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Tag-based user modeling for social multi-device adaptive guides 总被引:2,自引:0,他引:2
Francesca Carmagnola Federica Cena Luca Console Omar Cortassa Cristina Gena Anna Goy Ilaria Torre Andrea Toso Fabiana Vernero 《User Modeling and User-Adapted Interaction》2008,18(5):497-538
This paper aims to demonstrate that the principles of adaptation and user modeling, especially social annotation, can be integrated
fruitfully with those of the web 2.0 paradigm and thereby enhance in the domain of cultural heritage. We propose a framework
for improving recommender systems through exploiting the users tagging activity. We maintain that web 2.0’s participative
features can be exploited by adaptive web-based systems in order to enrich and extend the user model, improve social navigation
and enrich information from a bottom-up perspective. Thus our approach stresses social annotation as a new and powerful kind
of feedback and as a way to infer knowledge about users. The prototype implementation of our framework in the domain of cultural
heritage is named iCITY. It is serving to demonstrate the validity of our approach and to highlight the benefits of this approach
specifically for cultural heritage. iCITY is an adaptive, social, multi-device recommender guide that provides information
about the cultural resources and events promoting the cultural heritage in the city of Torino. Our paper first describes this
system and then discusses the results of a set of evaluations that were carried out at different stages of the systems development
and aimed at validating the framework and implementation of this specific prototype. In particular, we carried out a heuristic
evaluation and two sets of usability tests, aimed at checking the usability of the user interface, specifically of the adaptive
behavior of the system. Moreover, we conducted evaluations aimed at investigating the role of tags in the definition of the
user model and the impact of tags on the accuracy of recommendations. Our results are encouraging.
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Fabiana VerneroEmail: |
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《Advanced Engineering Informatics》2004,18(3):129-142
The paper proposes an adaptive web system—that is, a website that is capable of changing its original design to fit user requirements. For the purpose of improving shortcomings of the website, and also to make it much easier for users to access information, the system analyzes user browsing patterns from their access records. This paper concentrates on the operating-efficiency of a website—that is, the efficiency with which a group of users browse a website. By achieving high efficiency, users spend less operating cost to accomplish a desired user goal. Based on user access data, we analyze each user's operating activities as well as their browsing sequences. With this data, we can calculate a measure of the efficiency of the user's browsing sequences. The paper develops an algorithm to accurately calculate this efficiency and to suggest how to increase the efficiency of user operations. This can be achieved in two ways: (i) by adding a new link between two web pages, or (ii) by suggesting to designers to reconsider existing inefficient links so as to allow users to arrive at their target pages more quickly. Using this algorithm, we develop a prototype to prove the concept of efficiency. The implementation is an adaptive website system to automatically change the website architecture according to user browsing activities and to improve website usability from the viewpoint of efficiency. 相似文献
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Andy Smith Lynne Dunckley Tim French Shailey Minocha Yu Chang 《Interacting with computers》2012,24(4):174-187
In this paper we present a process model for developing usable cross-cultural websites. Compatible with ISO 13407, the process model documents an abstraction of the design process focusing on cultural issues in development. It provides a framework in which a variety of user-based and expert-based techniques for analysis and design are placed within the life-cycle of website development. In developing the model, we relate practical approaches to design with theories and models of culture and discuss the relevance of such theories to the practical design process. In particular we focus on four key concerns: how an audit of local website attractors can inform the design process; the concept of a cultural fingerprint to contrast websites with the cultural needs of local users; the problems associated with user evaluation; and cross-cultural team development. We then show their relation to our process model. We conclude by summarising our contribution to date within the field. 相似文献
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Understanding relationships between people and organizations by reading newspaper articles is difficult to manage for humans due to the large amount of data. To address this problem, we present and evaluate a new visual analytics system, which offers interactive exploration and tagging of social networks extracted from newspapers. For the visual exploration of the network, we extract “interesting” neighbourhoods of nodes, using a new degree of interest (DOI) measure based on edges instead of nodes. It improves the seminal definition of DOI, which we find to produce the same “globally interesting” neighbourhoods in our use case, regardless of the query. Our approach allows answering different user queries appropriately, avoiding uniform search results. We propose a user‐driven pattern‐based classifier for discovery and tagging of non‐taxonomic semantic relations. Our approach does not require any a‐priori user knowledge, such as expertise in syntax or pattern creation. An evaluation shows that our classifier is capable of identifying known lexico‐syntactic patterns as well as various domain‐specific patters. Our classifier yields good results already with a small amount of training, and continuously improves through user feedback. We conduct a user study to evaluate whether our visual interactive system has an impact on how users tag relationships, as compared to traditional text‐based interfaces. Study results suggest that users of the visual system tend to tag more concisely, avoiding too abstract or overly specific relationship labels. 相似文献
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We propose a user model to support personalized learning paths through online material. Our approach is a variant of student modeling using the computer tutoring concept of knowledge tracing. Knowledge tracing involves representing the knowledge required to master a domain, and, from traces of online user behavior, diagnosing user knowledge states as a profile over those elements. The user model is induced from documents tagged by an expert in a social tagging system. Tags identified with “expertise” in a domain can be used to identify a corpus of domain documents. That corpus can be fed to an automated process that distills a topic model representation characteristic of the domain. As a learner navigates and reads online material, inferences can be made about the degree to which topics in the target domain have been learned. We validate this knowledge tracing approach against data from a social tagging study. As part of this evaluation, we match the predictions of the knowledge-tracing model to individual participant responses made to individual question items used to test domain knowledge. 相似文献
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While recent progress has been achieved in understanding the structure and dynamics of social tagging systems, we know little about the underlying user motivations for tagging, and how they influence resulting folksonomies and tags. This paper addresses three issues related to this question. (1) What distinctions of user motivations are identified by previous research, and in what ways are the motivations of users amenable to quantitative analysis? (2) To what extent does tagging motivation vary across different social tagging systems? (3) How does variability in user motivation influence resulting tags and folksonomies? In this paper, we present measures to detect whether a tagger is primarily motivated by categorizing or describing resources, and apply these measures to datasets from seven different tagging systems. Our results show that (a) users’ motivation for tagging varies not only across, but also within tagging systems, and that (b) tag agreement among users who are motivated by categorizing resources is significantly lower than among users who are motivated by describing resources. Our findings are relevant for (1) the development of tag-based user interfaces, (2) the analysis of tag semantics and (3) the design of search algorithms for social tagging systems. 相似文献
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While recent progress has been achieved in understanding the structure and dynamics of social tagging systems, we know little about the underlying user motivations for tagging, and how they influence resulting folksonomies and tags. This paper addresses three issues related to this question. (1) What distinctions of user motivations are identified by previous research, and in what ways are the motivations of users amenable to quantitative analysis? (2) To what extent does tagging motivation vary across different social tagging systems? (3) How does variability in user motivation influence resulting tags and folksonomies? In this paper, we present measures to detect whether a tagger is primarily motivated by categorizing or describing resources, and apply these measures to datasets from seven different tagging systems. Our results show that (a) users’ motivation for tagging varies not only across, but also within tagging systems, and that (b) tag agreement among users who are motivated by categorizing resources is significantly lower than among users who are motivated by describing resources. Our findings are relevant for (1) the development of tag-based user interfaces, (2) the analysis of tag semantics and (3) the design of search algorithms for social tagging systems. 相似文献
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Development of an Adaptive EC Website With Online Identified Cognitive Styles of Anonymous Customers
This study developed an adaptive electronic commerce (EC) website based on users' cognitive styles without asking users to complete any evaluation forms. In this system, a multilayer feed forward neural network (MLFF) was designed to identify the cognitive styles of anonymous users by observing their browsing behavior. Then the system presented the adaptive interfaces, designed by investigating the relationships between users' cognitive styles and browsing behavior, to users based on the identified cognitive styles. Experiments were conducted to evaluate the effectiveness of the system. The experimental results verified the potential benefits of MLFF in identifying anonymous users' cognitive styles during browsing of EC applications and provided evidence that an adaptive EC website that presents product data consistent with the users' cognitive styles can be beneficial to one-to-one Internet marketing not only for users whose cognitive styles are known before browsing but also for anonymous users whose cognitive styles are identified during browsing. 相似文献
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This paper presents research on the development of a domain ontology adaptation system for personalized knowledge search and recommendation that adapts a suitable domain ontology according to the previous browsing and reading behavior of users (i.e., usage history log). An adaptive domain ontology can satisfy the future requirements of users and promote use value. In developing the system, a domain ontology adaptation model is first designed. Based on the designed adaptation model, a methodology for domain ontology adaptation is developed. Subsequently, a domain ontology adaptation system is implemented with an illustrative example of securities trading. Finally, a system evaluation for user satisfaction and a methodology evaluation are conducted to demonstrate that the developed methodology and system worked efficiently. 相似文献
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Learning can benefit from the modern Web structure through the convergence of top‐down encyclopedic institutional knowledge and bottom‐up user‐generated annotations. A promising approach to such convergence consists in leveraging the social functionalities in 3.0 executable environments through the recommendation of tags with the mediation of lexical and semantic resources. This paper addresses such issues through the design and evaluation of a tag recommendation system in a Web 3.0 Web portal, ‘150 Digit’. Designed for schools, 150 Digit encourages students and teachers to interact with a set of four exhibitions on the historical and social aspects of the Italian unification process in a virtual environment. The website displays the exhibits and their related documents promoting the users' active participation through tagging, voting and commenting on the exhibits. Tags become a way for students to create and explore new relations among the site contents, orthogonal to the institutional viewpoint. In this paper, we illustrate the recommendation strategy incorporated in 150 Digit, which relies on a semantic middleware to mediate between the input expressed by the users through tags and the top‐down institutional classification provided by the curators of the exhibitions. Following this, we describe the evaluation process conducted in a real experimental setting and discuss the evaluation results and their implications for learning environments. 相似文献
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Dianne Cyr 《Electronic Commerce Research and Applications》2013,12(6):373-385
User perceptions of website design (for Information Content, Information Design, Navigation Design, Visual Design), Website Trust, and Transaction Security are examined for differences in an eight country sample. Motivation for the investigation includes: (1) to test and compare user reactions to website design in countries with different degrees of uncertainty avoidance, (2) to consider user reactions based on country economic and technological conditions related to the theory of institutional trust and social capital, and (3) to extend clustering theory and the GLOBE cultural cluster model to determine if culturally similar countries group regarding user perceptions of websites. Overall and as predicted, users in low uncertainty avoidance, high institutional trust and social capital countries such as Canada and the USA have the most favorable perceptions of website design. An interesting finding is that while country economic and technological conditions may temper user perceptions in some instances, overall culture is a stronger predictor. Clustering theory is a useful determinant of user perceptions, and there is strong support that users within a given cultural cluster have similar requirements regarding website design. 相似文献
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In recent years,there is a fast proliferation of collaborative tagging(a.k.a.folksonomy) systems in Web 2.0 communities.With the increasingly large amount of data,how to assist users in searching their interested resources by utilizing these semantic tags becomes a crucial problem.Collaborative tagging systems provide an environment for users to annotate resources,and most users give annotations according to their perspectives or feelings.However,users may have different perspectives or feelings on resources,e.g.,some of them may share similar perspectives yet have a conflict with others.Thus,modeling the profile of a resource based on tags given by all users who have annotated the resource is neither suitable nor reasonable.We propose,to tackle this problem in this paper,a community-aware approach to constructing resource profiles via social filtering.In order to discover user communities,three different strategies are devised and discussed.Moreover,we present a personalized search approach by combining a switching fusion method and a revised needs-relevance function,to optimize personalized resources ranking based on user preferences and user issued query.We conduct experiments on a collected real life dataset by comparing the performance of our proposed approach and baseline methods.The experimental results verify our observations and effectiveness of proposed method. 相似文献
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User participation emerged as a critical issue for collaborative and social recommender systems as well as for a range of other systems based on the power of user community. A range of mechanisms to encourage user participation in social systems has been proposed over the last few years; however, the impact of these mechanisms on users behavior in recommender systems has not been studied sufficiently. This paper investigates the impact of encouraging user participation in the context of CourseAgent, a community-based course recommender system. The recommendation power of CourseAgent is based on course ratings provided by a community of students. To increase the number of course ratings, CourseAgent applies an incentive mechanism which turns user feedback into a self-beneficial activity. In this paper, we describe the design and implementation of our course recommendation system and its incentive mechanism. We also report a dual impact of this mechanism on user behavior discovered in two user studies. 相似文献
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In-depth analysis of user interactions with applications in large systems is widely adopted as a means to understand user’s behavior for strategic purposes such as fraud detection, system security, weblog analysis, social networking, and customer relationship management. Overall, the user behavior presents characteristics, relationships, structures, and effects of a sequence of actions in a specific application domain. The interaction of users with applications at the business-level generates events that make the elements of the user behavior. Formal modelling and representation of complex patterns of user actions using expressive languages are critical aspects of behavior analysis. We present a model to describe the behavior elements and their relationships. The model also provides a systematic mechanism for describing and presenting events, sequence of events, and complex behavior patterns. A behavior pattern can be defined as a sequence of typed events that occur during specific time intervals. An event consists of a tuple of attributes whose values represent an observation of the behavior. In this paper, first we define a semantic model of the user behavior to address the issues around the user behavior representation, and then we present syntax and semantics of a generic Behavior Pattern Language (BPL), which enables the analysts to define a variety of complex behavior patterns in a declarative manner. We present the feasibility of the approach through several examples of complex behavior patterns expressed using the proposed language. 相似文献
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The user experience of current P2P Personal and Social networking systems does not meet the usability needs of the technically naïve users. This is the motivation behind MyNet, a P2P platform that enables non-expert users to easily organize their resources and share them in their immediate social neighborhood. In this paper, we present our experience following a user-centered approach in designing MyNet: using real-world metaphors in the core system, leveraging NFC-based touch to mirror human behavior models, and involving actual users in the design process. The results of our 50-user usability evaluation are also presented in detail. 相似文献
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推荐系统的冷启动问题是近期的研究热点,而用户的活跃性判定是冷启动问题的基础。已有方法在判定用户的活跃性时,单纯地考虑了用户发表信息量,对社交媒体的社交关系及行为等特征利用不够。该文面向微博网络,提出了系统的用户活跃性判定方法,创新性主要体现在: (1)提出了微博网络影响用户活跃性的四类指标,包括用户背景、社交关系、发表内容质量及社交行为,避免了仅仅使用用户发表信息数量判定用户是否活跃的粗糙方式;(2)提出了用户活跃性判定流程,提出了基于四类指标的用户与用户集的差异度计算模型。以新浪微博为例,选取了学术研究、企业管理、教育、文化、军事五个领域的900个用户作为测试集,使用准确率P、召回率R及F值为评价指标,进行了实验分析和比较。结果显示,该文所提用户活跃性判定方法的准确率P、召回率R、F值比传统的判定方法分别提高了21%、13%和16%,将该文所提方法用于用户推荐,得到的P、R和F值比最新的方法分别提高了5%、2%和3%,验证了所提方法的有效性。 相似文献