Utilizing contextual ontological user profiles for personalized recommendations

As users may have different needs in different situations and contexts, it is increasingly important to consider user context data when filtering information. In the field of web personalization and recommender systems, most of the studies have focused on the process of modelling user profiles and the personalization process in order to provide personalized services to the user, but not on contextualized services. Rather limited attention has been paid to investigate how to discover, model, exploit and integrate context information in personalization systems in a generic way. In this paper, we aim at providing a novel model to build, exploit and integrate context information with a web personalization system. A context-aware personalization system (CAPS) is developed which is able to model and build contextual and personalized ontological user profiles based on the user’s interests and context information. These profiles are then exploited in order to infer and provide contextual recommendations to users. The methods and system developed are evaluated through a user study which shows that considering context information in web personalization systems can provide more effective personalization services and offer better recommendations to users.     

基于前后端日志记录的个性化推荐系统

为了有效地吸引和留住用户,提高网站服务的质量,在原有个性化实现技术基础上,提出了一种前后端日志相结合的方式存取用户浏览信息,对用户浏览站点的行为进行跟踪,为Web日志挖掘提供更精确有效的信息.结合前后端日志记录相结合的策略,提出了一个可伸缩的,独立于具体Web站点的页面推荐系统架构.实验分析结果表明,该方式能更准确全面的收集用户数据,同时个性化模块以一种非侵入的方式与系统集成,提高了系统的灵活性,方便系统重用.     

AdROSA—Adaptive personalization of web advertising

One of the greatest and most recent challenges for online advertising is the use of adaptive personalization at the same time that the Internet continues to grow as a global market. Most existing solutions to online advertising placement are based on demographic targeting or on information gained directly from the user. The AdROSA system for automatic web banner personalization, which integrates web usage and content mining techniques to reduce user input and to respect users’ privacy, is presented in the paper. Furthermore, certain advertising policies, important factors for both publishers and advertisers, are taken into consideration. The integration of all the relevant information is accomplished in one vector space to enable online and fully personalized advertising.     

Ontology-based mobile augmented reality in cultural heritage sites: information modeling and user study

Augmented reality (AR) has received much attention in the cultural heritage domain as an interactive medium for requesting and accessing information regarding heritage sites. In this study, we developed a mobile AR system based on Semantic Web technology to provide contextual information about cultural heritage sites. Most location-based AR systems are designed to present simple information about a point of interest (POI), but the proposed system offers information related to various aspects of cultural heritage, both tangible and intangible, linked to the POI. This is achieved via an information modeling framework where a cultural heritage ontology is used to aggregate heterogeneous data and semantically connect them with each other. We extracted cultural heritage data from five web databases and modeled contextual information for a target heritage site (Injeongjeon Hall and its vicinity in Changdeokgung Palace in South Korea) using the selected ontology. We then implemented a mobile AR application and conducted a user study to assess the learning and engagement impacts of the proposed system. We found that the application provides an agreeable user experience in terms of its affective, cognitive, and operative features. The results of our analysis showed that specific usage patterns were significant with regard to learning outcomes. Finally, we explored how the study’s key findings can provide practical design guidance for system designers to enhance mobile AR information systems for heritage sites, and to show system designers how to support particular usage patterns in order to accommodate specific user experiences better.

     

关于提取Web用户浏览行为特征的研究

当前,Web日志挖掘技术已成为实现网站个性化服务的研究热点.运用Markov模型来预测用户的浏览模式,从而提高站点访问率、为站点重组提供有利信息是该领域广泛采用的方法之一.但传统方法建立的Markov模型,存在着数据冗余复杂、模型庞大繁琐等问题.针对这些问题,介绍了一种改进的Markov模型.其方法主要是在原有模型的基础之上,在数据清洗、用户会话识别过程中删除一些不予考虑的因素,大大简化了建立的Markov模型,提高了Web日志挖掘的效率.     

Web页面信息主动检索模型

单个页面信息量远远大于特定用户对页面中的信息需求.为快速准确从当前页面中获取特定用户所需求的兴趣信息,提出了页面信息主动检索模型.该检索模型中,根据页面Block特点将当前Web页面转化成信息树,根据用户过去的浏览行为构造用户特征树,挖掘用户特征树产生用户需求信息集,然后从当前页面中检索需求的信息,获取用户兴趣信息集.详述了主动检索的基本原理,给出了相应的算法描述,并通过实验证明了该模型具有可行性.     

Web personalization for user acceptance of technology: An empirical investigation of E-government services

E-Commerce firms have adopted Web Personalization techniques extensively in the form of recommender systems for influencing user behavior for customer retention. Although there are numerous studies in this area, academic research addressing the role of Web Personalization in user acceptance of technology is very scant. Further, owing to the potential of recommender systems to attract and retain customers, most studies in web personalization have been done in E-Commerce setting. In this research, the ‘Consumer Acceptance and Use of Information Technology’ theory proposed in previous research has been extended to include web personalization as a moderator and has been tested in an E-Government context. Data collection involved conducting a laboratory experiment with the treatment group receiving personalized web forms for requesting an E-Government service. Our analyses show that personalizing the Web by self-reference and content relevance has a significant moderator role in influencing the relationship between determinants of intention to use and behavioral intention in certain cases.     

个性化服务中用户近期兴趣视图的生成

随着时间和环境的改变,Web用户的兴趣也会随之改变,在信息服务中应该能捕获到用户的这种近期兴趣变化以便能为用户提供更好的个性化服务。对现在描述网页的特征片技术中的关键词权重的计算做了改进以更加准确地描述网页,给出了利用行为分析得到网页兴趣度的方法,进而给出了根据某领域的标准分类树形成网页分类树,并最终生成能准确表示用户近期兴趣的兴趣视图的新方法。以此进行个性化推荐也更加有效。     

Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems

Personalization technologies offer powerful tools for enhancing the user experience in a wide variety of systems, but at the same time raise new privacy concerns. For example, systems that personalize advertisements according to the physical location of the user or according to the user??s friends?? search history, introduce new privacy risks that may discourage wide adoption of personalization technologies. This article analyzes the privacy risks associated with several current and prominent personalization trends, namely social-based personalization, behavioral profiling, and location-based personalization. We survey user attitudes towards privacy and personalization, as well as technologies that can help reduce privacy risks. We conclude with a discussion that frames risks and technical solutions in the intersection between personalization and privacy, as well as areas for further investigation. This frameworks can help designers and researchers to contextualize privacy challenges of solutions when designing personalization systems.     

DYNAMIC DISPLAY OF PERSONALIZED SOFTWARE FUNCTIONS

Generalized software packages endowed with a large spectrum of functionalities are often underutilized because users are not always aware of all the functionalities. It is hence desirable to display personalized information about the package. Though popular in web-based applications, personalization as a field of research in the design of generalized software packages is rare. This article develops a semi-Markov model of user navigation and an adaptive dynamic programming formulation to select high-utility software functions (states) for dynamically displaying them to a user. The personalization algorithm considers the interests of the software designers, the past users, and the current user. Frequency of visit to a state and the holding time in the state together determines the utility of the state. The personalization algorithm considers the interests of the software designers, the past users, and the current user. The algorithm is built in a demo package of ActiveX Servers and Controls. Graduate students tested the package. Pareto analysis and tests of hypothesis conducted on the test results indicate that the users did utilize the information on the displayed personalized software functions.     

Towards a contingency approach with whitelist- and blacklist-based anti-phishing applications: what do usability tests indicate?

In web browsers, a variety of anti-phishing tools and technologies are available to assist users to identify phishing attempts and potentially harmful pages. Such anti-phishing tools and technologies provide Internet users with essential information, such as warnings of spoofed pages. To determine how well users are able to recognise and identify phishing web pages with anti-phishing tools, we designed and conducted usability tests for two types of phishing-detection applications: blacklist-based and whitelist-based anti-phishing toolbars. The research results mainly indicate no significant performance differences between the application types. We also observed that, in many web browsing cases, a significant amount of useful and practical information for users is absent, such as information explaining professional web page security certificates. Such certificates are crucial in ensuring user privacy and protection. We also found other deficiencies in web identities in web pages and web browsers that present challenges to the design of anti-phishing toolbars. These challenges will require more professional, illustrative, instructional, and reliable information for users to facilitate user verification of the authenticity of web pages and their content.     

基于分类方法的Web站点实时个性化推荐

提出一种新的基于分类方法的实时个性化推荐方法，该文首先根据用户访问事务文法生成序列访问事务集，用于得到每个用户访问的序列特性并且便于分类器进行分类，然后利用该事务集训练一个多类分类器，作者通过推荐引擎得到每个用户的当前访问序列和用户当前请求页面，然后把该序列送入分类器进行分类，以得到用户的下面一些可能访问的页面，这些推荐页面的地址被附加到用户当前请求的页面的底部由推荐引擎返回以进行推荐，在这种方法中，用户不需要注册信息，推荐不打扰用户，可以为用户提供实时个性化的服务，实验表明这种方法是成功的。     

User-interface design for the Ripoll Monastery exhibition at the National Art Museum of Catalonia

Computer graphics and virtual reality technologies provide powerful tools for visualizing, documenting and disseminating cultural heritage. Virtual inspection tools have been used proficiently to show cultural artifacts either through the web or in museum exhibits. The usability of the user interface has been recognized to play a crucial role in overcoming the typical fearful attitude of the cultural heritage community towards 3D graphics. In this paper we discuss the design of the user interface for the virtual inspection of the impressive entrance of the Ripoll Monastery in Spain. The system was exhibited in the National Art Museum of Catalonia (MNAC) and it is now part of the Romanesque exhibition at the MAPFRE foundation. The MNAC is the third most visited art museum in Spain, and features the world's largest collection on Romanesque Art. We analyze the requirements from museum curators and discuss the main interface design decisions. The user interface combines (a) focus-plus-context visualization, with focus (detail view) and context (overview) being shown at separate displays, (b) touch-based camera control techniques, and (c) continuous feedback about the exact location of the detail area within the entrance. The interface allows users to aim the camera at any point of the entrance with centimeter accuracy using a single tap. We provide the results of a user study comparing our user interface with alternative approaches. We also discuss the benefits the exhibition had to the cultural heritage community.     

Web mining and privacy concerns: Some important legal issues to be consider before applying any data and information extraction technique in web-based environments

Web mining is a concept that gathers all techniques, methods and algorithms used to extract information and knowledge from data originating on the web (web data). A part of this technique aims to analyze the behavior of users in order to continuously improve both the structure and content of visited web sites. Behind this quite altruistic belief – namely, to help the user feel comfortable when they visit a site through a personalization process – there underlie a series of processing methodologies which operate at least arguably from the point of view of the users’ privacy.Thus, an important question arises; to what extent may the desire to improve the services offered through a web site infringe upon the privacy of those who visit it? The use of powerful processing tools such as those provided by web mining may threaten users’ privacy.Current legal scholarship on privacy issues suggests a flexible approach that enables the determination, within each particular context, of those behaviors that can threaten individual privacy. However, it has been observed that TIC professionals, with the purpose of formulating practical rules on this matter, have a very narrow-minded concept of privacy, primarily centered on the dichotomy between personal identifiable information (PII) and anonymous data.The aim of this paper is to adopt an integrative approach based on the distinctive attributes of web mining in order to determine which techniques and uses are harmful.     

Program transformations for information personalization

Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end-user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens, and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of hierarchical hypermedia, and providing supplemental interactions for improving the personalized experience. The primary form of personalization discussed is out-of-turn interaction—a technique which empowers a user navigating a hierarchical website to postpone clicking on any of the hyperlinks presented on the current page and, instead, communicate the label of a hyperlink nested deeper in the hierarchy. When the user supplies out-of-turn input we personalize the hierarchy to reflect the user's informational need. While viewing a website as a program and site transformation as program transformation is non-traditional, it offers a new way of thinking about personalized interaction, especially with hierarchical hypermedia. Our use of program transformations casts personalization in a formal setting and provides a systematic and implementation-neutral approach to designing systems. Moreover, this approach helped connect our work to human-computer dialog management and, in particular, mixed-initiative interaction. Putting personalized web interaction on a fundamentally different landscape gave birth to this new line of research. Relating concepts in the web domain (e.g., sites, interactions) to notions in the program-theoretic domain (e.g., programs, transformations) constitutes the creativity in this work.     

基于Web挖掘的个性化技术研究

针对用户特性向用户提供个性化服务已经成为Web技术的研究热点。Web挖掘是实现Web个性化服务的关键技术之一。研究了Web挖掘技术,阐述了Web挖掘技术存在的不足,并对应用Web挖掘技术实现个性化服务的发展前景进行了分析。     

Building a Knowledge Graph for the History of Vienna with Semantic MediaWiki

While research on semantic wikis is declining, Semantic MediaWiki (SMW) can still play an important role in the emerging field of knowledge graph curation.The Vienna History Wiki, a large knowledge base curated by the city government in collaboration with other institutions and the general public, provides an ideal use case for demonstrating strengths and weaknesses of SMW as well as discussing the challenges of co-curation in a cultural heritage setting. This paper describes processes like collaborative editing, interlinking unique identifiers on the web, sharing data with Wikidata, making use of Schema.org, and other ontologies. It presents insights from a user survey, access statistics, and a knowledge graph analysis.This work contributes to the scarce research in wiki usage outside of the Wikipedia ecosystem as well as to the field of community-based knowledge graph curation. The availability of a now significantly improved RDF representation indicates future directions for research and practice.     

Tag-based user modeling for social multi-device adaptive guides

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.