Traveling companions are object groups that move together in a period of time. To quickly identify traveling companions from a special kind of streaming traffic data, called Automatic Number Plate Recognition (ANPR) data, this paper proposes a framework and several algorithms to discover companion vehicles. Compared to related approaches, our main contribution is that the framework can instantly detect suspicious companion vehicles with their probabilities when they pass through monitoring cameras. Our framework can be used in many time-sensitive scenarios like taking surveillance on the suspect trackers for specific vehicles. Experiments show that our approach can process streaming ANPR data directly and discover the companion vehicles in nearly real time.
{"title":"Instant Traveling Companion Discovery Based on Traffic-Monitoring Streaming Data","authors":"Xiongbin Wang, Chen Liu, Meiling Zhu","doi":"10.1109/WISA.2016.27","DOIUrl":"https://doi.org/10.1109/WISA.2016.27","url":null,"abstract":"Traveling companions are object groups that move together in a period of time. To quickly identify traveling companions from a special kind of streaming traffic data, called Automatic Number Plate Recognition (ANPR) data, this paper proposes a framework and several algorithms to discover companion vehicles. Compared to related approaches, our main contribution is that the framework can instantly detect suspicious companion vehicles with their probabilities when they pass through monitoring cameras. Our framework can be used in many time-sensitive scenarios like taking surveillance on the suspect trackers for specific vehicles. Experiments show that our approach can process streaming ANPR data directly and discover the companion vehicles in nearly real time.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122590040","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}
Zhibin Zhao, Yanfeng Jia, Lan Yao, Ge Yu, Xiangyang Li
A hash tag is an important metadata in micro blogs and used to mark topics or index messages. However, statistics show hash tags are absent from most of the micro blogs. It poses great challenges to the retrieve and analysis of these tagless micro blogs. In this paper, we summarize the similarity between micro blogs and short message news, and then propose an algorithm named 5WTAG for detecting micro blog topics based on 5W (When, Where, Who, What, how) model. Since 5W attributes are the core components in event description, it is guaranteed theoretically that 5WTAG can extract the semantics of the micro blogs properly. We introduce the detailed procedure of 5WTAG in this paper including the candidate hash tag construction and recommendation computation. Finally, we verify the semantical correctness of the candidate hash tags as well as the effectiveness of recommendation computation using the real data set from Sina Weibo.
{"title":"5WTAG: Detecting the Topics of Chinese Microblogs Based on 5W Model","authors":"Zhibin Zhao, Yanfeng Jia, Lan Yao, Ge Yu, Xiangyang Li","doi":"10.1109/WISA.2013.52","DOIUrl":"https://doi.org/10.1109/WISA.2013.52","url":null,"abstract":"A hash tag is an important metadata in micro blogs and used to mark topics or index messages. However, statistics show hash tags are absent from most of the micro blogs. It poses great challenges to the retrieve and analysis of these tagless micro blogs. In this paper, we summarize the similarity between micro blogs and short message news, and then propose an algorithm named 5WTAG for detecting micro blog topics based on 5W (When, Where, Who, What, how) model. Since 5W attributes are the core components in event description, it is guaranteed theoretically that 5WTAG can extract the semantics of the micro blogs properly. We introduce the detailed procedure of 5WTAG in this paper including the candidate hash tag construction and recommendation computation. Finally, we verify the semantical correctness of the candidate hash tags as well as the effectiveness of recommendation computation using the real data set from Sina Weibo.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117324243","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}
Dengchao He, Wenning Hao, Wenyan Gan, Gang Chen, Dawei Jin
In this paper, an improved decision tree algorithm based on dispersion measure of attribute information was proposed, which combined information gain and dispersion of attribute information as an evaluation criterion of attribute selection in order to overcome the deficiency that ID3 decision tree algorithm leaned to the multi-value attribute. From results of the experiment, it can be demonstrated that the proposed algorithm could over the deficiency of leaning to the multi-value attribute, and has good performance on classification.
{"title":"A Decision Tree Algorithm Based on Dispersion Measure of Attribute Information","authors":"Dengchao He, Wenning Hao, Wenyan Gan, Gang Chen, Dawei Jin","doi":"10.1109/WISA.2013.25","DOIUrl":"https://doi.org/10.1109/WISA.2013.25","url":null,"abstract":"In this paper, an improved decision tree algorithm based on dispersion measure of attribute information was proposed, which combined information gain and dispersion of attribute information as an evaluation criterion of attribute selection in order to overcome the deficiency that ID3 decision tree algorithm leaned to the multi-value attribute. From results of the experiment, it can be demonstrated that the proposed algorithm could over the deficiency of leaning to the multi-value attribute, and has good performance on classification.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117175314","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}
Kaiqiang Zhang, Li Kang, Qing Wang, Hong Chen, Dehai Zhu, Xinrong Cheng
Knowledge representation is a strategy which represents the human knowledge as the data structure and the system control structure that can be processed by computer. As a knowledge representation method, domain ontology can represent the specific knowledge of a specific area. In the design of skill knowledge base, it will involve a lot of corresponding events to skills, and the knowledge contained in the event is dynamic. Dynamic knowledge can't be fully expressed in a static concept, so skill knowledge base needs both static knowledge in the field of domain ontology and dynamic knowledge in the field of event ontology. So, taking building skill knowledge base for rural migrant workers as the application background, based on analyzing the ontology structure and application model, this paper proposes a construction method of skill knowledge base with the combination of domain ontology and event ontology, which realizes the ontology database storage. Experimental results show that when we apply the knowledge base to knowledge training rules and knowledge map, we can better recommend the challenge missions of application games.
{"title":"Ontology-Based Skills Knowledge Base Construction Method and Its Application in Educational Games","authors":"Kaiqiang Zhang, Li Kang, Qing Wang, Hong Chen, Dehai Zhu, Xinrong Cheng","doi":"10.1109/WISA.2014.52","DOIUrl":"https://doi.org/10.1109/WISA.2014.52","url":null,"abstract":"Knowledge representation is a strategy which represents the human knowledge as the data structure and the system control structure that can be processed by computer. As a knowledge representation method, domain ontology can represent the specific knowledge of a specific area. In the design of skill knowledge base, it will involve a lot of corresponding events to skills, and the knowledge contained in the event is dynamic. Dynamic knowledge can't be fully expressed in a static concept, so skill knowledge base needs both static knowledge in the field of domain ontology and dynamic knowledge in the field of event ontology. So, taking building skill knowledge base for rural migrant workers as the application background, based on analyzing the ontology structure and application model, this paper proposes a construction method of skill knowledge base with the combination of domain ontology and event ontology, which realizes the ontology database storage. Experimental results show that when we apply the knowledge base to knowledge training rules and knowledge map, we can better recommend the challenge missions of application games.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114436772","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}
Similarity has been widely used in finding similar objects among complex and large scale information networks. Most of the current similarity comparison methods are the distance-based, link-based, neighborhood based similarity or the reference based similarity, and so on. They mainly make the similarity comparison with some kind of metrics but are lack of the measurement of the objects' semantics. The complex semantics and reactions within information networks require the metrics of wider aspects. In this paper, we integrate the attribute-based semantics with the role similarity and propose a unified attribute based role similarity measure method (UARS). It tries to resolve the deficiency of the current methods and achieve attribute based semantic similarity of objects besides the structural or the automorphism similarity of the original role based similarity. The development, computation and properties of UARS are given in detail. The experiment results are also showed to demonstrate the effectiveness and superiority of UARS.
{"title":"A Unified Attribute Based Role Similarity Measure in Information Networks","authors":"Wandan Zeng, D. Ma, Juyang Zhang","doi":"10.1109/WISA.2014.59","DOIUrl":"https://doi.org/10.1109/WISA.2014.59","url":null,"abstract":"Similarity has been widely used in finding similar objects among complex and large scale information networks. Most of the current similarity comparison methods are the distance-based, link-based, neighborhood based similarity or the reference based similarity, and so on. They mainly make the similarity comparison with some kind of metrics but are lack of the measurement of the objects' semantics. The complex semantics and reactions within information networks require the metrics of wider aspects. In this paper, we integrate the attribute-based semantics with the role similarity and propose a unified attribute based role similarity measure method (UARS). It tries to resolve the deficiency of the current methods and achieve attribute based semantic similarity of objects besides the structural or the automorphism similarity of the original role based similarity. The development, computation and properties of UARS are given in detail. The experiment results are also showed to demonstrate the effectiveness and superiority of UARS.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122983107","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}
Recently, Point of Interest Recommendation is widely used in LBS navigation systems. It makes use of the real-time GPS locations of users as well as their preferences to recommend POIs that mostly match these preferences and the paths leading to the POIs. Previous studies are focused on the following two issues: (1) Similarity measurement between POIs and the user preferences, and (2) Optimum path selection from the user location to the recommended POIs. However in most scenarios, users need not only some isolated POIs, but a combination of several POIs that covers the user preferences as well as the paths connecting them. Essentially, it is the schedule planning problem. Schedule planning is usually with strict time limits, and equivalent to Generalized Traveling Sales Man Problem (GTSP) which was proved a NP-hard problem. This imposes great challenge to its solution. In this paper, we formalize the problem of Schedule Planning with strict Time Constraint (SPwTC). Especially, we wrap the static paths between POIs into route activities, thus a globally unified model of user activity can be defined. Based on Genetic Algorithm, we propose the schedule recommendation algorithm to generate candidate route plans. Subsequently, we propose the recommendation function for sorting the recommended schedule plans so as to make the recommended result more in line with user expectation. At the end of this paper, we verify the efficiency of the algorithm as well as its rationality of the recommended result with real road network data.
{"title":"An Algorithm for LBS-based Schedule Recommendation with Time Constraint","authors":"Yuxiang Cai, Zhibin Zhao, Lan Yao, Y. Bao","doi":"10.1109/WISA.2015.17","DOIUrl":"https://doi.org/10.1109/WISA.2015.17","url":null,"abstract":"Recently, Point of Interest Recommendation is widely used in LBS navigation systems. It makes use of the real-time GPS locations of users as well as their preferences to recommend POIs that mostly match these preferences and the paths leading to the POIs. Previous studies are focused on the following two issues: (1) Similarity measurement between POIs and the user preferences, and (2) Optimum path selection from the user location to the recommended POIs. However in most scenarios, users need not only some isolated POIs, but a combination of several POIs that covers the user preferences as well as the paths connecting them. Essentially, it is the schedule planning problem. Schedule planning is usually with strict time limits, and equivalent to Generalized Traveling Sales Man Problem (GTSP) which was proved a NP-hard problem. This imposes great challenge to its solution. In this paper, we formalize the problem of Schedule Planning with strict Time Constraint (SPwTC). Especially, we wrap the static paths between POIs into route activities, thus a globally unified model of user activity can be defined. Based on Genetic Algorithm, we propose the schedule recommendation algorithm to generate candidate route plans. Subsequently, we propose the recommendation function for sorting the recommended schedule plans so as to make the recommended result more in line with user expectation. At the end of this paper, we verify the efficiency of the algorithm as well as its rationality of the recommended result with real road network data.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125032554","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}
Frequent item sets mining algorithms in uncertain data streams almost base on the expected frequent item sets. Compared to probabilistic frequent item sets, it can't reflect the confidence of item sets. We propose the algorithm based on probabilistic frequent item sets mining in uncertain data streams. The algorithm processes one basic sliding window every time, and the mining results are stored in the Probabilistic Frequent Tree. When the window sliding, it dynamically updates Probabilistic Frequent Tree to delete old data and add new data. Theoretical analysis and experiments show that the algorithm is effective.
{"title":"Mining of Probabilistic Frequent Itemsets over Uncertain Data Streams","authors":"Lixin Liu, Xiaolin Zhang, Huanxiang Zhang","doi":"10.1109/WISA.2014.49","DOIUrl":"https://doi.org/10.1109/WISA.2014.49","url":null,"abstract":"Frequent item sets mining algorithms in uncertain data streams almost base on the expected frequent item sets. Compared to probabilistic frequent item sets, it can't reflect the confidence of item sets. We propose the algorithm based on probabilistic frequent item sets mining in uncertain data streams. The algorithm processes one basic sliding window every time, and the mining results are stored in the Probabilistic Frequent Tree. When the window sliding, it dynamically updates Probabilistic Frequent Tree to delete old data and add new data. Theoretical analysis and experiments show that the algorithm is effective.","PeriodicalId":178339,"journal":{"name":"IEEE WISA","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126575656","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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