User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation re...User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation regarding to each user;2) Group adaptation focusing on group of users. To support group adaptation, the basic problem which needs to be solved is how to create user groups. This relates to clustering techniques so as to cluster user models because a group is considered as a cluster of similar user models. In this paper we discuss two clustering algorithms: k-means and k-medoids and also propose dissimilarity measures and similarity measures which are applied into different structures (forms) of user models like vector, overlay, and Bayesian network.展开更多
In this paper we describe UMIS, a service architecture that enables user adaptive applications to exchange User Model data on the Web. UMIS provides a set of facilities that allow applications to interoperate with min...In this paper we describe UMIS, a service architecture that enables user adaptive applications to exchange User Model data on the Web. UMIS provides a set of facilities that allow applications to interoperate with minimum changes in their internal logics and knowledge representation. The goal is to support the process of interoperability in three ways: providing an efficient centralized discovery service;offering a service for simple interaction for the exchange of UM value in a p2p way;and offering a negotiation mechanism to be used in case of communication hurdles (i.e. semantic ambiguities and missing response). We developed a proof-of-concept prototype of UMIS and we tested it with an existing user-adaptive application. According to our test results, our approach improves the communication with respect to standard solutions for interoperability regarding the quality of exchange, with a negligible impact on the communication costs and traffic generation.展开更多
In this paper, we present a novel approach to model user request patterns in the World Wide Web. Instead of focusing on the user traffic for web pages, we capture the user interaction at the object level of the web pa...In this paper, we present a novel approach to model user request patterns in the World Wide Web. Instead of focusing on the user traffic for web pages, we capture the user interaction at the object level of the web pages. Our framework model consists of three sub-models: one for user file access, one for web pages, and one for storage servers. Web pages are assumed to consist of different types and sizes of objects, which are characterized using several categories: articles, media, and mosaics. The model is implemented with a discrete event simulation and then used to investigate the performance of our system over a variety of parameters in our model. Our performance measure of choice is mean response time and by varying the composition of web pages through our categories, we find that our framework model is able to capture a wide range of conditions that serve as a basis for generating a variety of user request patterns. In addition, we are able to establish a set of parameters that can be used as base cases. One of the goals of this research is for the framework model to be general enough that the parameters can be varied such that it can serve as input for investigating other distributed applications that require the generation of user request access patterns.展开更多
The User Interface Transition Diagram (UITD) is a formal modeling notation that simplifies the specification and design of user-system interactions. It is a valuable communication tool for technical and non-technical ...The User Interface Transition Diagram (UITD) is a formal modeling notation that simplifies the specification and design of user-system interactions. It is a valuable communication tool for technical and non-technical stakeholders during the requirements elicitation phase, as it provides a simple yet technically complete notation that is easy to understand. In this paper, we investigated the efficiency of creating UITDs using draw.io, a widely used diagramming software, compared to a dedicated UITD editor. We conducted a study to compare the time required to use each tool to complete the task of creating a medium size UITD, as well as the subjective ease of use and satisfaction of participants with the dedicated Editor. Our results show that the UITD editor is more efficient and preferred by participants, highlighting the importance of using specialized tools for creating formal models such as UITDs. The findings of this study have implications for software developers, designers, and other stakeholders involved in the specification and design of user-system interactions.展开更多
Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a to...Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a topic mining model based on Latent Dirichlet Allocation(LDA) named user-topic model.For each user,the interests are divided into two parts by different ways to generate the microblogs:original interest and retweet interest.We represent a Gibbs sampling implementation for inference the parameters of our model,and discover not only user's original interest,but also retweet interest.Then we combine original interest and retweet interest to compute interest words for users.Experiments on a dataset of Sina microblogs demonstrate that our model is able to discover user interest effectively and outperforms existing topic models in this task.And we find that original interest and retweet interest are similar and the topics of interest contain user labels.The interest words discovered by our model reflect user labels,but range is much broader.展开更多
At present, how to enable Search Engine to construct user personal interest model initially, master user's personalized information timely and provide personalized services accurately have become the hotspot in the r...At present, how to enable Search Engine to construct user personal interest model initially, master user's personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model's construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model (UIM) is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile (UIP) are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.展开更多
To evaluate the trail potential of converged heterogeneous network (CHN) market, the logistic method for adoption modeling of CHN is used. User growth & penetration have been taken as two variants to find saturatio...To evaluate the trail potential of converged heterogeneous network (CHN) market, the logistic method for adoption modeling of CHN is used. User growth & penetration have been taken as two variants to find saturation condition in market. Model is continuous in time but modifications are done for discrete recurrence equation, commonly known as logistic map. Dynamic and static phases are taken into consideration while penetration decay is not covered in this model.展开更多
A new method to evaluate fuzzily user's relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method f...A new method to evaluate fuzzily user's relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval (PIR) system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.展开更多
We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user inter...We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuurn. In some sense, specific interests correspond to shortterm interests, while general interests correspond to longterm interests. So this representation more really reflects the users' interests. The algorithm can automatically model a us er's multiple interest domains, dynamically generate the in terest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.展开更多
In agent-based automated negotiation research area,a key problem is how to make software agent more adaptable to represent user preferences or suggestions,so that agent can take further proposals that reflect user req...In agent-based automated negotiation research area,a key problem is how to make software agent more adaptable to represent user preferences or suggestions,so that agent can take further proposals that reflect user requirements to implement ecommerce activities like automated transactions.The difficulty lies in the uncertainty of user preferences that include uncertain description and contents,non-linear and dynamic variability.In this paper,fuzzy language was used to describe the uncertainty and combine with multiple classified artificial neural networks(ANNs) for self-adaptive learning of user preferences.The refinement learning results of various negotiation contracts' satisfaction degrees in the extent of fuzzy classification can be achieved.Compared to unclassified computation,the experimental results illustrate that the learning ability and effectiveness of agents have been improved.展开更多
A critical component of the smart grid (SG) infrastructure is the embedded communications network, where an important objective of the latter is the expansion of its throughput, in conjunction with the satisfaction of...A critical component of the smart grid (SG) infrastructure is the embedded communications network, where an important objective of the latter is the expansion of its throughput, in conjunction with the satisfaction of specified latency and accuracy requirements. For the effective design of the communications network, the user and traffic profiles, such as known-user vs. unknown-user populations and bursty vs. non-bursty data traffics, must be carefully considered and subsequently modeled. This paper relates user and traffic models to the deployment of effective multiple access transmission algorithms in the communications network of the SG.展开更多
Blogs have permeated into our daily lives at a fast speed, and various kinds of blog spaces have attracted our attention. However, little effort has been made on studying the users' motivation to participate in bl...Blogs have permeated into our daily lives at a fast speed, and various kinds of blog spaces have attracted our attention. However, little effort has been made on studying the users' motivation to participate in blog activities. This paper aims to construct a theoretical model about the blog adoption based on technology acceptance model(TAM theory), social capital theory and social exchange theory, and put forward 18 related hypotheses. Then the survey method is adopted to analyze the data from 208 questionnaires using the SPSS and LISREL tools, and to examine the theoretical model and hypotheses. Finally, the paper makes a discussion from five aspects due to the results of data analysis, including individual driving factors, group driving factors, community driving factors, technology acceptance factors and moderating variables. The results show that curiosity/enjoyment, user's experience, social interaction and social identification will greatly affect users' motivation to accept a blog; meanwhile, perceived ease of use, exchange cost and trust will partially influence users' intention to participate in blog activities. The results also suggest that age and education degrees have significant moderating effects on users' acceptance and updating of blogs.展开更多
On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of the...On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of their convenience,information quality,personalization and site aesthetics,which may affect the overall satisfaction of users.Statistical analysis was also made to build a user satisfaction-based quality evaluation system of network information service.展开更多
文摘User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation regarding to each user;2) Group adaptation focusing on group of users. To support group adaptation, the basic problem which needs to be solved is how to create user groups. This relates to clustering techniques so as to cluster user models because a group is considered as a cluster of similar user models. In this paper we discuss two clustering algorithms: k-means and k-medoids and also propose dissimilarity measures and similarity measures which are applied into different structures (forms) of user models like vector, overlay, and Bayesian network.
文摘In this paper we describe UMIS, a service architecture that enables user adaptive applications to exchange User Model data on the Web. UMIS provides a set of facilities that allow applications to interoperate with minimum changes in their internal logics and knowledge representation. The goal is to support the process of interoperability in three ways: providing an efficient centralized discovery service;offering a service for simple interaction for the exchange of UM value in a p2p way;and offering a negotiation mechanism to be used in case of communication hurdles (i.e. semantic ambiguities and missing response). We developed a proof-of-concept prototype of UMIS and we tested it with an existing user-adaptive application. According to our test results, our approach improves the communication with respect to standard solutions for interoperability regarding the quality of exchange, with a negligible impact on the communication costs and traffic generation.
文摘In this paper, we present a novel approach to model user request patterns in the World Wide Web. Instead of focusing on the user traffic for web pages, we capture the user interaction at the object level of the web pages. Our framework model consists of three sub-models: one for user file access, one for web pages, and one for storage servers. Web pages are assumed to consist of different types and sizes of objects, which are characterized using several categories: articles, media, and mosaics. The model is implemented with a discrete event simulation and then used to investigate the performance of our system over a variety of parameters in our model. Our performance measure of choice is mean response time and by varying the composition of web pages through our categories, we find that our framework model is able to capture a wide range of conditions that serve as a basis for generating a variety of user request patterns. In addition, we are able to establish a set of parameters that can be used as base cases. One of the goals of this research is for the framework model to be general enough that the parameters can be varied such that it can serve as input for investigating other distributed applications that require the generation of user request access patterns.
文摘The User Interface Transition Diagram (UITD) is a formal modeling notation that simplifies the specification and design of user-system interactions. It is a valuable communication tool for technical and non-technical stakeholders during the requirements elicitation phase, as it provides a simple yet technically complete notation that is easy to understand. In this paper, we investigated the efficiency of creating UITDs using draw.io, a widely used diagramming software, compared to a dedicated UITD editor. We conducted a study to compare the time required to use each tool to complete the task of creating a medium size UITD, as well as the subjective ease of use and satisfaction of participants with the dedicated Editor. Our results show that the UITD editor is more efficient and preferred by participants, highlighting the importance of using specialized tools for creating formal models such as UITDs. The findings of this study have implications for software developers, designers, and other stakeholders involved in the specification and design of user-system interactions.
基金This work was supported by the National High Technology Research and Development Program of China(No. 2010AA012505, 2011AA010702, 2012AA01A401 and 2012AA01A402), Chinese National Science Foundation (No. 60933005, 91124002,61303265), National Technology Support Foundation (No. 2012BAH38B04) and National 242 Foundation (No. 2011A010)
文摘Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a topic mining model based on Latent Dirichlet Allocation(LDA) named user-topic model.For each user,the interests are divided into two parts by different ways to generate the microblogs:original interest and retweet interest.We represent a Gibbs sampling implementation for inference the parameters of our model,and discover not only user's original interest,but also retweet interest.Then we combine original interest and retweet interest to compute interest words for users.Experiments on a dataset of Sina microblogs demonstrate that our model is able to discover user interest effectively and outperforms existing topic models in this task.And we find that original interest and retweet interest are similar and the topics of interest contain user labels.The interest words discovered by our model reflect user labels,but range is much broader.
基金Supported by the National Natural Science Foundation of China (50674086)the Doctoral Foundation of Ministry of Education of China (20060290508)the Youth Scientific Research Foundation of CUMT (0D060125)
文摘At present, how to enable Search Engine to construct user personal interest model initially, master user's personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model's construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model (UIM) is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile (UIP) are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.
基金Supported by the National Natural Science Foundation of China(60772066)
文摘To evaluate the trail potential of converged heterogeneous network (CHN) market, the logistic method for adoption modeling of CHN is used. User growth & penetration have been taken as two variants to find saturation condition in market. Model is continuous in time but modifications are done for discrete recurrence equation, commonly known as logistic map. Dynamic and static phases are taken into consideration while penetration decay is not covered in this model.
文摘A new method to evaluate fuzzily user's relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval (PIR) system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.
基金Supported by the National Natural Science Funda-tion of China (69973012 ,60273080)
文摘We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuurn. In some sense, specific interests correspond to shortterm interests, while general interests correspond to longterm interests. So this representation more really reflects the users' interests. The algorithm can automatically model a us er's multiple interest domains, dynamically generate the in terest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.
基金National Natural Science Foundation of China (No. 70631003)
文摘In agent-based automated negotiation research area,a key problem is how to make software agent more adaptable to represent user preferences or suggestions,so that agent can take further proposals that reflect user requirements to implement ecommerce activities like automated transactions.The difficulty lies in the uncertainty of user preferences that include uncertain description and contents,non-linear and dynamic variability.In this paper,fuzzy language was used to describe the uncertainty and combine with multiple classified artificial neural networks(ANNs) for self-adaptive learning of user preferences.The refinement learning results of various negotiation contracts' satisfaction degrees in the extent of fuzzy classification can be achieved.Compared to unclassified computation,the experimental results illustrate that the learning ability and effectiveness of agents have been improved.
文摘A critical component of the smart grid (SG) infrastructure is the embedded communications network, where an important objective of the latter is the expansion of its throughput, in conjunction with the satisfaction of specified latency and accuracy requirements. For the effective design of the communications network, the user and traffic profiles, such as known-user vs. unknown-user populations and bursty vs. non-bursty data traffics, must be carefully considered and subsequently modeled. This paper relates user and traffic models to the deployment of effective multiple access transmission algorithms in the communications network of the SG.
文摘Blogs have permeated into our daily lives at a fast speed, and various kinds of blog spaces have attracted our attention. However, little effort has been made on studying the users' motivation to participate in blog activities. This paper aims to construct a theoretical model about the blog adoption based on technology acceptance model(TAM theory), social capital theory and social exchange theory, and put forward 18 related hypotheses. Then the survey method is adopted to analyze the data from 208 questionnaires using the SPSS and LISREL tools, and to examine the theoretical model and hypotheses. Finally, the paper makes a discussion from five aspects due to the results of data analysis, including individual driving factors, group driving factors, community driving factors, technology acceptance factors and moderating variables. The results show that curiosity/enjoyment, user's experience, social interaction and social identification will greatly affect users' motivation to accept a blog; meanwhile, perceived ease of use, exchange cost and trust will partially influence users' intention to participate in blog activities. The results also suggest that age and education degrees have significant moderating effects on users' acceptance and updating of blogs.
基金supported by the Ministry of Education of China(Grant No.06JJD870006)
文摘On the basis of user satisfaction,authors made research hypotheses by learning from relevant e-service quality evaluation models.A questionnaire survey was then conducted on some content-based websites in terms of their convenience,information quality,personalization and site aesthetics,which may affect the overall satisfaction of users.Statistical analysis was also made to build a user satisfaction-based quality evaluation system of network information service.