing the content of the music, including recognize similar patterns, but limitation in creating the music, e.g., Electronic Music. We also carried some detailed tests based on the previous Neural Network systems, with Music Definition Language (MDL) and Music Manipulation Language (MML). Furthermore, we have tested our previous classification system with new melody query, to see how it can handle with external music pieces, which beyond the self-testing from a self-organising-map. The conclusion is that our system can classify variation type, including key variations, expansion and reduction, which is better than those existing Music Information Retrieval (MIR) systems.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131006986","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}
Jinyu Zhang, Yao Zhou, W. Tang, Han Gu, Jiaqi Yan, Huaiqing Wang
The tourism industry has been radically transformed by Internet-related technologies. Today, online travel agencies (OTAs) have replaced traditional travel agencies offering customers online booking services related to their travels. However, the current OTAs model is limited to the "search, compare, and book" business process. For a traveler, it can be time consuming and labor intensive to look for a suitable choice across a large number of hotels online. On the other hand, hotel service providers cannot adaptively adjust their marketing strategies in real time according to potential customers' requirements. There is a lack of an effective communication mechanism to automatically matching requirements and interests between customers and service providers. In this paper, we propose to improve the current OTAs model with an agent-mediated tendering mechanism. We elicit the requirements of both hotel customers and service providers with the agent oriented modeling language i*. Based on such functional and non-functional requirement analysis, an agent-based tendering system is built to help hotel service provider to proactively adapt their room price and help traveler to automatically suggest suitable hotel choices. We find that such agent-mediated tendering mechanism can pareto-improve the OTAs model in terms of the cost and benefit of both the customer and the service provider.
{"title":"An Agent-Mediated Tendering Mechanism for Intelligent Hotel Reservation","authors":"Jinyu Zhang, Yao Zhou, W. Tang, Han Gu, Jiaqi Yan, Huaiqing Wang","doi":"10.1109/ICEBE.2017.56","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.56","url":null,"abstract":"The tourism industry has been radically transformed by Internet-related technologies. Today, online travel agencies (OTAs) have replaced traditional travel agencies offering customers online booking services related to their travels. However, the current OTAs model is limited to the \"search, compare, and book\" business process. For a traveler, it can be time consuming and labor intensive to look for a suitable choice across a large number of hotels online. On the other hand, hotel service providers cannot adaptively adjust their marketing strategies in real time according to potential customers' requirements. There is a lack of an effective communication mechanism to automatically matching requirements and interests between customers and service providers. In this paper, we propose to improve the current OTAs model with an agent-mediated tendering mechanism. We elicit the requirements of both hotel customers and service providers with the agent oriented modeling language i*. Based on such functional and non-functional requirement analysis, an agent-based tendering system is built to help hotel service provider to proactively adapt their room price and help traveler to automatically suggest suitable hotel choices. We find that such agent-mediated tendering mechanism can pareto-improve the OTAs model in terms of the cost and benefit of both the customer and the service provider.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129367109","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}
This paper proposes and implements a parallel scheme of FP-growth algorithm and implements this parallel algorithm (PFP-growth algorithm). Experimental results show that, compared with FP-growth algorithm, PFP-growth algorithm is more efficient, and the larger the data set is, the lower the support threshold is, the more remarkable the speedup is.
{"title":"A Parallel FP-Growth Algorithm Based on GPU","authors":"Hao Jiang, He Meng","doi":"10.1109/ICEBE.2017.24","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.24","url":null,"abstract":"This paper proposes and implements a parallel scheme of FP-growth algorithm and implements this parallel algorithm (PFP-growth algorithm). Experimental results show that, compared with FP-growth algorithm, PFP-growth algorithm is more efficient, and the larger the data set is, the lower the support threshold is, the more remarkable the speedup is.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125381395","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}
Spark SQL lets spark programmers query structured data inside Spark programs using SQL statements. It provides spark programmers with great convenience to leverage the benefits of relational processing, and its internal RDD distributed processing also accelerates query on large data sets. However, Spark SQL is not designed for long-run services and its built-in data source would load data from storage system, such as HDFS and local file system, in each table scan without cache mechanism. Although users could keep data in memory using "cache" command explicitly, the data cached in memory is coarse grained. In this paper, we present an indexing structure which is a pluggable component of Spark SQL based on Apache Spark. Compared with Spark SQL, it has some additional advantages. Firstly, it allows users to create index of structured data to be processed, which speeds up the query performance greatly. Secondly, it enables programmers to load fine-grained data file of structured data into memory, which is flexible to load "hot data" into memory and to evict "cold data" out of memory.
{"title":"Indexing for Large Scale Data Querying Based on Spark SQL","authors":"Yi Cui, Guoqiang Li, Hao Cheng, Daoyuan Wang","doi":"10.1109/ICEBE.2017.25","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.25","url":null,"abstract":"Spark SQL lets spark programmers query structured data inside Spark programs using SQL statements. It provides spark programmers with great convenience to leverage the benefits of relational processing, and its internal RDD distributed processing also accelerates query on large data sets. However, Spark SQL is not designed for long-run services and its built-in data source would load data from storage system, such as HDFS and local file system, in each table scan without cache mechanism. Although users could keep data in memory using \"cache\" command explicitly, the data cached in memory is coarse grained. In this paper, we present an indexing structure which is a pluggable component of Spark SQL based on Apache Spark. Compared with Spark SQL, it has some additional advantages. Firstly, it allows users to create index of structured data to be processed, which speeds up the query performance greatly. Secondly, it enables programmers to load fine-grained data file of structured data into memory, which is flexible to load \"hot data\" into memory and to evict \"cold data\" out of memory.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115026365","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}
Currently, numerous small and medium-sized enterprises and the local governments have been in the preliminary stage to develop the public opinion monitoring, and such monitoring task of these aspects is mainly realized artificially. For this reason, a reliable and high-efficient internet public opinion monitoring is urgently required to assist the monitoring of the public opinion. The web crawler technology and the search engine are adopted in this paper hereof to establish a public opinion pre-warning analysis platform being well geared into the requirement of the majority of the small and medium-sized enterprises and local governments. This platform shall set forth different fetching strategies in accordance with the different structures from various types of public opinion information, and the online public opinion data shall be collected by the commonly adopted web crawler. In the meantime, the suitable word segmentation shall be adopted, and the full-text retrieval engine shall be applied to fulfill the searching and index of the public opinion information. Eventually, a vertical searching method is designed in this paper, accordingly realizing the commonly used public opinion monitoring function and the topic monitoring function. Such method can be well adopted in the majority of the small and medium-sized enterprises and the institutions of local government to monitor the public opinion.
{"title":"Analysis and Design of Public Opinion Pre-Warning Analysis Platform Based on Vertical Search Engine","authors":"Kun Liu, Kun Ma, Zonglin Yue","doi":"10.1109/ICEBE.2017.53","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.53","url":null,"abstract":"Currently, numerous small and medium-sized enterprises and the local governments have been in the preliminary stage to develop the public opinion monitoring, and such monitoring task of these aspects is mainly realized artificially. For this reason, a reliable and high-efficient internet public opinion monitoring is urgently required to assist the monitoring of the public opinion. The web crawler technology and the search engine are adopted in this paper hereof to establish a public opinion pre-warning analysis platform being well geared into the requirement of the majority of the small and medium-sized enterprises and local governments. This platform shall set forth different fetching strategies in accordance with the different structures from various types of public opinion information, and the online public opinion data shall be collected by the commonly adopted web crawler. In the meantime, the suitable word segmentation shall be adopted, and the full-text retrieval engine shall be applied to fulfill the searching and index of the public opinion information. Eventually, a vertical searching method is designed in this paper, accordingly realizing the commonly used public opinion monitoring function and the topic monitoring function. Such method can be well adopted in the majority of the small and medium-sized enterprises and the institutions of local government to monitor the public opinion.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134515989","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}
Shang-Pin Ma, Peng-Zhong Chen, Wen-Tin Lee, Zhi-Wei Lu
Nowadays, open data has become more and more popular and is widely used in a variety of service domains. However, in Taiwan, most open datasets are still separate while linked open data (LOD) is still lacking. Without LOD, application developers are difficult to locate and combine appropriate open datasets to create innovative applications. Therefore, to facilitate the consumption and the spreading of open data in Taiwan, we propose a new data query language, referred to as LODQL (Linked Open Data Query Language), to allow the definition of rules for building LOD by data experts and the consumption of LOD via RESTful services by application developers. We designed the LODE (LODQL Engine) to parse the LODQL, build LOD in RDF (Resource Description Framework) according to LODQL, and generate the corresponding RESTful services that extract required LOD based on the user query. LODE is also able to perform data visualization to show relevance of open datasets and relations between open data items. The developed system implementation and the evaluation experiments fully demonstrate that the feasibility and effectiveness of LODQL and LODE.
{"title":"LODQL: A Language for Creation, Query, and Service Generation of Linked Open Data","authors":"Shang-Pin Ma, Peng-Zhong Chen, Wen-Tin Lee, Zhi-Wei Lu","doi":"10.1109/ICEBE.2017.16","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.16","url":null,"abstract":"Nowadays, open data has become more and more popular and is widely used in a variety of service domains. However, in Taiwan, most open datasets are still separate while linked open data (LOD) is still lacking. Without LOD, application developers are difficult to locate and combine appropriate open datasets to create innovative applications. Therefore, to facilitate the consumption and the spreading of open data in Taiwan, we propose a new data query language, referred to as LODQL (Linked Open Data Query Language), to allow the definition of rules for building LOD by data experts and the consumption of LOD via RESTful services by application developers. We designed the LODE (LODQL Engine) to parse the LODQL, build LOD in RDF (Resource Description Framework) according to LODQL, and generate the corresponding RESTful services that extract required LOD based on the user query. LODE is also able to perform data visualization to show relevance of open datasets and relations between open data items. The developed system implementation and the evaluation experiments fully demonstrate that the feasibility and effectiveness of LODQL and LODE.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124854539","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}
Jiawei Du, Hongming Cai, Lihong Jiang, Chengxi Huang
Precise and continuous service management is needed in today's mobile application development, with consideration of Continuous Delivery. This paper presents a framework to introduce sustained process discovery to service management for mobile APPs. Leveraging service logs accumulated at runtime, this framework bridges the gap between traditional process mining techniques and mobile APPs, demonstrating a log conversion method to deduce the missing case identifiers and gathering multiple versions of the process model, providing rich information for user behavior analysis, auto scaling of computing resources, etc. A case study is conducted based on a Chinese m-health APP to show our approach can provide comprehensive supports in many application scenarios. Experimental results demonstrate that our framework successfully handles with the incompleteness of original service logs by correctly deducing missing case identifiers in most cases.
{"title":"Methods of Introducing Continuous Process Mining to Service Management for Mobile APPs","authors":"Jiawei Du, Hongming Cai, Lihong Jiang, Chengxi Huang","doi":"10.1109/ICEBE.2017.29","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.29","url":null,"abstract":"Precise and continuous service management is needed in today's mobile application development, with consideration of Continuous Delivery. This paper presents a framework to introduce sustained process discovery to service management for mobile APPs. Leveraging service logs accumulated at runtime, this framework bridges the gap between traditional process mining techniques and mobile APPs, demonstrating a log conversion method to deduce the missing case identifiers and gathering multiple versions of the process model, providing rich information for user behavior analysis, auto scaling of computing resources, etc. A case study is conducted based on a Chinese m-health APP to show our approach can provide comprehensive supports in many application scenarios. Experimental results demonstrate that our framework successfully handles with the incompleteness of original service logs by correctly deducing missing case identifiers in most cases.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127790588","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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